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  • Published: 27 October 2017

Montessori education: a review of the evidence base

  • Chloë Marshall 1  

npj Science of Learning volume  2 , Article number:  11 ( 2017 ) Cite this article

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The Montessori educational method has existed for over 100 years, but evaluations of its effectiveness are scarce. This review paper has three aims, namely to (1) identify some key elements of the method, (2) review existing evaluations of Montessori education, and (3) review studies that do not explicitly evaluate Montessori education but which evaluate the key elements identified in (1). The goal of the paper is therefore to provide a review of the evidence base for Montessori education, with the dual aspirations of stimulating future research and helping teachers to better understand whether and why Montessori education might be effective.

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Introduction

Maria Montessori (1870–1952) was by any measure an extraordinary individual. She initially resisted going into teaching—one of the few professions available to women in the late 19th century—and instead became one of the very first women to qualify as a medical doctor in Italy. As a doctor she specialised in psychiatry and paediatrics. While working with children with intellectual disabilities she gained the important insight that in order to learn, they required not medical treatment but rather an appropriate pedagogy. In 1900, she was given the opportunity to begin developing her pedagogy when she was appointed director of an Orthophrenic school for developmentally disabled children in Rome. When her pupils did as well in their exams as typically developing pupils and praise was lavished upon her for this achievement, she did not lap up that praise; rather, she wondered what it was about the education system in Italy that was failing children without disabilities. What was holding them back and preventing them from reaching their potential? In 1907 she had the opportunity to start working with non-disabled children in a housing project located in a slum district of Rome. There, she set up her first 'Casa dei Bambini' ('children’s house') for 3–7-year olds. She continued to develop her distinctive pedagogy based on a scientific approach of experimentation and observation. On the basis of this work, she argued that children pass through sensitive periods for learning and several stages of development, and that children’s self-construction can be fostered through engaging with self-directed activities in a specially prepared environment. There was international interest in this new way of teaching, and there are now thousands of Montessori schools (predominantly for children aged 3–6 and 6–12) throughout the world. 1 , 2 , 3 , 4

Central to Montessori’s method of education is the dynamic triad of child, teacher and environment. One of the teacher’s roles is to guide the child through what Montessori termed the 'prepared environment, i.e., a classroom and a way of learning that are designed to support the child’s intellectual, physical, emotional and social development through active exploration, choice and independent learning. One way of making sense of the Montessori method for the purposes of this review is to consider two of its important aspects: the learning materials, and the way in which the teacher and the design of the prepared environment promote children’s self-directed engagement with those materials. With respect to the learning materials, Montessori developed a set of manipulable objects designed to support children’s learning of sensorial concepts such as dimension, colour, shape and texture, and academic concepts of mathematics, literacy, science, geography and history. With respect to engagement, children learn by engaging hands-on with the materials most often individually, but also in pairs or small groups, during a 3-h 'work cycle' in which they are guided by the teacher to choose their own activities. They are given the freedom to choose what they work on, where they work, with whom they work, and for how long they work on any particular activity, all within the limits of the class rules. No competition is set up between children, and there is no system of extrinsic rewards or punishments. These two aspects—the learning materials themselves, and the nature of the learning—make Montessori classrooms look strikingly different to conventional classrooms.

It should be noted that for Montessori the goal of education is to allow the child’s optimal development (intellectual, physical, emotional and social) to unfold. 2 This is a very different goal to that of most education systems today, where the focus is on attainment in academic subjects such as literacy and mathematics. Thus when we ask the question, as this review paper does, whether children benefit more from a Montessori education than from a non-Montessori education, we need to bear in mind that the outcome measures used to capture effectiveness do not necessarily measure the things that Montessori deemed most important in education. Teachers and parents who choose the Montessori method may choose it for reasons that are not so amenable to evaluation.

Despite its existence for over 100 years, peer-reviewed evaluations of Montessori education are few and they suffer from a number of methodological limitations, as will be discussed in Section 3. This review has three aims, namely to (1) identify some key elements of the Montessori educational method, (2) review existing evaluations of Montessori education, and (3) review studies that do not explicitly evaluate Montessori education but which evaluate the key elements identified in (1). My goal is to provide a review of the scientific evidence base for Montessori education, with the dual aspirations of stimulating future research and helping teachers to better understand whether and why Montessori education might be effective.

Some key elements of the Montessori educational method

The goal of this section is to isolate some key elements of the Montessori method, in order to better understand why, if Montessori education is effective, this might be, and what elements of it might usefully be evaluated by researchers. These are important considerations because there is considerable variability in how the Montessori method is implemented in different schools, and the name, which is not copyrighted, is frequently used without full adherence. 5 , 6 Nevertheless, some elements of the method might still be beneficial, or could be successfully incorporated (or, indeed, are already incorporated) into schools that do not want to carry the name 'Montessori' or to adhere fully to its principles. Pinpointing more precisely what—if anything—about the Montessori method is effective will enable a better understanding of why it works. Furthermore, it has been argued that there might be dangers in adopting wholesale and uncritically an educational method that originated over 100 years ago, in a world that was different in many ways to today’s. 7 If the method is to be adopted piecemeal, which pieces should be adopted? As outlined previously, two important aspects of Montessori’s educational method are the learning materials, and the self-directed nature of children’s engagement with those materials. Some key elements of each of these aspects will now be considered in turn.

The learning materials

The first learning materials that the child is likely to encounter in the Montessori classroom are those that make up the practical life curriculum. These are activities that involve pouring different materials, using utensils such as scissors, tongs and tweezers, cleaning and polishing, preparing snacks, laying the table and washing dishes, arranging flowers, gardening, doing up and undoing clothes fastenings, and so on. Their aims, in addition to developing the child’s skills for independent living, are to build up the child’s gross and fine motor control and eye-hand co-ordination, to introduce them to the cycle of selecting, initiating, completing and tidying up an activity (of which more in the next section), and to introduce the rules for functioning in the social setting of the classroom.

As the child settles into the cycle of work and shows the ability to focus on self-selected activities, the teacher will introduce the sensorial materials. The key feature of the sensorial materials is that each isolates just one concept for the child to focus on. The pink tower, for example, consists of ten cubes which differ only in their dimensions, the smallest being 1 cm 3 , the largest 10 cm 3 . In building the tower the child’s attention is being focused solely on the regular decrease in volume of successive cubes. There are no additional cues—different colours for example, or numbers written onto the faces of the cube—which might help the child to sequence the cubes accurately. Another piece of sensorial material, the sound boxes, contains six pairs of closed cylinders that vary in sound from soft to loud when shaken, and the task for the child is to find the matching pairs. Again, there is only one cue that the child can use to do this task: sound. The aim of the sensorial materials is not to bombard the child’s senses with stimuli; on the contrary, they are tools designed for enabling the child to classify and put names to the stimuli that he will encounter on an everyday basis.

The sensorial materials, are, furthermore, designed as preparation for academic subjects. The long rods, which comprise ten red rods varying solely in length in 10 cm increments from 10 cm to 1 m, have an equivalent in the mathematics materials: the number rods, where the rods are divided into alternating 10 cm sections of red and blue so that they take on the numerical values 1–10. The touchboards, which consist of alternate strips of sandpaper and smooth paper for the child to feel, are preparation for the sandpaper globe in geography—a globe where the land masses are made of rough sandpaper but the oceans and seas are smooth. The touchboards are also preparation for the sandpaper letters in literacy and sandpaper numerals in mathematics, which the child learns to trace with his index and middle fingers.

Key elements of the literacy curriculum include the introduction of writing before reading, the breaking down of the constituent skills of writing (pencil control, letter formation, spelling) before the child actually writes words on paper, and the use of phonics for teaching sound-letter correspondences. Grammar—parts of speech, morphology, sentence structure—are taught systematically through teacher and child-made materials.

In the mathematics curriculum, quantities 0–10 and their symbols are introduced separately before being combined, and large quantities and symbols (tens, hundreds and thousands) and fractions are introduced soon after, all through concrete materials. Operations (addition, subtraction, multiplication, division, the calculation of square roots) are again introduced using concrete materials, which the child can choose to stop using when he is able to succeed without that concrete support.

Principles running throughout the design of these learning materials are that the child learns through movement and gains a concrete foundation with the aim of preparing him for learning more abstract concepts. A further design principle is that each piece of learning material has a 'control of error' which alerts the child to any mistakes, thereby allowing self-correction with minimal teacher support.

Self-directed engagement with the materials

Important though the learning materials are, 8 they do not, in isolation, constitute the Montessori method because they need to be engaged with in a particular way. Montessori observed that the young child is capable of concentrating for long periods of time on activities that capture his spontaneous interest. 2 , 3 , 4 There are two features of the way that children engage with the learning materials that Montessori claimed promoted this concentration. The first is that there is a cycle of activity surrounding the use of each piece of material (termed the 'internal work cycle ' 9 ). If a child wishes to use the pink tower, for example, he will have to find a space on the floor large enough to unroll the mat that will delineate his work area, carry the ten cubes of the pink tower individually to the mat from where they are stored, then build the tower. Once he has built the tower he is free to repeat this activity as many times as he likes. Other children may come and watch, and if he wishes they can join in with him, but he will be able to continue on his own if he prefers and for as long as he likes. When he has had enough, he will dismantle the pink tower and reassemble it in its original location, ready for another child to use. This repeated and self-chosen engagement with the material, the lack of interruption, and the requirement to set up the material and put it away afterwards, are key elements aimed at developing the child’s concentration. 10

The second feature which aims to promote concentration is that these cycles of activity take place during a 3-h period of time (termed the 'external work cycle' 9 ). During those 3 h children are mostly free to select activities on their own and with others, and to find their own rhythm of activity, moving freely around the classroom as they do so. One might wonder what the role of the teacher is during this period. Although the children have a great deal of freedom in what they do, their freedom is not unlimited. The teacher’s role is to guide children who are finding it hard to select materials or who are disturbing others, to introduce new materials to children who are ready for a new challenge, and to conduct small-group lessons. Her decisions about what to teach are made on the basis of careful observations of the children. Although she might start the day with plans of what she will do during the work cycle, she will be led by her students and their needs, and there is no formal timetable. Hence the Montessori classroom is very different to the teacher-led conventional classroom with its highly structured day where short timeslots are devoted to each activity, the whole class is engaged in the same activities at the same time, and the teacher instructs at the front of the class.

In summary, there are two aspects of Montessori classrooms that are very different to conventional classrooms: the learning materials themselves, and the individual, self-directed nature of the learning under the teacher’s expert guidance. All the elements described here—the features of the learning materials themselves (e.g., each piece of material isolates just one concept, each contains a control of error that allows for self-correction, learning proceeds from concrete to abstract concepts) and the child-led manner of engagement with those materials (e.g., self-selection, repeated and active engagement, tidying up afterwards, freedom from interruption, lack of grades and extrinsic rewards) might potentially benefit development and learning over the teaching of the conventional classroom. We will return to many of the elements discussed here in the following two sections. (This has necessarily been only a brief survey of some of the most important elements of the Montessori method. Readers wanting to find out more are again directed to refs. 2 , 3 , 4 ).

Evaluations of Montessori education

There are few peer-reviewed evaluations of Montessori education, and the majority have been carried out in the USA. Some have evaluated children’s outcomes while those children were in Montessori settings, and others have evaluated Montessori-educated children after a period of subsequent conventional schooling. As a whole this body of research suffers from several methodological limitations. Firstly, few studies are longitudinal in design. Secondly, there are no good quality randomised control trials; most researchers have instead tried to match participants in Montessori and comparison groups on as many likely confounding variables as possible. Thirdly, if children in the Montessori group do score higher than those in the non-Montessori group on a particular outcome measure, then assuming that that effect can be attributed to being in a Montessori classroom, what exactly is it about Montessori education that has caused the effect? Montessori education is a complex package—how can the specific elements which might be causing the effect be isolated? At a very basic level—and drawing on two of the main aspects of Montessori education outlined above—is the effect due to the learning materials or to the self-directed way in which children engage with them (and can the two be separated)? Fourthly, there are presumably differences between Montessori schools (including the way in which the method is implemented) that might influence children’s outcomes, but studies rarely include more than one Montessori school, and sometimes not more than one Montessori class. Fifthly, and relatedly, there is the issue of 'treatment fidelity'—what counts as a Montessori classroom? Not all schools that call themselves 'Montessori' adhere strictly to Montessori principles, have trained Montessori teachers, or are accredited by a professional organisation. A sixth, and again related, point is that children’s experiences in Montessori education will vary in terms of the length of time they spend in Montessori education, and the age at which they attend. Finally, the numbers of children participating in studies are usually small and quite narrow in terms of their demographics, making generalisation of any results problematic. These methodological issues are not limited to evaluations of Montessori education, of course—they are relevant to much of educational research.

Of these, the lack of randomised control trials is particularly notable given the recognition of their importance in education. 11 , 12 Parents choose their child’s school for a host of different reasons, 13 and randomisation is important in the context of Montessori education because parents who choose a non-conventional school for their child might be different in relevant ways from parents who do not, for example in their views on child-rearing and aspirations for their child’s future. This means that if a study finds a benefit for Montessori education over conventional education this might reflect a parent effect rather than a school effect. Furthermore, randomisation also controls for socio-economic status (SES). Montessori schools are often fee-paying, which means that pupils are likely to come from higher SES families; children from higher SES families are likely to do better in a variety of educational contexts. 14 , 15 , 16 A recent report found that even public (i.e., non-fee-paying) Montessori schools in the USA are not representative of the racial and socioeconomic diversity of the neighbourhoods they serve. 17 However, random assignment of children to Montessori versus non-Montessori schools for the purposes of a randomised control trial would be very difficult to achieve because it would take away parental choice.

Arguably the most robust evaluation of the Montessori method to date is that by Lillard and Else-Quest. 18 They compared children in Montessori and non-Montessori education and from two age groups—5 and 12-year olds—on a range of cognitive, academic, social and behavioural measures. Careful thought was given to how to overcome the lack of random assignment to the Montessori and non-Montessori groups. The authors’ solution was to design their study around the school lottery that was already in place in that particular school district. All children had entered the Montessori school lottery; those who were accepted were assigned to the Montessori group, and those who were not accepted were assigned to the comparison (other education systems) group. Post-hoc comparisons showed similar income levels in both sets of families. Although group differences were not found for all outcome measures, where they were found they favoured the Montessori group. For 5-year olds, significant group differences were found for certain academic skills (namely letter-word identification, phonological decoding ability, and math skills), a measure of executive function (the card sort task), social skills (as measured by social reasoning and positive shared play) and theory of mind (as measured by a false-belief task). For 12-year olds, significant group differences were found on measures of story writing and social skills. Furthermore, in a questionnaire that asked about how they felt about school, responses of children in the Montessori group indicated that they felt a greater sense of community. The authors concluded that 'at least when strictly implemented, Montessori education fosters social and academic skills that are equal or superior to those fostered by a pool of other types of schools'. 18

Their study has been criticised for using just one Montessori school, 19 but Lillard and Else-Quest’s response is that the school was faithful to Montessori principles, which suggests that the results might be generalisable to other such schools. 20 That fidelity might impact outcomes has long been of concern, 21 and was demonstrated empirically in a further, longitudinal, study, 6 that compared high fidelity Montessori classes (again, from just one school), 'supplemented' Montessori classes (which provided the Montessori materials plus conventional activities such as puzzles, games and worksheets), and conventional classrooms. Children in these classes were 3–6 years old, and they were tested at two time-points: towards the beginning and towards the end of the school year. Although the study lacked random assignment of children to groups, the groups were matched with respect to key parent variables such as parental education. As in Lillard and Else-Quest’s earlier study, 18 outcome measures tapped a range of social and academic skills related to school readiness (i.e., children’s preparedness to succeed in academic settings). There were two research questions: firstly, do preschool children’s school readiness skills change during the academic year as a function of school type, and secondly, within Montessori schools, does the percentage of children using Montessori materials in a classroom predict children’s school readiness skills at the end of the academic year? Overall, the answer to both questions was “yes”. Children in the high-fidelity Montessori school, as compared with children in the other two types of school, showed significantly greater gains on measures of executive function, reading, math, vocabulary, and social problem-solving. Furthermore, the degree to which children were engaged with Montessori materials significantly predicted gains in executive function, reading and vocabulary. In other words, treatment fidelity mattered: children gained fewer benefits from being in a Montessori school when they were engaged in non-Montessori activities.

This study does not demonstrate definitively that the Montessori materials drove the effect: there might have been other differences between the high and lower fidelity classrooms—such as the teachers’ interactions with their pupils—that were responsible for the difference in child outcomes. 6 In a move to explore the role of the Montessori materials further, a more recent experimental study 22 removed supplementary materials, to leave just the Montessori materials, from two of the three classrooms in a Montessori school that served 3–6-year olds. Over a period of 4 months children in the classrooms from which supplementary materials were removed made significantly greater gains than children from the unchanged classroom on tests of letter-word identification and executive function, although not on measures of vocabulary, theory of mind, maths, or social problem-solving. The authors acknowledge weaknesses in the study design, including the small number of participants (just 52 across the three classrooms) and the short duration. Nevertheless, the study does provide a template for how future experimental manipulations of fidelity to the Montessori method could be carried out.

Fidelity is important because variation in how faithful Montessori schools are to the 'ideal' is likely to be an important factor in explaining why such mixed findings have been found in evaluations of the Montessori method. 6 For example, two early randomised control trials to evaluate Head Start in the USA did not find any immediate benefit of Montessori preschool programmes over other types of preschool programmes. 23 , 24 In both programmes, only 4-year olds were included, whereas the ideal in Montessori preschool programmes is for 3–6 year olds to be taught in the same class in order to foster child-to-child tutoring. 6 Furthermore, in one of the programmes 23 the ideal 3-h work cycle was reduced to just 30 min. 6 A more recent study of older children compared 8th grade Montessori and non-Montessori students matched for gender, ethnicity and socio-economic status. 25 The study found lower scores for Montessori students for English/Language Arts and no difference for maths scores, but the participating Montessori school altered the “ideal” by issuing evaluative grades to pupils and introducing non-Montessori activities. 6

These same limitations then make it difficult to interpret studies that have found 'later' benefits for children who have been followed up after a subsequent period of conventional education. In one of the studies discussed earlier, 23 social and cognitive benefits did emerge for children who had previously attended Montessori preschools and then moved to conventional schools, but these benefits did not emerge until adolescence, while a follow-up study 26 found cognitive benefits in Montessori males only, again in adolescence. Although such 'sleeper effects' have been widely reported in evaluations of early years interventions, they may be artefacts of simple measurement error and random fluctuations. 27 Importantly, if the argument is that lack of fidelity to the Montessori method is responsible for studies not finding significant benefits of Montessori education at younger ages, it is not logical to then credit the Montessori method with any benefits that emerge in follow-up studies.

Some studies report positive outcomes for certain curricular areas but not others. One, for example, investigated scores on maths, science, English and social studies tests in the final years of compulsory education, several years after children had left their Montessori classrooms. 28 Compared to the non-Montessori group (who were matched for gender, socioeconomic status, race/ethnicity and high school attended), the Montessori group scored significantly higher on maths and science, but no differences were found for English and social studies. What might explain this differential effect? The authors suggested that the advantages for maths might be driven by the materials themselves, compared to how maths is taught in conventional classes. 28 Alternatively, or perhaps in addition, children in Montessori classrooms might spend more time engaged in maths and science activities compared to children in conventional classes, with the amount of time spent on English and social studies not differing. However, the authors were unable, within the design of their study, to provide details of exactly how much time children in the Montessori school had spent doing maths, science, English and social studies, in comparison to the time that children in conventional classes were spending on those subjects.

Just as knowing what is going on in the Montessori classroom is vital to being able to interpret the findings of evaluations, so is knowing what is going on in the comparison classrooms. One of the earliest evaluations of Montessori education in the USA 29 speculated that Montessori would have found much to appreciate in one of the non-Montessori comparison classes, including its 'freedom for the children (moving about; working alone); its planned environment (innovative methods with tape recorder playback of children’s conversations; live animals, etc.); its non-punitive character (an “incorrect” answer deserves help, not anger; original answers are reinforced, but other answers are pursued); and its emphasis on concentration (the children sustained activity without direct supervision for relatively long periods of time)'. In some evaluations, the differences between Montessori and conventional classrooms might not actually be so great, which might explain why benefits of being educated in a Montessori classroom are not found. And even if the Montessori approach to teaching a particular curriculum area is different to those used in conventional classrooms, there are likely to be different, equally-effective approaches to teaching the same concepts. This is a suggested explanation for the finding that although children in Montessori kindergartens had an advantage relative to their conventionally-educated peers for base-10 understanding in mathematics, they did not maintain this advantage when tested 2 years later. 30

While most evaluations are interested in traditional academic outcomes or factors related to academic success such as executive functions, a small number have investigated creativity. For example, an old study 31 compared just 14 four and five-year-old children who attended a Montessori nursery school with 14 four and five-year olds who attended a conventional nursery school (matched for a range of parental variables, including attitudes and parental control). In a non-verbal creativity task, involving picture construction, they were given a blank sheet of paper, a piece of red gummed paper in the shape of a curved jellybean, and a pencil. They were then asked to think of and draw a picture in which the red paper would form an integral part. Each child’s construction was rated for originality, elaboration, activity, and title adequacy, and these ratings were then combined into a 'creativity' score. The group of conventionally-schooled children scored almost twice as high as the Montessori group. A second task involved the child giving verbal descriptions of seven objects: a red rubber ball, a green wooden cube, a short length of rope, a steel mirror, a piece of rectangular clear plastic, a piece of chalk, and a short length of plastic tubing. Each description was scored as to whether it was functional (i.e., focused on the object’s use) or whether it was a description of the object’s physical characteristics (i.e., shape, colour, etc.). Like the non-verbal creativity task, this task differentiated the two groups: whereas the conventionally educated children gave more functional descriptions (e.g., for the cube: “you play with it”), the Montessori children gave more physical descriptions (e.g., “it’s square, it’s made of wood, and it’s green”). A third task, the Embedded Figure Test, involved the child first being presented with a stimulus figure and then locating a similar figure located in an embedding context. Both accuracy and speed were measured. While the two groups did not differ in the number of embedded figures accurately located, the Montessori group completed the task significantly more quickly. The fourth and final task required children to draw a picture of anything they wanted to. Drawings were coded for the presence or absence of geometric figures and people. The Montessori group produced more geometric figures, but fewer people, than the conventional group.

The authors were careful not to cast judgement on the performance differences between the two groups. 31 They wrote that 'The study does, however, support the notion that differing preschool educational environments yield different outcomes' and 'Montessori children responded to the emphasis in their programme upon the physical world and upon a definition of school as a place of work; the Nursery School children responded on their part to the social emphasis and the opportunity for spontaneous expression of feeling'. They did not, however, compare and contrast the particular features of the two educational settings that might have given rise to these differences.

Creativity has been studied more recently in France. 32 Seven to twelve-year olds were tested longitudinally on five tasks tapping different aspects of creativity. 'Divergent' thinking tasks required children to (1) think of unusual uses for a cardboard box, (2) come up with ideas for making a plain toy elephant more entertaining, and (3) make as many drawings as possible starting from pairs of parallel lines. 'Integrative' thinking tasks required children to (1) invent a story based on a title that was provided to them, and (2) invent a drawing incorporating six particular shapes. Their sample was bigger than that of the previous study, 31 comprising 40 pupils from a Montessori school and 119 from two conventional schools, and pupils were tested in two consecutive years (no information is provided about whether pupils from different schools were matched on any variable other than age). For both types of task and at both time-points the Montessori-educated children scored higher than the conventionally-educated children. Again, the authors made little attempt to pinpoint the precise differences between schools that might have caused such differences in performance.

None of the studies discussed so far has attempted to isolate individual elements of the Montessori method that might be accounting for any of the positive effects that they find. There are several studies, however, that have focused on the practical life materials. A quasi-experimental study 33 demonstrated that the practical life materials can be efficacious in non-Montessori classrooms. More than 50 different practical life exercises were introduced into eight conventional kindergarten classes, while five conventional kindergarten classes were not given these materials and acted as a comparison group. The outcome measure was a fine motor control task, the 'penny posting test', whereby the number of pennies that a child could pick up and post through a one-inch slot in a can in two 30 s trials was counted. At pre-test the treatment and comparison groups did not differ in the number of pennies posted, but at post-test 6 months later the treatment group achieved a higher score than the comparison group, indicating finer motor control. A nice feature of this study is that teachers reported children in both groups spending the same amount of time on tasks designed to support fine motor control development, suggesting that there was something specific to the design of the practical life materials that was more effective in this regard than the conventional kindergarten materials on offer. And because the preschools that had used the practical life activities had introduced no other elements of the Montessori method, the effect could be confidently attributed to the practical life materials themselves.

An extension of this study 34 investigated the potential benefits of the practical life materials for fine motor control by comparing 5-year olds in Montessori kindergarten programmes with 5-year olds in a conventional programme (reported to have similarities in teaching mission and pupil background characteristics) on the 'flag posting test'. In this task, the child was given a solid hardwood tray covered with clay in which there were 12 pinholes. There were also 12 paper flags mounted on pins, six to the right of the tray and six to the left, and the child’s task was to place the flags one at time in the holes. The child received three scores: one for the amount of time taken to finish the activity, one for the number of attempts it took the child to put each flag into the hole, and one for hand dominance (to receive a score of 1 (established dominance) the child had to consistently use the same hand to place all 12 flags, whereas mixed dominance received a score of 0). Children were pre-tested at the beginning of the school year and post-tested 8 months later. Despite the lack of random assignment to groups, the two groups did not differ on pre-test scores, but they did at post-test: at post-test the Montessori group were significantly faster and significantly more accurate at the task, and had more established hand dominance. However, no attempt was made to measure how frequently children in both groups engaged with materials and activities that were designed to support fine motor control development. Furthermore, the children in the Montessori classrooms were at the age where they should also have been using the sensorial materials, some of which (for example, the 'knobbed cylinders' and 'geometric cabinet') are manipulated by holding small knobs, and whose use could potentially enhance fine motor control. At that age children would also have been using the 'insets for design', materials from the early literacy curriculum designed to enhance pencil control. Therefore, although the results of this study are consistent with the practical life materials enhancing fine motor control, the study does not securely establish that they do.

A further study 35 introduced practical life exercises into conventional kindergarten classes, while control kindergarten classes were not given these materials. 15 min were set aside in the experimental schools’ timetable for using the practical life materials, and they were also available during free choice periods. This time the outcome measure at pre-test and post-test was not fine motor skill but attention. There were benefits to attention of being in the experimental group, but only for girls—boys showed no such benefits. The differential gender impact of the practical life materials on the development of attention is puzzling. Girls did not appear to engage with the materials more than boys during the time that was set aside for using them, but no measure was taken of whether girls chose them more frequently than boys during the free choice periods. Similarly, there were no measurements of the time that children in both the experimental and control groups spent engaged in other activities that might have enhanced fine motor control. Nor is it clear whether it was the fine motor practice directly or rather the opportunity to select interesting activities (the teachers in the experimental schools commented on how interesting the children found the practical life activities) that was responsible for the benefits to attention that were recorded for girls.

Finally, it has been found that young adolescents in Montessori middle schools show greater intrinsic motivation than their peers in conventional middle schools (matched for an impressive array of background variables, including ethnicity, parental education and employment, home resources, parental involvement in school, and number of siblings). 36 The authors did not establish exactly which elements of the Montessori method might be responsible for this finding, but they did speculate that the following might be relevant: “students were provided at least 2 h per day to exercise choice and self-regulation; none of the students received mandatory grades; student grouping was primarily based on shared interests, not standardised tests; and students collaborated often with other students”. The authors did not evaluate the Montessori and non-Montessori groups on any measures of academic outcomes, but given the links between academic success and motivation at all stages of education (they provide a useful review of this literature), this link would be worth investigating in Montessori schools.

This section has discussed studies that have evaluated the Montessori method directly. To date there have been very few methodologically robust evaluations. Many suffer from limitations that make it challenging to interpret their findings, whether those findings are favourable, neutral or unfavourable towards the Montessori method. However, while randomised control trials could (and should) be designed to evaluate individual elements of the Montessori method, it is difficult to see how the random assignment of pupils to schools could work in practice (hence the ingenuity of the study reported in ref. 18 ). Nor could trials be appropriately blinded—teachers, and perhaps parents and pupils too, would know whether they were in the Montessori arm of the trial. In other words, although random assignment and blinding might work for specific interventions, it is hard to see how they could work for an entire school curriculum. Furthermore, given the complexity of identifying what it is that works, why it works, and for whom it works best, additional information, for example from observations of what children and teachers are actually doing in the classroom, would be needed for interpreting the results.

Evaluations of key elements of Montessori education that are shared with other educational methods

This final section examines studies that have not evaluated the Montessori method directly, but have evaluated other educational methods and interventions that share elements of the Montessori method. They, together with our growing understanding of the science underpinning learning, can add to the evidence base for Montessori education. Given the vast amount of research and the limited space in which to consider it, priority is given to systematic reviews and meta-analyses.

One of the best-researched instructional techniques is the use of phonics for teaching children to read. Phonics is the explicit teaching of the letter-sound correspondences that allow the child to crack the alphabetic code. Montessori’s first schools were in Italy, and Italian orthography has relatively transparent one-to-one mappings between letters and sounds, making phonics a logical choice of method for teaching children the mechanics of reading and spelling. English orthography is, however, much less regular: the mappings between letters and sounds are many-to-many, and for this reason the use of phonics as a method of instruction has been challenged for English. 37 Nevertheless, there is overwhelming evidence of its effectiveness despite English’s irregularities. 38 , 39 , 40 At the same time, great strides have been made in elucidating the neural mechanisms that underlie early reading and reading impairments, and these too demonstrate the importance to successful reading of integrating sound and visual representations. 41

As always in education, the devil is in the detail. Importantly, phonics programmes have the greatest impact on reading accuracy when they are systematic. 39 , 40 By 'systematic' it is meant that letter-sound relationships are taught in an organised sequence, rather than being taught on an ad hoc as-and-when-needed basis. However, within systematic teaching of phonics there are two very different approaches: synthetic phonics and analytic phonics. Synthetic phonics starts from the parts and works up to the whole: children learn the sounds that correspond to letters or groups of letters and use this knowledge to sound out words from left to right. Analytic phonics starts from the whole and drills down to the parts: sound-letter relationships are inferred from sets of words which share a letter and sound, e.g., \(\underline{h}\) at , \(\underline{h}\) en , \(\underline{h}\) ill , \(\underline{h}\) orse . Few randomised control trials have pitted synthetic and analytic phonics against one another, and it is not clear that either has the advantage. 40

The Montessori approach to teaching phonics is certainly systematic. Many schools in the UK, for example, use word lists drawn from Morris’s 'Phonics 44'. 42 , 43 Furthermore, the Montessori approach to phonics is synthetic rather than analytic: children are taught the sound-letter code before using it to encode words (in spelling) and decode them (in reading). One of the criticisms of synthetic phonics is that it teaches letters and sounds removed from their meaningful language context, in a way that analytic phonics does not. 44 It has long been recognised that the goal of reading is comprehension. Reading for meaning requires both code-based skills and language skills such as vocabulary, morphology, syntax and inferencing skills, 45 and these two sets of skills are not rigidly separated, but rather interact at multiple levels. 46 Indeed, phonics instruction works best where it is integrated with text-level reading instruction. 39 , 40 The explicit teaching of phonics within a rich language context—both spoken and written—is central to the Montessori curriculum. No evaluations have yet pitted phonics teaching in the Montessori classroom versus phonics teaching in the conventional classroom, however, and so whether the former is differentially effective is not known.

Research into writing supports Montessori’s view that writing involves a multitude of component skills, including handwriting, spelling, vocabulary and sentence construction. 47 , 48 Proficiency in these skills predicts the quality of children’s written compositions. 49 , 50 In the Montessori classroom these skills are worked on independently before being brought together, but they can continue to be practised independently. A growing body of research from conventional and special education classrooms demonstrates that the specific teaching of the component skills of writing improves the quality of children’s written compositions. 51 , 52 , 53 , 54

With respect to teaching mathematics to young children, there are many recommendations that Montessori teachers would recognise in their own classrooms, such as teaching geometry, number and operations using a developmental progression, and using progress monitoring to ensure that mathematics instruction builds on what each child knows. 55 Some of the recommended activities, such as 'help children to recognise, name, and compare shapes, and then teach them to combine and separate shapes' 55 map exactly on to Montessori’s sensorial materials such as the geometric cabinet and the constructive triangles. Other activities such as 'encourage children to label collections with number words and numerals' 55 map onto Montessori’s early mathematics material such as the number rods, the spindle box and the cards and counters. The importance of conceptual knowledge as the foundation for children being able to understand fractions has been stressed. 56 The Montessori fraction circles—which provide a sensorial experience with the fractions from one whole to ten tenths—provide just such a foundation, as do practical life exercises such as preparing snacks (how should a banana be cut so that it can be shared between three children?) and folding napkins.

Finally in this section, it is worth returning to the sustained attention and self-regulation that have been argued to characterise children’s engagement with the learning materials in the Montessori classroom. 2 , 3 , 4 These are important parts of the complex cognitive construct of executive functions (EFs), which also include inhibition, working memory and planning. Put simply, EFs are the set of processes that allow us to control our thoughts and actions in order to engage in motivated, goal-directed behaviour. That EFs are critical for academic success is backed by a wealth of research evidence. 57 , 58 , 59 , 60 , 61 Given this key role, EFs have become the target for a number of individually-administered interventions, full curricula, and add-ons to classroom curricula, such as CogMed (Pearson Education, Upper Saddle River, NJ), Tools of the Mind, 62 PATHS (PATHS Training LLC, Seattle, WA), music, yoga and martial arts. A review study compared these, including Montessori education, and concluded that compared to interventions such as CogMed that solely target EFs, 'school curricula hold the greatest promise for accessibility to all and intervening early enough to get children on a positive trajectory from the start and affecting EFs most broadly'. 63

Conclusions

Montessori education has been in existence for over a hundred years. Such longevity could well be due, at least in part, to its adaptability. 6 However, by its very nature, of course, greater adaptability means lower fidelity. This paper has discussed evidence that children may benefit cognitively and socially from Montessori education that is faithful to its creator’s principles, but it is less clear that adapted forms—which usually result in children spending less time engaged with self-chosen learning materials—are as effective. Nevertheless, studies suggest that the practical life materials can be usefully introduced into non-Montessori classrooms to support the development of young children’s fine motor skills and attention, and there is ample evidence from the wider educational literature that certain elements of the Montessori method—such as teaching early literacy through a phonic approach embedded in a rich language context, and providing a sensorial foundation for mathematics education—are effective. It has not been possible in this paper to give an exhaustive discussion of all the elements of Montessori education that might be beneficial, for example the lack of extrinsic rewards, the reduced emphasis on academic testing and lack of competition between pupils, the 3-year age-banding that fosters cross-age tutoring, or the presence of a trained teacher in the early years classroom.

Where does this leave Montessori education more than 100 years after its birth, and more than 60 years after the death of its creator? As others have noted, Montessori was a scientist who truly valued the scientific method and would not have expected her educational method to remain static. 64 Yet Montessori teachers often feel fear or uncertainty about being able to apply Montessori’s theories in new and innovative ways while still adhering to her underlying philosophical principles. 65 Ultimately, only empirical research, undertaken by teachers and researchers working together, can be our guide, because the questions that need answering are empirical in nature. Neuroscientific research—using neuroimaging methods which were not available in Montessori’s day—might also play a guiding role. For example, Montessori was prescient in her views that adolescence was a special time in development where the individual required a specially-designed form of education to address their needs. 66 Recent neuroimaging evidence points to adolescence as indeed being an important period for neural development, particularly for areas involved in executive functions and social cognition. 67 , 68 Montessori did not fully develop her ideas for the education of 12–18-year olds during her lifetime, but it is an area where current Montessorians might be able to take over the reins. Although some Montessori schools take pupils up to the age of 18, they are few and far between, and to my knowledge there are no published evaluations of their effectiveness. Developing a Montessori education for this age group in conjunction with the best of our current knowledge of developmental cognitive neuroscience has the potential to make a very positive contribution.

Nor did Montessori consider using her method with the elderly. In the context of a rapidly aging population and increasing numbers of elderly adults with acquired cognitive impairments such as those that result from Alzheimer’s disease, 69 it is interesting to note that the Montessori method is now being adapted for use with dementia patients, with the aim of improving functioning in activities of daily living, such as feeding, and in cognition. There is strong evidence for a reduction in difficulties with eating, weak evidence for benefits on cognition, and mixed evidence for benefits on constructive engagement and positive affect. 70 However, the quality of studies varies across domains; those evaluating effects on cognition have been of rather poor quality so far, and they have not yet examined whether there might be long-term effects. Nevertheless, given the challenges to developing successful medication for patients with Alzheimer’s disease despite a detailed knowledge of changes in their neurobiology, it would be sensible to continue the search for successful behavioural interventions alongside that for medical interventions. 71 One method for delivering Montessori-based activities to the elderly is via inter-generational programmes, whereby older adults with dementia are supported in teaching Montessori-based lessons to preschool children. Benefits have been reported for the adults involved, 72 but whether the children also benefit in particular ways from such inter-generational teaching has not been evaluated. Nor is it known whether a Montessori education in childhood or Montessori-based activities experienced in later life can protect the executive control circuits of the brain, as has been proposed for bilingualism. 73 A lifespan approach to the evaluation of the Montessori method involving both behavioural and neuroimaging methods might be valuable.

In sum, there are many methodological challenges to carrying out good quality educational research, including good quality research on the Montessori method. Arguably the most obvious challenge to emerge from the literature reviewed here is the practical difficulty of randomly allocating pupils to Montessori and non-Montessori schools in order to compare outcomes. The majority of studies have relied instead on trying to match pupils and teachers in Montessori and non-Montessori schools on a number of different variables, with the concomitant danger that unidentified factors have contributed to any difference in outcomes. Even if randomisation is achievable, studies need to be conducted on a large enough scale to not only allow generalisations to be made beyond the particular schools studied, but to also allow investigation of which children the Montessori method suits best. On a more optimistic note, recent experimental studies—whereby features of existing Montessori classrooms are manipulated in some way, or features of the Montessori method are added to non-Montessori classrooms—hold promise for investigating the effectiveness of particular elements of the Montessori method. The evidence base can be strengthened yet further by drawing on research of educational interventions with which it shares certain elements, and by drawing on related research in the science of learning. National and regional education systems are beset by regular swings of the pendulum, for example towards and away from phonics, 74 and towards and away from children working individually. 75 This means that elements of the Montessori method will sometimes be in vogue and sometimes not. It is therefore particularly important that Montessori teachers understand the evidence base that supports, or does not support, their pedagogy.

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Acknowledgements

I dedicate this work to Sandra Nash Petrek (1939–2017), an inspiring Montessorian.

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THE PERSISTENCE OF PRESCHOOL EFFECTS FROM EARLY CHILDHOOD THROUGH ADOLESCENCE

Arya ansari.

University of Virginia

Associated Data

Using data from the Early Childhood Longitudinal Study Kindergarten Cohort of 1998 ( n = 15,070), this study used propensity scores to examine the short- and long-term academic and psychosocial benefits of preschool education for a diverse sample of middle-class children. Compared with children who attended informal care at age 4, preschool attendees consistently performed better on achievement tests from age 5 through early adolescence, but exhibited less optimal psychosocial skills. These negative behavioral effects of preschool were concentrated among children who attended preschool for 20 or more hours per week, but otherwise, there was little evidence of heterogeneity as a function of program type or child- and family-characteristics. The long-term academic advantages of preschool were, however, largely explained by their positive effects on academic skills early in formal schooling and there was evidence for convergence in children’s academic test scores, which was partially attributed to the differences in children’s social skills during the early elementary school years.

Disparities in educational achievement are established early in the life course, and once these gaps are established, children’s prospects of upward mobility are diminished ( Kalil, 2015 ). These initial differences in early childhood often accumulate into long-term differences in educational attainment because they shape children’s early experiences, including their interactions with teachers and classmates ( Entwisle, Alexander, & Olson, 2005 ), curricular placement ( Winsler et al., 2012 , 2013 ), and interactions with their family ( Crosnoe, Augustine, & Huston, 2012 ), such that these systems act on the initial disparities and compound them from year-to-year. These disparities in early learning and development are, thus, the underpinning for later inequality, which is why the early childhood years serve as a critical juncture for intervening in children’s long-term educational careers ( Heckman, 2008 ).

There is an extensive literature documenting preschool programs as an effective means of preparing both low-income and middle-class children academically for kindergarten, but there is no consensus on the effects of preschool for children’s psychosocial development and even less is known about the extent to which the early academic benefits of preschool persist into adolescence ( Phillips et al., 2017 ). Addressing these questions regarding the short-term academic and psychosocial benefits of preschool education—defined as the benefits within the program year or shortly thereafter into kindergarten—and long-term benefits of preschool education—defined as the benefits during the elementary and middle school years—has important theoretical and policy implications as it could point to groups of children and to critical periods in the life course that can be targeted for efforts to boost, or at least maintain, preschool effects.

Although the question of whether preschool programs have academic and psychosocial benefits for children has been the subject of decades of research, the current investigation attempts to address some inconsistencies in the literature and tackles this question in new ways and, in doing so, this study takes some key steps to advance this important literature. For example, this study moves the early childhood field forward by considering both the direct and indirect effects of preschool participation, and therefore, provides a more in depth and nuanced understanding of why contemporary preschool programs may have long-term academic and psychosocial benefits for middle class children. Here, I define indirect effects as those that operate through a mediator variable. This investigation also contributes to the existing literature by directly assessing the extent to which, and the periods during which, there is convergence in the academic and social-behavioral development of children who did and did not attend preschool. Finally, this study considers heterogeneity in these long-term associations as a function of child, family, and program characteristics. I use data from the Early Childhood Longitudinal Study Kindergarten (ECLS-K) 1998 Cohort ( Tourangeau et al., 2009 ) to address these objectives, which although over 10 years old, is one of the only contemporary national samples that has followed children from kindergarten through the end of middle school, which allows for a careful analysis of the study objectives.

Preschool Education: Persistence, Convergence, and Sleeper Effects

The short-term associations between preschool enrollment and children’s academic achievement are fairly clear (e.g., Bassok, 2010 ; Bumgarner & Brooks-Gunn, 2015 ; Crosnoe, 2007 ; Gormley et al., 2005 ; Magnuson & Waldfogel, 2005 ; Puma et al., 2010 ; Votruba-Drzal et al., 2004 ; Weiland & Yoshikawa, 2013 ). Evidence from both experimental and correlational research have consistently shown that children from both low-income and middle-class families who attend preschool, especially those of high quality, enter kindergarten more ready academically than children who experience informal care. Even though there is a rich literature documenting the short-term academic benefits of preschool, the long-term effects into elementary school and beyond are more ambiguous, with some scholars documenting continued academic benefits of both publicly and privately funded preschool programs for children during middle childhood and adolescence ( Ansari et al., 2017 ; Magnuson et al., 2007 ; Vandell, Belsky, Burchinal, Vandergrift, & Steinberg, 2010 ; Vandell, Burchinal, & Pierce, 2016 ) and others documenting no consistent benefits shortly beyond the program year ( Hill et al., 2015 ; Lipsey et al., 2015 ; Puma et al., 2012 ). And although the evidence-base to date has largely focused on the experiences of children from lower-income families (approximately 90% of rigorous evaluations; Leak et al., 2010 ), recent studies from across the country do suggest that middle-class children also benefit from preschool enrollment. For example, quasi-experimental research on the short-term academic benefits of preschool programs in both Boston and Tulsa have found that for middle-class children preschool impacts were roughly 70–90% of the impact for lower-income children ( Gormley, Gayer, Phillips, & Dawson, 2005 ; Weiland & Yoshikawa, 2013 ). Similar conclusions have been drawn from other evaluations of programs in New Jersey ( Lamy, Barnett, & Jung, 2005 ) and Georgia ( Peisner,-Feinberg, Schaaf, LaForett, Hildebrandt, & Sideris, 2014 ) along with correlational studies using nationally representative samples ( Loeb, Bridges, Bassok, Fuller & Rumberger, 2007 ). Thus, the evidence that does exist on the experiences of middle-class children indicates that although these children might benefit slightly less than lower-income children, they do benefit in the short-term from preschool enrollment, and do so quite substantially.

In contrast to the short-term academic benefits of preschool, the short-term implications of preschool for children’s psychosocial functioning remains far more ambiguous, with some educational scholars documenting negative effects of preschool enrollment (e.g. Bassok et al., 2015 ; Magnuson et al., 2007 ; National Institute of Child Health and Human Development Early Child Care Research Network, 2003 ) and others documenting positive or null effects ( Ansari et al., 2017 ; Zachrisson, Dearing, Lekhal, & Toppelberg, 2013 ; Zhai et al., 2015). Some scholars have also argued that preschool programs are more likely to have negative effects for children’s socio-emotional development when they come from higher- and not lower-income homes and that these negative effects manifest because of disruptions in parent-child relationships and/or via exposure to new high stress contexts and peers ( Huston, Bobbitt, & Bentley, 2015 ). While these assertions are rooted in attachment and social-learning theory, there has been inconsistent empirical support for these points. And even among the studies that have found that preschoolers do worse behaviorally as a result of their enrollment, these effects have been found to disappear fairly rapidly ( Dearing, Zachrisson, & Naerde, 2015 ; Pingault, Tremblay, Vitaro, Japel, Boivin, & Cote, 2015 ).

These discrepancies in the literature discussed above have raised a number of questions about the long-term efficacy of contemporary preschool programs. In response, developmental and educational scholars have proposed a number of conceptual models that lay the groundwork for potentially reconciling disparities in the existing literature and for understanding both whether and why preschool programs may have long-term academic and psychosocial benefits for children, namely models of persistence, convergence, and sleeper effects ( Bailey et al., 2017 ; Barnett, 2011 ; Yoshikawa et al., 2013 ). I outline these three developmental models below and discuss them in light of the existing evidence-base surrounding the longer-term benefits of preschool participation.

Persistence of preschool effects

Classic, long-term evaluations of early childhood programs (Abecedarian: Campbell & Ramey, 1994 ; Chicago Parent-Child Centers: Reynolds, Temple, White, Ou, & Robertson, 2011 ; Perry Preschool: Schweinhart, 2005 ) and theories from the economic and developmental literatures on skill building ( Bailey et al., 2017 ; Cunha et al., 2006 ) argue that preschool effects are likely to persist over time because these programs can provide children with the foundational skills necessary for later school success. As one example, children’s early counting skills have been documented as the basis for math (and reading) achievement in subsequent years such that children with higher math abilities during the transition to kindergarten are more likely to score higher on future assessments of more advanced mathematics knowledge ( Duncan et al., 2007 ). Likewise, children’s earlier social-behavioral functioning lay the groundwork for their future educational engagement ( Ansari et al., 2017 ; Wright, Morgan, Coyne, Beaver, & Barnes, 2014 ).

Thus, from this perspective, we would hypothesize that successful preschool programs that promote children’s early academic achievement and psychosocial functioning may have long-term benefits within these domains because children enter school more ready to learn. That is, preschool participation results in greater kindergarten readiness (broadly defined), and that early school success lays the foundation for accelerated achievement through elementary school, which in turn leads to greater middle school success. In support of this developmental model, the follow-up to the Abecedarian Project revealed that the children who attended the program during early childhood were more likely to graduate from college and had greater annual earnings when compared with children in the control group who stayed at home ( Campbell et al., 2012 ). Other experimental and correlational studies of contemporary preschool programs targeted at both low-income and middle class families have also been linked with improvements in moderate-to longer-term outcomes ( Curenton et al., 2015 ; Magnuson et al., 2007 ; Phillips, Gormley, & Anderson, 2016 ) and suggest that these longer-term academic and psychosocial benefits can be accounted for by improvements in earlier skill development ( Ansari et al., 2017 ; Campbell et al., 2002 ; Reynolds, 1992; Sorensen & Dodge, 2015 ; Vandell et al., 2010 ). Thus, these studies suggest that preschool programs not only have short-term academic and psychosocial benefits for children through the transition to kindergarten, but these benefits can persist through middle childhood, adolescence, and in some cases, even into young adulthood. These results also suggest that children’s earlier academic achievement and psychosocial functioning can serve as important mediators of the long-term benefits of preschool.

Convergence of preschool effects

Despite the potential long-term benefits of preschool (versus other informal care arrangements), in recent years its efficacy has often been found to be minimal across different communities and at the national level ( Hill et al., 2015 ; Lipsey et al., 2015 ; Magnuson et al., 2007 ; Puma et al., 2012 ), with the short-term academic impacts persisting at full strength for 1–2 years beyond the program year before dissipating ( Leak et al., 2010 ). Thus, even though preschool programs can have long-term academic benefits for children of all backgrounds, much of the recent findings of contemporary preschool programs have often been described as experiencing convergence. Convergence can occur for one of the following two reasons (see also: Bailey et al., 2017 ; Barnett, 2011 ; Magnuson et al., 2007 ; Yoshikawa et al., 2013 ):

  • Catchup : Children who enter kindergarten without a preschool background and, therefore, with a less developed skillset (broadly defined), may accelerate in their learning over time and catch-up with their classmates who entered school with preschool experiences and stronger skills and behaviors.
  • Fadeout : Children who enter kindergarten with a preschool background and as a result with stronger skills, may make fewer gains in subsequent school years as compared with their classmates who entered school without a preschool experience and with a less developed skill set.

In line with these arguments, recent experimental evaluations of the federally funded Head Start program documented positive program impacts for low-income children’s academic achievement through the end of preschool, but by the time children entered kindergarten and first grade, there were no consistent academic advantages ( Puma et al., 2012 ). Similar patterns of convergence have also been documented across other localized preschool programs that have considered the efficacy of programs targeted at largely low-income children ( Hill et al., 2015 ; Lipsey et al., 2015 ) as well as with national samples of middle class families ( Magnuson et al., 2004 , 2007 ).

With regards to children’s psychosocial behaviors, and as briefly discussed above, prior studies that have documented negative effects of preschool in the short-term have also documented fairly rapid convergence ( Dearing et al., 2015 ; Pingault et al., 2015 ). Some scholars speculate that this convergence in behavioral effects is due to the fact that children who do not experience preschool undergo a transition to new social groups that negatively impacts their social behavioral development during the elementary school years, which is an adaptation process that preschoolers have already experienced ( Pingault et al., 2015 ). Put another way, this adaptation hypothesis posits that there is convergence in the negative effects of preschool for children’s psychosocial skills because children who did not receive preschool catch up with those who did.

At the same time, however, it is important to acknowledge that one potential explanation for the differences between classic preschool evaluations that show sustained effects and those of more recent evaluations of scaled-up programs that show convergence is the changing counterfactual ( Duncan & Magnuson, 2013 ; Phillips et al., 2017 ; Yoshikawa et al., 2013 ). That is, the early childhood experiences of the control groups were markedly different in the classic studies of preschool education, where children generally stayed at home ( Campbell et al., 2012 ; Ramey & Ramey, 2006; Schweinhart, 2005 ), than they are in today’s evaluations, where children generally experience some other form of preschool education ( Puma et al., 2012 ). Yet, despite the extensive debates regarding the convergence in outcomes between preschool participants and non-participants across different domains of early learning and development, there has been limited empirical evidence about when and why convergence occurs.

Sleeper effects

Finally, the sleeper-effects phenomena states that educational benefits of preschool may emerge later in the life course even in the absence of initial programmatic benefits ( Clarke & Clarke, 1981 ). Although there has not been much empirical evidence for sleeper effects with classic evaluations of early childhood programs ( Campbell et al., 2012 ; Schweinhart, 2006 ), which have documented fairly consistent impacts for children throughout the life course that carry forward (i.e., no break in the benefits of preschool), there has been growing recognition of the sleeper effects model in the developmental literature. In line with this model, two studies of preschool programs targeted at middle class families in the United States found that the academic benefits of quality preschool programs increased over time, even when there were no short-term non-linear effects of classroom quality ( Vandell et al., 2010 ) and when compared with other informal care arrangements in a national sample ( Magnuson et al., 2007 ). Similar patterns of sleeper effects have also been documented in other evaluations of intervention programs during the early elementary school years (e.g., Barrera et al., 2002 ). While it is not entirely clear why these sleeper effects emerge, some scholars speculate that these patterns may be attributed to improvements in socio-emotional development and other complex functional abilities that, in turn, serve as the basis for more advanced academic learning ( Heckman & Kautz, 2012 ; McClleland et al., 2013 ). Accordingly, these studies suggest that children’s early psychosocial functioning can serve as an important mediator of the long-term academic benefits of preschool participation.

Heterogeneity in Preschool Effects

Although the above theoretical models outline why, on average, the benefits of preschool may persist or diminish over time, educational and developmental scholars have also become increasingly interested in optimizing preschool education by understanding heterogeneity in preschool effects ( Duncan & Magnuson, 2013 ). After all, children’s education does not occur in a vacuum nor are all preschool experiences the same—children enter school with wide-ranging differences in personal, experiential, and social-cultural experiences that can either be built on by their teachers or can hinder the benefits children derive from these early investments ( Entwisle & Alexander, 1988 ). Moving beyond the overall (or main) effects of preschool participation, this study also considers whether: (a) children from different backgrounds respond differently to preschool programs; and (b) children respond in different ways to different programs.

Heterogeneity in preschool effects by child and family characteristics

As outlined above, on average, children from various demographic backgrounds benefit from preschool enrollment. However, given the goal of preschool, which is to prepare children for kindergarten, there has been growing interest in understanding whether preschool programs meet this goal for all children or only a subset of children as this has implications for policy and practice. As part of this effort, a great deal of research and policy attention has been paid to variation in preschool effects as a function of children’s race/ethnicity, gender, disability status, and socioeconomic status, but who benefits most has remained fairly ambiguous ( Phillips et al., 2017 ; Yoshikawa et al., 2013 ). For example, evidence from both Tulsa and the Boston suggest that Latino children may benefit more in the short-term from preschool enrollment than non-Latino children ( Gormley et al., 2005 ; Weiland & Yoshikawa, 2013 ), whereas other correlational and experimental preschool evaluations suggest that Black children may benefit more ( Bassok, 2010 ; Puma et al., 2010 ). As another example, data from older experimental trials suggest that girls benefit more than boys from early childhood programs (Anderson, 2008), but a recent meta-analysis by Magnuson and colleagues (2016) appears to indicate that the impacts of early childhood investments for measures of achievement and behavior do not vary as a function of child gender. Other studies have suggested conflicting support for heterogeneity in preschool effects across the socioeconomic distribution (e.g., Gormley et al., 2005 ; Loeb et al., 2007 ; Weiland & Yoshikawa, 2013 ) and only a handful of studies have considered the benefits of preschool for children with disabilities ( Bloom & Weiland, 2015 ; Phillips & Meloy, 2012 ; Weiland, 2016).

Despite these discrepancies in who might benefit more from preschool, what most of these studies have in common is that they have been restricted to short-term evaluations of the academic and social-behavioral benefits of preschool and, thus, have not been able to consider heterogeneity in the persistence of preschool effects. To illustrate the importance of this point consider what we know is generally true: low-income and middle-class children both benefit academically from preschool in the short-term. Does this mean that the degree to which these benefits persist over time will be the same? In reality, this scenario might be unlikely because low-income children are likely to face more external barriers to and constraints on their ability to succeed and, therefore, it is possible—if not probable—that lower-income children experience a greater degree of convergence over time than do middle-class children ( Brooks-Gunn, 2003 ). Accordingly, it is necessary to consider whether the persistence of preschool effects varies across different groups of children and as a function of the experiences children bring to the table.

Heterogeneity in preschool effects by program characteristics

Developmental science also suggests that another potential source of heterogeneity stems from program implementation. Indeed, a number of developmental and educational scholars have illustrated that children’s day-to-day experiences in preschool matters greatly ( Mashburn et al., 2008 ; Peisner-Feinberg, Burchinal, Clifford, Culkin, Howes, Kagan, & Yazejian, 2001 ). And although proximal indicators of preschool quality and experience are not available in the ECLS-K: 1998 Cohort, there are other important dimensions of preschool experience that shape children’s academic and psychosocial functioning including the number of hours children are in preschool and program type, which in this study I consider as potential sources of heterogeneity.

Correlational studies from across the country on the extent of children’s overall participation in preschool (as measured by hours) have yielded mixed evidence when looking at children’s academic achievement as the outcome (Burchinal, Zaslow, & Tarullo, 2016; Loeb et al., 2007 ; NICHD & Duncan, 2003 ; Reynolds et al., 2014 ). Similarly, while several analyses from the NICHD SECCYD have found that children who spend more hours in early child care and preschool exhibit less optimal social-behavioral development ( Belsky et al., 2007 ; NICHD ECCRN, 2006; Vandell et al., 2010 ), a number of national and international studies have found no significant differences as a function of dosage and care quantity (for a review see: Dearing & Zachrisson, 2017 ). And even among the studies that have documented significant behavioral differences, these effects have been found to diminish over time ( Dearing et al., 2015 ; Pingault et al., 2015 ). In terms of program type, prior studies suggest that public prekindergarten programs generally have more rigorous standards and offer a higher quality learning experience than center-based programs ( Bassok, Fitzpatrick, Greenberg & Loeb, 2016 ), which might mean that this subset of programs has larger effects that persist over time ( Ansari et al., 2017 ; Bassok et al., 2016 ), but longer-term evaluations of these programs have been few and far between. For these very reasons, there is a need for continued work that considers the long-term implications of the extent of children’s preschool participation along with the type of experiences children have.

The Current Study

The current study attempts to address some of these inconsistencies in the existing literature by considering the different ways in which preschool enrollment at age 4 might affect children’s short- and long-term school success, both academically and in terms of children’s psychosocial functioning. First, in evaluating the models of persistence and sleeper effects, I consider the following research questions: (RQ1) Are there academic and psychosocial benefits of preschool education for children as they transition into middle childhood and adolescence? Next, in evaluating the model of convergence I address the following question: (RQ2) Is there evidence for convergence of academic test scores and children’s psychosocial functioning across preschool participants and non-participants and, if so, when and why does it occur? In comparing each of these conceptual models, I also consider: (RQ3) What share of the long-term academic benefits of preschool is a result of earlier academic and psychosocial functioning? Finally, as a means of moving beyond the average effects of preschool I also consider: (RQ4) The extent to which the academic and psychosocial benefits of preschool through early adolescence differ by demographic groups (i.e., race/ethnicity, gender, disability status, and income) and preschool characteristics (i.e., dosage and program type). In addressing each of these objectives, this study adds to the discussion surrounding the benefits of preschool education by adjudicating among the three conceptual models underlying the long-term benefits of preschool and capturing the different ways in which these programs might shape children’s long-term school success. Given the conflicting evidence regarding the long-term academic and psychosocial effects of preschool and who benefits most for these experiences, I leave the study objectives as largely exploratory.

Data for this study were drawn from the ECLS-K 1998 Cohort ( Tourangeau et al., 2009 ), a nationally representative sample of roughly 21,000 kindergarteners who were followed from kindergarten entry through the end of eighth grade. Children were followed across six waves of data collection: (1) the fall of kindergarten; (2) the spring of kindergarten; (3) the spring of first grade; (4) the spring of third grade; (5) the spring of fifth grade; and (6) the spring of eighth grade. Across each time point, information was collected from parents and teachers as well as direct assessments of children. For the purposes of this investigation, I restricted the sample to children who (a) were first time kindergartners ( n = 16,752) and (b) had valid kindergarten data and preschool information ( n = 16,637). Similar to prior publications with the ECLS-K (see also: Bassok, Gibbs, & Latham, 2015 ; Curenton et al., 2015 ; Loeb et al., 2007 ; Magnuson et al., 2004 ) and other early childhood evaluations (see also, Lee, Zhai, Brooks-Gunn, Han, & Waldfogel, 2014), Head Start was removed from the preschool category for three reasons: (1) it is widely regarded as different than standard center-based care or state-funded pre-K; (2) prior studies have shown that there are no added benefits of Head Start participation in the ECLS-K as compared with parental care ( Curenton et al., 2015 ; Magnuson et al., 2007 ); and (3) it was not possible to achieve optimal balance across the Head Start and preschool conditions when using propensity score matching, even within the low-income sample (see also: Magnuson et al., 2007 ). The above exclusion criteria resulted in a final analytic sample of 15,070 children and families.

For sample descriptives stratified by children’s age 4 preschool arrangement, both before and after matching (propensity score matching is discussed below), see Table 1 . It should be noted that because of the inclusion criteria and matching algorithm employed as part of the current investigation, the study sample was diverse, but included predominantly middle class families. At the aggregate level, the sample of children from the matched models were predominantly White (66%), came from households with an average annual income of $60,245 ( SD = $37,951), and had mothers who averaged a little over 14 years of education ( SD =2.42). Roughly one out of every ten mothers received government assistance (6% received Temporary Assistance for Needy Families [TANF] and 10% received food stamps) and 92% of children spoke English at home.

Descriptive statistics of the focal variables in the ECLS-K, before and after matching.

Notes. All estimates correspond to means or proportions. Estimates in brackets correspond to standard deviations. Proportions may not sum to 1.00 due to rounding. n = 15,070 before matching. n = 14,521–14,629 after matching. Sample sizes in the matched samples vary across the 50 imputed datasets.

Preschool enrollment

During the beginning of the kindergarten year, parents were asked both whether and how many hours their child attended a “day care center, nursery school, preschool, or prekindergarten program” during the prior school year. Similar to prior studies using the ECLS-K, children who attended any of the above programs (excluding Head Start) were categorized as having attended preschool, but only if they were enrolled for five or more hours per week ( Bassok et al., 2015 ). Due to limited exposure, children who attended preschool for less than five hours per week were classified as having attended informal care along with children who were cared for by a relative, non-relative, family child care provider, or parent (see also: Ansari & Crosnoe, 2015 ; Iruka, Gardner-Neblett, Matthews, Winn, 2014 ; Tucker-Drob, 2012 ). Thus, the focal predictor was a binary marker of preschool enrollment defined as a center- or school-based program (1 = enrolled in a preschool program , n = 9,207; 0 = no preschool enrollment, n = 5,873).

Preschool program characteristics

As a means of looking at program characteristics, I disaggregated the preschool category in two different ways. First, I re-classified preschool attendees into two mutually exclusive groups: those who attended public prekindergarten programs ( n = 2,576, 17% of full sample and 28% of preschool sample) and those who attended center-based care ( n = 6,631, 44% of full sample and 72% of preschool sample) at age 4 (see also, Bassok et al., 2015 ; Magnuson et al., 2007 ), both of which were compared with informal care. It is important to note that the 17% participation rate in prekindergarten programs closely matches estimates of the proportion of 4-year-olds enrolled in public school prekindergarten programs during that time ( Smith, Kleiner, Parsad, Farris, & Green, 2003 ). I also constructed a measure of dosage based on the number of hours per week children attended preschool. In line with both Bassok and colleagues (2015) and Magnuson and colleagues (2007) , I grouped children into those who attended preschool full-time (20+ hours per week; n = 4,413, 29% of full sample and 48% of preschool sample) and those who attended preschool for part-time (5–20 hours per week; n = 4,794, 32% of full sample and 52% of preschool sample).

Children’s outcomes

Three domains of children’s academic achievement and psychosocial functioning were assessed over time and selected because prior educational studies have found that these are outcomes that are influenced by preschool education ( Ansari et al., 2017 ; Bumgarner & Brooks-Gunn, 2013 ; Weiland & Yoshikawa, 2013 ; Winsler et al., 2007) and shape children’s future school success ( Ansari et al., 2017 ; Duncan et al., 2007 ; McClleland et al., 2013; Vandell et al., 2010 ). First, children’s math and reading skills were directly assessed from kindergarten through eighth grade using age standardized assessments developed by the National Center for Educational Statistics (for more information on these measures, see: Rock & Pollack, 2002 ). Content from the reading assessment covered letter recognition, reading, and phonological awareness, whereas the math assessment covered children’s conceptual knowledge, procedural knowledge, and problem solving skills. Both assessments of math (α’s across waves = .92–.94) and reading (α’s across waves = .87–.93; Rock & Pollack, 2002 ) have demonstrated strong reliability. The earlier assessments during kindergarten and first grade emphasized basic reading and math skills, whereas the later assessments placed a stronger emphasis on more advanced academic skills (e.g., reading comprehension and algebra). Due to the high correlation between the math and reading subscales (mean r= .71, range = .66-.73), and because all results were comparable when examining the two scales separately (results are available upon request), an average composite was created at each wave for children’s academic achievement (for similar methods see: Coley & Kull, 2016 ).

Next, using an adapted version of the Social Rating Scale (SRS; Gresham & Elliot, 1990 ) teachers reported on children’s social-emotional and behavioral problems from kindergarten through fifth grade (not available at eighth grade). The SRS was based on a 4-point Likert scale (1 = never to 4 = very often ) and used to create the two final outcomes of interest: (1) children’s social skills, which were based on 9 items that captured children’s self-control and interpersonal skills; and (2) children’s externalizing behavior problems, which were based on six items from the SRS and captured children’s aggression and impulsivity (for more information on the measure see: Rock & Pollack, 2002 ). Both measures of children’s social skills (α’s across assessment waves = .75-.89) and behavior problems demonstrated acceptable reliability (α’s across assessment waves = .77-.78). Even though the correlation between social skills and behavior problems were of similar magnitude to that correlation between math and reading, these measures were kept as separate indicators in the primary analyses because the effects of preschool on these two outcomes (and the associations among the outcomes) were different (discussed in more depth below).

As a means of capturing skill gaps (i.e., convergence) over time, all focal outcomes of interest were standardized within each wave at the population level after imputation to have a mean of 0 and standard deviation of 1 with the ECLS-K cross-sectional weights using the full sample of children (C1CW0-C7CW0; for similar methods see: Tourangeau et al., 2009 ; Magnuson et al., 2007 ). Thus, the average American child between the fall of 1998 (i.e., fall of kindergarten) and spring of 2007 (i.e., eighth grade) had an outcome score of 0 and standard deviation of 1 on assessments of academic achievement, social skills, and externalizing behavior, and therefore, the estimates reported herein are relative to the population as a whole. For unstandardized and standardized outcome descriptives at the population level (which were used for standardization) as compared with descriptives for the unmatched and matched preschool and informal care samples, see Appendix Table 1 . And for bivariate correlations among the focal variables of interest, see Appendix Table 2 .

Analysis Plan

A primary concern with studies on preschool education is that the preschool enrollment is endogenous, which can undermine causal inference to be made about associations between preschool participation and children’s academic and social-behavioral development, as factors that select children into preschool might also influence their success in school ( Crosnoe, Purtell, Davis-Kean, Ansari, & Benner, 2016 ; Duncan & Magnuson, 2013 ). To address this issue of selection, the current study implements a form of propensity scores where the conditional probability of attending preschool given a set of covariates is used to create matched samples ( Rosenbaum & Rubin, 1983 ). To generate these samples, I included a number of variables that fall under six broader factors that are often considered in theoretical work geared at understanding parents’ preschool decisions (see: Coley, Votruba-Drzal, Collins & Miller, 2014 ; Crosnoe et al., 2016 ; Meyers & Jordan, 2006). It is important to note that the below variables do not include time varying covariates from middle childhood and adolescence because if time varying factors were to be affected by preschool enrollment then their inclusion in the models would bias the estimates generated. The factors included in the propensity score models were:

  • Children’s characteristics: child age at kindergarten entry, children’s age of first care, children’s gender, and children’s disability status.
  • Cultural background: race and ethnicity (White, Black, Latino, Asian/other) along with home language (English, not English).
  • Household structure and characteristics: mothers’ marital status, mothers’ age, household size, and the number of siblings in the home.
  • Family socioeconomic status: mothers’ employment status (employed full time, employed part time, unemployed), household income, receipt of TANF, receipt of Food Stamps, and mothers’ years of education.
  • Family home and school involvement: home learning activities (e.g., reading books and singing songs), parents’ school involvement (e.g., attended open house and parent-teacher conference), and educational resources (i.e., number of child books) in the home.
  • Community characteristics: urbanicity (large city, suburbs, town) and region (Northeast, Midwest, South West).

The primary omitted variables, which are not available in the 1998 Cohort of the ECLS-K, are children’s academic achievement and psychosocial functioning prior to preschool entry. If higher functioning children were more likely to experience preschool, then that would inflate the preschool estimates reported in this study. However, two prior studies with the Early Childhood Longitudinal Study Birth (ECLS-B) Cohort, a nationally representative sample of children who were followed from birth to kindergarten during a similar time frame as the ECLS-K, found that net of the above factors used in the propensity scores, higher functioning children were not more likely to experience preschool ( Coley et al., 2014 ; Crosnoe et al., 2016 ). And although it is not possible to comprehensively assess issues of omitted variable bias with non-experimental data, the inclusion of over 30 covariate indicators coupled with propensity scores approximates randomization as best as possible within the context of the data available ( Rosenbaum & Rubin, 1983 ).

With the above in mind, I used the nearest neighbor method (with four matches) with a caliper of .01, ensuring a sufficient overlap between the various conditions on their propensity scores. The first three research questions were addressed within these matched samples, which were weighted by the number of times “control” cases (i.e., children in informal care at age 4) were matched with “treatment” cases (i.e., children in preschool at age 4). To ensure that the models were unbiased, all models included clustering and stratification variables to adjust for shared variance. Finally, 50 datasets were imputed via chained equations in Stata (Stata Corp, 2009) to address missing data, which ranged from 0–53% per variable (mean of 16%) and were generally due to sample attrition by the eighth grade wave of data collection (see also, Coley & Kull, 2016 ). After data were imputed in Stata, the 50 datasets were exported to the Mplus program where all focal models were estimated ( Muthén & Muthén, 2013 ). As a precaution, all primary preschool versus informal care analyses were also estimated among the subsample of children who participated in data collection through the end of eighth grade and all findings were the same as those reported below (see Appendix Table 3 ). Similar to Coley and Kull (2016) who also looked at eighth grade outcomes using the ECLS-K, I report models that used multiple imputation.

The focal research objectives were addressed in a series of steps. First, to understand the short- and long-term associations between preschool participation and children’s learning and development, I estimated fully saturated path models that corresponded to Figure 1 (although not shown in the figure, all within time variables were covaried). Specifically paths A1-A2, B1-B2, and C1-C2 of Figure 1 correspond to the short-term effects of preschool for children’s externalizing behavior, academic achievement, and social skills, respectively, whereas paths A3-A5, B3-B6, and C3-C5 correspond with the long-term benefits of preschool for the same set of outcomes from first grade through the end of fifth and/or eighth grade. It is also important to note that there would be empirical evidence for sleeper effect if the following conditions were met: (a) paths B2-B6 were statistically significant; (b) path B1 was not statistically significant; and (c) the coefficients for B1 and B2-B6 were significantly different from one another (i.e., B1 ≠ B2-B6).

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Hypothesized model for the direct effects of preschool enrollment on children’s social skills (A paths), academic achievement (B paths), and externalizing behavior (C paths). K = kindergarten. G = grade. All within time measures were covaried.

Next, to assess for convergence (i.e., research question 2), I created difference scores that compared the regression slopes of preschool participation versus informal care from either: (a) baseline to each of the subsequent waves (t x -t 1 ) or (b) from one wave to the next (t x -t x - 1 ). The first set of analyses illustrates whether there is empirical evidence for convergence of test scores from kindergarten through eighth grade, whereas the second set of analyses illustrates when convergence occurs during the periods between kindergarten and eighth grade. Across both specifications, these difference scores capture changes in the benefits of preschool for children’s academic and social-behavioral development, which can be interpreted as the degree of convergence between the different study periods (see also: Magnuson et al., 2007 ). I use this modeling strategy as opposed to a simple growth curve model because this method allows me to address this specific question regarding the periods during which convergence occurs, which is not possible within a growth curve-modeling framework.

To address the third research question (i.e., the extent to which the long-term academic benefits of preschool were attributed to earlier skill development), all models were re-estimated and included autoregressive and cross lag pathways between children’s psychosocial functioning and academic achievement (see Figure 2 ). Similar to a number of other studies using this methodology (e.g., MacKenzie, Nicklas, Brooks-Gunn, & Waldfogel, 2015 ; Ritchie, Bates, & Plomin, 2015 ), I include all potential lagged and cross-lagged pathways to capture all potential unique pathways through which preschool might shape children’s subsequent development. The INDIRECT command, which takes the product of the regression coefficients, was used to estimate the total indirect effects of preschool on children’s academic learning over time. These indirect effects of preschool for children’s academic learning were then decomposed to assess the specific contribution of children’s earlier academic skills, behavior problems, and social skills.

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Hypothesized model for the total indirect effects of preschool enrollment. Black lines correspond to preschool effects. Blue lines correspond to fall of kindergarten effects. Red lines correspond to spring of kindergarten effects. Green lines correspond to spring of first grade effects. Purple lines correspond to spring of third grade effects. Orange lines correspond to spring of fifth grade effects. K = kindergarten. G = grade. All within time measures were covaried.

The fourth and final research question regarding heterogeneity in preschool effects as a function of child and program characteristics was addressed in two different ways. When considering variation as a function of child characteristics, I used interaction terms within the matched samples discussed above to gauge the extent to which preschool effects varied across different subgroups in the population. To address heterogeneity as a function of program characteristics, I re-estimated the propensity score models to create demographically comparable groups of children in the different types of preschool programs, both as a function of preschool type (i.e., prekindergarten and center-based care) and dosage (i.e., part and full day). After achieving balance, I re-estimated the path models within these matched samples and compared children who attended informal care with: (a) children who attended preschool full-time (20+ hours per week) and those who attended preschool for part-time (5–20 hours per week); and (b) children who attended public prekindergarten programs and those who attended center-based programs.

While the above served as the primary model specification for the propensity scores, I also estimated a number of alternative specifications for the focal preschool versus informal care contrast to ensure that the findings were robust to the analytic decisions. First, it is important to acknowledge that there is controversy over the best approach to addressing survey weights when using propensity scores ( Austin et al., 2016 ; DuGoff et al., 2014 ). Similar to the recommendations of DuGoff and colleagues (2014) , I estimated supplemental models that included a series of cross-sectional weights from each wave of data collection as covariates in the propensity score matching algorithm (i.e., C1CW0-C7CW0) to address any issues that may stem from the sampling strategy and nonresponse bias over time (children who attrited from the sample and did not have an assigned weight were coded as “−1” to reflect that they no were longer present). Results from these supplemental analyses were the same as those presented below (see Appendix Tables 3 ). There is also debates surrounding whether survey weights should be used in the models to predict outcomes and whether these propensity scores should be generalizable to the population ( Austin et al., 2016 ; DuGoff et al., 2014 ; Zanutto et al., 2006 ). Considering that the propensity scores used in this study were not intended to generalize to the population and because the cases were weighted by the number of times children were matched across conditions (i.e., a survey weight could not also be used), I estimated additional models that included the kindergarten weight within an OLS framework that replicated the sample specific analyses at the population level. Results from these nationally representative analyses were largely the same as those presented below (see Appendix Table 3 ). The final point of consideration is surrounding the inclusion of covariates when predicting outcomes in the matched samples (doubly robust estimation; Funk et al., 2011 ). Accordingly, I estimated supplemental models that controlled for each of the covariates listed in Table 1 within the matched samples and all results were quantitatively and qualitatively similar to the results from the primary specification (see Appendix Table 3 ).

Across the 50 imputed datasets, I was able to successfully match roughly 96–97% of children across preschool and informal care. To assess the overall quality of matches, I: (a) checked the standardized mean differences between preschool and informal care for all of the covariates using the 10% benchmark, which is a standard in the propensity score literature indicating negligible differences between groups (see Austin, 2011 ); (b) regressed each of the covariates, individually, on the indicator variable that distinguished children in informal care as compared with preschool within the matched samples; and (c) separated the comparison conditions into quartiles on the basis of children’s propensity scores and checked the balance of covariates within each quartile. As can be seen in Table 1 , before matching, almost all of the covariate contrasts were significantly different; after matching, however, there were no longer any differences. Likewise, all of the standardized mean differences across the two groups were less than 10% of a standard deviation and there were no significant differences among the covariates within the different strata of the propensity scores, which, when taken together, indicate that balance was successfully achieved. Again, however, it is important to emphasize that as part of the matching process, the resulting sample was more economically advantaged.

Persistence of preschool effects versus sleeper effects

Having successfully balanced the preschool and informal care conditions, I estimated a fully saturated path model within the matched samples. Note that because these were fully saturated models, these path models fit the data perfectly (i.e., CFI =1.00, RMSEA = 0.00). As can be seen in column 1 of Table 2 , children who attended preschool at age 4 scored significantly higher on kindergarten assessments of academic achievement (E.S. = 0.20 standard deviation units [ SD ]). Similar, albeit slightly smaller, academic benefits were documented through the end of eighth grade, with effect sizes ranging from 0.09–0.16 SD s. Despite these academic benefits through early adolescence, preschool attendees were found to demonstrate higher levels of externalizing behavior upon kindergarten entry (E.S. = 0.18 SD s), which persisted at reduced levels through the end of fifth grade (E.S. = 0.05–0.16 SD s). Likewise, preschool attendees exhibited less optimal social skills upon kindergarten entry (E.S. = 0.07 SD s), which persisted through the end of first grade (but not third or fifth grade). When taken together, these results from the ECLS-K: 1998 Cohort reveal that there was no “break” in the benefits (or drawbacks) of preschool and, thus, there was no support for the sleeper effects hypothesis, at least concerning the outcomes examined. Instead, the associations between preschool participation and children’s academic achievement and psychosocial skills persisted, but at reduced levels, through middle childhood and early adolescence.

The associations between participation in preschool versus informal care at age 4 and children’s academic and psychosocial functioning over time, using matched data.

Notes. All estimates in brackets correspond to standard errors. All continuous variables were standardized to have a mean of 0 and standard deviation of 1 and, therefore, the coefficients in this table correspond to effect sizes. Because these were fully saturated path models, the above models had a CFI of 1.00, RMSEA of 0.00. Convergence estimates might not sum to the effect sizes differences due to rounding.

Having illustrated both the short- and long-term associations between preschool participation and children’s learning and development, I proceeded to assess whether, and when, convergence of preschool effects occurred. As can be seen in column 2 of Table 2 , results from these analyses indicated that, as compared with baseline, the academic benefits of preschool shrunk over time. It is of note, however, that this convergence of test scores occurred almost entirely through the end of kindergarten and first grade. As can be seen in column 3 of Table 2 and in Panel A of Figure 3 , the initial academic benefits of preschool participation shrunk by approximately 20% ( p < .05; calculated by dividing the effect size for each wave by the baseline effect size) from the fall to the spring of kindergarten year. Although not reaching conventional levels of statistical significance, there was also some suggestive evidence of attenuation from the spring of kindergarten to spring of first grade (roughly 20% , p < .10). There was no further attenuation in the academic benefits of preschool, from one year to the next, after the spring of first grade. Put another way, roughly 70% of the convergence that was documented by the end of eighth grade had already manifested during the two years after preschool. In terms of children’s psychosocial skills, these convergence analyses revealed that the negative associations between preschool enrollment and children’s externalizing behavior shrunk by a little over 70% through the end of fifth grade (see columns 2 and 3 of Table 2 and panel B of Figure 3 ), whereas for children’s social skills, convergence largely occurred between first grade and third grade (see column 3 of Table 2 and panel C of Figure 3 ).

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Plots of the children’s academic test scores (panel A), externalizing behavior (panel B), and social skills (panel C) from kindergarten entry through the end of eighth grade across the preschool and informal care conditions, using the matched samples. Kinder = kindergarten.

Prior functioning as mediators

The third research objective was to determine the extent to which the associations between preschool programs and children’s long-term academic development were mediated by their earlier academic and psychosocial functioning. To address these objectives, these models included autoregressive and cross-lags and the resulting model fit the data well (CFIs > 0.95, RMSEA < 0.07; for autoregressive and cross-lag estimates see Appendix Table 4 ). Despite the evidence for convergence in children’s academic test scores, results from these mediational models indicated that the long-term associations between preschool enrollment and children’s academic functioning were almost entirely due to children’s earlier skill development, with indirect effects ranging from 8–16% of a SD (see column 3 of Table 3 ). Put another way, children’s earlier learning and development accounted for roughly 90–100% of the total direct association between preschool enrollment and children’s academic functioning over time (calculated by dividing the indirect effect by the direct effect). In contrast, the corresponding direct pathways were no longer statistically significant (see column 2 of Table 3 ).

The indirect associations between participation in preschool versus informal care at age 4 and children’s achievement over time, using propensity score matched data.

Notes. All estimates in brackets correspond to standard errors. All continuous variables were standardized to have a mean of 0 and standard deviation of 1 and, therefore, the coefficients in this table correspond to effect sizes. All models had good fit: CFIs > 0.95 and RMSEAs < 0.07.

Having established the indirect effects of preschool enrollment, I next decomposed these estimates into the long-term benefits of preschool that were attributed to children’s earlier: (a) academic achievement; (b) externalizing behavior; and (c) social skills (see columns 4–6 of Table 3 ). Results from this effort revealed two important points. First, the long-term academic benefits of preschool were almost entirely due to children’s earlier academic functioning during the early elementary school years. Second, there was evidence to suggest that the convergence of test scores across the preschool and informal care conditions were in part a function of children’s social skills. Specifically, the difference in children’s social skills throughout middle childhood that was attributed to preschool enrollment accounted for roughly 10–20% of the convergence in their academic test scores from kindergarten through eighth grade. That is, children who attended preschool at age 4 demonstrated lower social skills during kindergarten, which in turn resulted in them making fewer gains in academics during middle childhood and early adolescence. Results from these mediation models also indicated that preschool programs had academic benefits for children during third and fifth grade via heightened levels of externalizing behavior (i.e., preschool → greater externalizing behavior → greater academic achievement), but this was only true when including children’s social skills as a mediator of their academic performance over time. When models were: (a) re-estimated without social skills (see Appendix Table 5 ) and (b) re-estimated with a composite of social-behavioral functioning (see Appendix Table 5 ), these estimates were in the expected direction and all other findings were the same, suggesting that the strong correlation between social skills and externalizing behavior (within time r = |.65–.72|) resulted in a model that captured the variance in children’s academic achievement that was not explained by their social skills. Given the strong overlap between these two dimensions of social-behavior, these indirect effects via externalizing behavior should be interpreted with caution.

Heterogeneity in preschool effects

The final set of analyses considered heterogeneity in preschool effects as a function of both program and child-characteristics. In terms of child characteristics, results indicated that there was no consistent evidence for moderation as a function of children’s gender, race/ethnicity, and/or disability status (see Table 4 ). Among the 80 interactions tested, only one reached conventional levels of statistical significance and, therefore, was not interpreted. There was, however, some suggestive evidence for heterogeneity as a function of children’s socioeconomic status (3 of the 16 interactions reached conventional levels of significance and 2 reached marginal levels of significance). Specifically, although the academic benefits of preschool were comparable across the socioeconomic distribution, the negative effects of preschool for children’s social-behavioral development during the elementary school years were somewhat larger among children from less economically advantaged homes. Even in light of these suggestive patterns it is nonetheless important to emphasize that by early adolescence, there was no evidence for variation among the socio-demographic characteristics examined, and when taken as a whole, these results suggest that, at least among this diverse sample of middle class families, homogeneity in the effects of preschool was far more common than heterogeneity.

Heterogeneity in the direct associations between participation in preschool versus informal care at age 4 and children’s academic and psychosocial functioning over time, using matched data.

Notes. All estimates in brackets correspond to standard errors. All continuous variables were standardized to have a mean of 0 and standard deviation of 1 and, therefore, the coefficients in this table correspond to effect sizes.

In terms of program characteristics, after propensity score matching (see Appendix Tables 6–8 for descriptives before and after matching), I found no evidence of differences across the two mutually exclusive groups of public prekindergarten programs and center-based care (see Table 5 and see Appendix Figures 1–3 ). However, after balancing the various conditions (see Appendix Tables 9–11 for descriptives before and after matching), results from the dosage models revealed three important points (see Table 6 and Appendix Figures 4–6 ). First, both children who attended part- and full-day preschool programs outperformed their classmates who attended informal care in areas of academic achievement from kindergarten through eighth grade (8–22% of a SD ). Second, there was no difference in the academic performance of children who attended full-versus part-day programs. And, finally, the negative associations between preschool enrollment and children’s psychosocial functioning were only true among children in full-day programs, with effect sizes ranging from 8–33% of a SD when compared with children in informal care and 12–22% of a SD when compared with children in part-day programs. Ultimately, although both children in part- and full-day preschool programs experienced similar levels of convergence through the end of eighth grade as compared with non-preschool participants, the underlying cause for the convergence in their academic test scores was somewhat different. For children in full-day programs the convergence was largely rooted in fadeout that resulted from their lower levels of social skills, whereas the convergence in test scores for children in part-day programs was attributed to an unmeasured factor.

The associations between participation in public prekindergarten and center-based care versus informal care at age 4 and children’s academic and psychosocial functioning over time, using matched data.

Notes. All estimates in brackets correspond to standard errors. All continuous variables were standardized to have a mean of 0 and standard deviation of 1 and, therefore, the coefficients in this table correspond to effect sizes. Because these were fully saturated path models, the above model above had a CFI of 1.00, RMSEA of 0.00. Convergence estimates might not sum to the effect sizes differences due to rounding.

The associations between participation in part- and full-day preschool versus informal care at age 4 and children’s academic and psychosocial functioning over time, using matched data.

There is a great deal of experimental ( Campbell et al., 1994 ; Schweinhart et al., 2006 ) and correlational ( Crosnoe, 2007 ; Magnuson et al., 2004 , 2007 ; Weiland & Yoshikawa, 2013 ; Winsler et al., 2007) evidence to suggest that preschool programs can be leveraged to boost young children’s early learning, and these benefits hold true for children from all income backgrounds ( Gormley et al., 2005 ; Lamy et al., 2005 ; Peisner-Feinberg et al., 2014 ; Weiland & Yoshikawa, 2013 ). Despite the wealth of empirical inquiry into preschool education, whether contemporary preschool programs continue to have academic and psychosocial benefits for children through early adolescence and beyond has remained contested, especially among routinely implemented preschool programs for children from middle-class families (for a consensus statement see: Phillips et al., 2017 ). Accordingly, this investigation sought to push the early childhood literature forward by addressing these gaps in knowledge with a diverse sample of middle class children and families from the ECLS-K: 1998 Cohort. Below, I discuss four take home messages of this work.

First, results from this investigation revealed that children who attended preschool at age 4 not only outperformed their classmates in areas of academic achievement upon kindergarten entry, but these benefits were carried forward over time, which is both similar to (e.g., Curenton et al., 2015 ; Magnuson et al., 2007 ; Vandell et al., 2010 , 2016 ) and different from (e.g., Hill et al., 2015 ; Lipsey et al., 2015 ; Puma et al., 2012 ) the extant literature. One possible explanation for these inconsistencies is the difference in socioeconomic status between samples; the children who participated in the current study were, on average, from middle-class households, which means that this sample of children faced fewer external barriers to and constraints on their ability to succeed. Thus, although children from across the income distribution benefit from preschool enrollment, lower-income children may be more likely to experience a greater degree of convergence over time because preschool programs are not a panacea for the various disadvantages faced by children throughout the life course ( Brooks-Gunn, 2003 ).

It is also of note that the comparison condition used in this study was different from recent preschool evaluations whose control groups often include children enrolled in other types of preschool programs (e.g., Puma et al., 2012 ; Weiland & Yoshikawa et al., 2013 ). In this study, the children in the comparison condition did not experience alternative forms (or extensive hours) of preschool and when I compared children who attended center-based care and prekindergarten, no differences emerged. In that sense, the results reported herein are more comparable to the classic studies where children in the control group generally stayed at home. These differences in the counterfactual are of increasing importance and need to be considered when comparing the results of this study with the existing literature. As one example, Zhai and colleagues (2014) found that while the Head Start program did produce stronger academic skills for low-income children through the end of the program year as compared with the control group (roughly 0.20 SD s), the program was most beneficial for those who otherwise would have received informal care (roughly 0.35 SD s). These particular findings are of note because they suggest that the effect sizes documented herein would be smaller if the comparison condition were more similar to recent control groups that have included children who experienced other forms of preschool. Nonetheless, when making comparisons between the results of this study and the extant literature, careful attention should be paid to the comparison condition.

Similar to the published literature, however, there was evidence to suggest that the initial academic advantages conferred by preschool programs shrunk over time; the academic benefits of preschool participation reduced in size by approximately half once children were nine years from the end of preschool. Some convergence in preschool effects is perhaps inevitable, but there is an important distinction between preschool effects that diminish over time and effects that disappear. To this very point, the results of this study are in line with recent evaluations of publicly and privately-funded programs in North Carolina ( Muschkin et al., 2015 ), Miami ( Ansari et al., 2017 ), and at the national level ( Curenton et al., 2015 ; Magnuson et al., 2007 ) and suggest that preschool programs do have academic benefits for children in the long run, regardless of child characteristics, dosage, and program type. These results build on these existing efforts by revealing that the advantages that persisted through the end of third and fifth grade can be maintained through the end of middle school. Not only were these advantages statistically significant and comparable to earlier studies done with the ECLS through the early elementary school years (0.07–0.12 SD s; Curenton et al., 2015 ; Magnuson et al., 2007 ), but the documented benefits of preschool education exceeded the benchmarks put forward by Chetty and colleagues (2011 ; 0.04–0.07 SD s) with respect to programs “breaking even” and matched the more conservative estimates developed by Magnuson and Duncan (2014 ; 0.09–0.15 SD s).

Next, while the effects of preschool on children’s socio-emotional development remains less clear than its effects on children’s academic achievement (e.g., Bassok et al., 2015 ; Dearing et al., 2015 ; Magnuson et al., 2007 ; National Institute of Child Health and Human Development Early Child Care Research Network, 2003 ), the results from the current investigation revealed that preschool attendees demonstrated less optimal psychosocial functioning over time as compared with children who attended informal care. Overall, however, these associations were concentrated among children who attended preschool for 20 or more hours per week and these negative social-behavioral effects converged to negligible levels over time. One potential explanation for some of the variation in results across studies is that the current investigation could not differentiate between more general preschool programs and programs that emphasized children’s socio-emotional development ( Yoshikawa et al., 2013 ). Moreover, some scholars have argued that early childhood programs are more likely to have negative effects for children’s socio-emotional development when they come from higher- and not lower-income homes ( Huston, Bobbitt, & Bentley, 2015 ), but the pattern of moderation that did emerge with regard to families socioeconomic status in this study does conflict with these assertions. Although speculative, one potential explanation circles back to the sampling of the ECLS-K coupled with the fact that the matching models resulted in fewer children who were truly economically disadvantaged, which limits the income distribution available for consideration (e.g., only 10% of families received food stamps in the matched samples, whereas lower-income samples from a similar time frame have rates closer to 45%; Chor, 2016 ).

Even so, it is worth emphasizing that unlike measures of academic achievement, the quality of measurement for children’s socio-emotional development needs to be considered, as does a more explicit focus on why programs result in less optimal behavior. While some developmental scholars speculate that these negative effects on children’s psychosocial behaviors might result from disruptions in parent-child relationships or via social learning, there has not been conclusive evidence for either hypothesis ( Huston et al., 2015 ). At the same time, however, these results are in line with the social group adaptation hypothesis ( Pingault et al., 2015 ), which posits that convergence in the negative behavioral effects of preschool occur because children who experienced informal care must adapt to social group settings after the transition to kindergarten, which preschool attendees have already experienced before the transition to formal schooling.

Third, by using six waves of data that spanned across nine years, this study was also able to pinpoint the periods in which partial convergence occurred. This study revealed that convergence of academic test scores across preschool and informal care groups happened almost entirely during the two years after preschool. After first grade, the initial academic advantages conferred by preschool programs were largely maintained. Put another way, during the two years after preschool, the academic benefits of children’s participation in these programs shrunk by roughly .035 standard deviation units per year, but between the end of first and eighth grade, these benefits shrunk by less than .005 standard deviation units per year. One potential explanation for these differences in convergence during early elementary school as compared with the later grades is the type of instruction that children are exposed to. Indeed, recent national studies have found that instruction during these early years often covers basic skills ( Engel, Claessens, Watts, & Farkas, 2016 ), which are skills that preschool children may have already mastered.

If these results regarding the periods of convergence are replicated across different samples, then these findings indicate that to maintain the academic benefits of preschool—which have been central to the discourse on preschool education—policymakers and researchers should focus on the one or two years after the end of preschool as a potential point of intervention. In doing so, we can better understand how to maintain the academic gains made by children through the transition to kindergarten. For example, the legacy impact of early experiences may vary as a function of experience in subsequent exogenous environments ( Bailey, Duncan, Odgers, & Wu, 2017 ) and, thus, studying the school environment during kindergarten and first grade can potentially provide answers for maintaining preschool effects ( Jenkins et al., 2016 ; Magnuson et al., 2007 ; Swain, Springer, & Hofer, 2015). Alternatively, providing booster interventions after preschool can also prove to be effective in maintaining the initial advantages conferred by these programs (see: Tolan, Gorman-Smith, Henry, & Schoeny, 2009 ) as can initiatives that aim to build stronger connections between preschool programs and elementary schools (e.g., Pre-K-3 rd Education; Benner, et al., 2016 ; Reynolds, Magnuson, & Ou, 2010 ; Shore, 2009 ). That is to say that, it is likely that more systematic and comprehensive interventions will have greater academic and psychosocial benefits for children than preschool programs that occur in isolation for only one year.

The fourth and final key point of this investigation centered on the underlying reasons for the long-term academic benefits of preschool education. Resonating with some of the recent empirical literature (e.g., Ansari et al.,, 2017 ; Sorensen & Dodge, 2015 ; Vandell et al., 2010 ) and some of the "landmark" studies in early childhood education (e.g., Campbell et al., 2002 ; Reynolds, 1992), the results of this study suggest that the long-term advantages of preschool were a function of children’s earlier academic achievement and that the convergence in test scores was partially attributed to the fact that preschoolers, especially those who attended full-day programs, entered school with less developed social skills. Thus, there was some support for models of skill building, which argue that preschool programs may have long-term benefits because human capital investments accumulate over time ( Cunha et al., 2006 )—after all, it was the early advantages that explained later achievement differences. At the same time, however, there was little support for the sleeper-effects phenomena, which posits that program benefits may emerge later in the life course even in the absence of initial programmatic benefits ( Clarke & Clarke, 1981 ). There was no “break” or hiatus in the benefits (or drawbacks) of preschool, at least among the outcomes examined, nor did the initial advantages that resulted from preschool accumulate over time. Rather, preschool programs provided children with a small academic boost for kindergarten, which persisted through early adolescence.

Despite these contributions to the early childhood literature, there are a number of limitations that need to be acknowledged. Primarily, although this study attempted to capture the different kinds of preschool programs attended by children (e.g., center-based care and public pre-K and as a function of dosage) to tease apart the heterogeneity that exists within this broader umbrella of preschool, there are other sources of heterogeneity that require attention (e.g., process quality; Johnson, Markowitz, Hill, & Phillips, 2016 ). That is, one of the consequences of using ECLS-K data is that the effects reported combine very different categories of experience and quality, which may lower all types of effects over time. Accordingly, continued work is necessary to understand which programs confer greater benefits for children, and why. Relatedly, in keeping with prior research done with the ECLS-K and other preschool evaluations (e.g., Lee et al., 2014 ; Loeb et al., 2007 ; Magnuson et al., 2004 ), Head Start programs were excluded from the current definition of preschool. This is of note because Head Start serves roughly a quarter of the low-income population ( Crosnoe et al., 2016 ), which is why these analyses do not speak to the experiences of low-income children. Nonetheless, understanding the long-term benefits of preschool for primarily middle-class families is equally important, and outside of work done by the NICHD Network ( Belsky et al., 2007 ; Vandell et al., 2010 , 2016 ) and older experimental trials ( Campbell et al., 2002 ; Reynolds et al., 2011 ; Schweinhart et al., 2006 ), this study is one of the few to consider the benefits of contemporary preschool programs through the end of middle school.

Additionally, much of the existing literature, including the current study, has relied on test scores as a means of evaluating the effectiveness of preschool programs. In light of some of the long-term follow-ups of early interventions, which reveal a host of psychosocial and economic benefits ( Campbell et al., 2012 ; Schweinhart, 2005 ), an important future direction is for researchers to think more broadly about the myriad of outcomes in elementary school and beyond that may result from preschool enrollment. For example, Bailey and colleagues (2017) discuss the importance of considering whether preschool experiences help children seize new opportunities and avoid imminent risks that can potentially shift children’s educational trajectories down the line. Within this framework, potential outcomes of interest can include placement in special education ( Muschkin et al., 2015 ), school retention ( Winsler et al., 2012 ), disciplinary infractions ( Wright et al., 2014 ), and course taking patterns ( Vandell et al., 2016 ).

It is also important to acknowledge that this study considered the landscape of preschool education during the 1997–1998 school year, which is prior to the major expansions of publicly funded preschool programs across the country. These data were selected because the ECLS-K: 1998 Cohort is one of the few contemporary national datasets that has tracked children’s experiences through early adolescence, which were required to address the study objectives. Even so, recent studies have found that the patterns documented in the 1998 cohort of the ECLS-K closely resemble those of the 2010 cohort through the end of first grade ( Bassok et al., 2015 ), suggesting that the findings documented herein are still relevant today. However, this limitation speaks to a larger issue in a field where cohort effects are of increasing importance for consideration given the changing landscape of early childhood education and, ultimately, because government initiatives may dramatically change this landscape in the coming decades. To this very point, the landmark studies often discussed in the early childhood literature are Perry Preschool and Abecedarian, but how those programs translate to today’s reality is unclear.

Finally, it is important to acknowledge two methodological limitations. First, the structure of the ECLS-K data collection limited the type of analyses that could be estimated. Similar to other studies with these data (e.g., Curenton et al., 2015 ; Magnuson et al., 2007 ), all of the variables used in the propensity score models were assessed after preschool attendance. Even though some of the variables were time invariant (e.g., race, gender, age), the best implementation of propensity scores is to use pre-treatment covariates. And even though this study used propensity score matching with a rich set of child and family covariates, which rules out many alternative explanations, these results do not imply cause and effect as it is not possible to completely rule out differential selection into preschool that result from unmeasured confounds. It is nonetheless interesting to point out that the propensity score models did little beyond the conditional regression models, which is perhaps not surprising given that this methodology does not change the causal identification (Elze et al., 2017). Considering that the estimated models included roughly 35 covariates regularly implicated in preschool selection (e.g., Coley et al., 2014 ; Crosnoe et al., 2016 ), it is likely that the OLS regression models were adequate in addressing issues related to bias. Second, some scholars emphasize the importance of disentangling “within” and “between” person effects and question whether cross-lagged models do so adequately ( Berry & Willoughby, 2017 ). In their work, Berry and Willoughby (2017) outline an alternative methodological approach to addressing this issue (i.e., autoregressive latent trajectory models), which requires further attention. While this alternative strategy is certainly one way of addressing these issues, it is not the only way. To address these issues, much of the current literature emphasizes the importance of including covariates, which help address between-person differences. And as other scholars have argued ( Gershoff, Aber, & Clements, 2009 ), the autoregressive lag in cross-lagged models becomes a “fixed effect” for time invariant characteristics that addresses within person differences. Thus, while there are alternative approaches to addressing these concerns, the models estimated in this study are in line with much of educational and developmental literatures.

With these limitations and future directions in mind, the current investigation advanced our knowledge about preschool education and the theories surrounding the development of children by illustrating the long-term implications of preschool enrollment for children’s academic achievement and psychosocial functioning. Moreover, the results of this study provided key insight into the periods of convergence, the similarities and differences in the long-term benefits of preschool across different subgroups of children and families, and the role of children’s psychosocial skills in the dissipating academic benefits of preschool from kindergarten through eighth grade. Ultimately, although preschool programs can be an effective means of preparing children for kindergarten, in the long run, these programs, short of other supports, are not, and should not be expected to be, a remedy for educational inequality throughout the life course.

Educational Impact and Implications Statement

Middle class children across the United States who attended preschool at the age 4 demonstrated stronger academic skills at the start of kindergarten as compared with their classmates who experienced informal care and these academic advantages persisted, albeit at reduced levels, through the end of eighth grade. At the same time, however, children who attended preschool for 20 or more hours per week also demonstrated somewhat greater externalizing behavior problems and less optimal social skills, which in the long run diminished to negligible levels. When taken together, these findings suggest that investments in preschool programs can have long-term academic benefits for children up to a decade later.

Supplementary Material

Acknowledgments.

The author acknowledges the support of grants from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01 HD069564, PI: Elizabeth Gershoff; R24 HD42849, PI: Mark Hayward; T32 HD007081-35, PI: Kelly Raley), the Interdisciplinary Collaborative on Development in Context, funded by a grant from the National Science Foundation (Grant: 1519686; PI: Elizabeth Gershoff and Robert Crosnoe), the Administration for Children and Families (90YE0161-01-00, PI: Arya Ansari), the Society for Research and Child Development, the American Psychological Foundation, and the Institute of Education Sciences, U.S. Department of Education (R305B130013, University of Virginia). The author also thanks Elizabeth Gershoff and Robert Crosnoe for their helpful comments on prior versions of this article.

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Child Development Research

The following are research articles published by staff at the WVU Child Development Laboratory (WVU Nursery School). Please click on the links to view the full articles.

Teaching Pre-Schoolers to Self-Assess Their Choices in Pre-K

drawing

Documentation Panels Enhance Teacher Education Programs

writing

Documentation of children’s projects is advantageous to their learning process and is also a good method for student teachers to observe the process of learning. Documentation panels are a unique way to help student teachers understand how children learn.

Read More...

Skinner Meets Piaget on the Reggio Playground

teacher and students

Practical synthesis of applied behavior analysis and developmentally appropriate practice orientations.

History Invades the Preschool Classroom

history project

This project was initiated at the WVU Nursery School. Young children engaged in a personal history project. Even with obvious developmental limitations to understanding past events, young children investigated occurrences of the past related to their families.

One of our students' history projects incorporated swing dancing lessons! Click here to view the video.

The Andy Warhol Project with a Touch of B.F. Skinner

art project

This visual arts project was initiated at the WVU Nursery School several years ago and has assisted children in reproducing prints of famous artists. Using the principles of behaviorism in conjunction with developmentally appropriate practice has helped young children extend their knowledge in the visual arts.

Hands on Harp: An Introductory Instrument for Young Children

playing with harp

A primary goal of any good program for young children is to maximize the children’s creative potential. The “Harp Project” is a learning center that has had a tremendous impact.

Encourage Young Children to Set Their Own Learning Goals

drawing

Why ask preschool children to set their own goals for learning? How do children use self-recording and reporting to develop important skills for life-long learning? Click on the link below to find out.

The Role of Etiquette in Social Skill Development of Preschoolers

tea party

Manners often are considered a lost art in today’s society but they are a topic of great interest to parents. This article presents a developmentally appropriate approach to teaching etiquette that was used with preschoolers at the WVU Nursery School. 

Paper Dolls: Back to Basics, With a Contemporary Twist

paper dolls

Paper dolls are an inexpensive toy that fascinates children and engages their minds for hours. What many parents may not realize are the benefits children are gaining from this experience. .

Wacky Wednesday

The Scrapbook project at the WVU Nursery School was implemented many years ago as a means to encourage children to create stories that are further used in other ways. The teacher plans various ways to encourage children to invent stories that include certain story elements.

  • Open access
  • Published: 20 February 2015

Early Childhood Education and Care in the United States: An Overview of the Current Policy Picture

  • Sheila B. Kamerman 1 &
  • Shirley Gatenio-Gabel 2  

International Journal of Child Care and Education Policy volume  1 ,  pages 23–34 ( 2007 ) Cite this article

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Early childhood education and care (ECEC) in the US includes a wide range of part-day, full-school-day, and full-work-day programs, under educational, social welfare, and commercial auspices, funded and delivered in a variety of ways in both the public and the private sectors, designed sometimes with an emphasis on the “care” component of ECEC and at other times with stress on “education” or with equal attention to both. Although ECEC scholars and advocates are increasingly convinced of the need to integrate all these program types, categorical funding coupled with diverse societal values continue to support the differences. The result is a fragmented ECEC system, of wide-ranging quality and with skewed access, but with some movement in recent years toward the integration of early childhood education and care.

Increased attention to early childhood education and care (ECEC) has been observed in all the industrialized countries but our focus here is on a current picture of ECEC in the United States (U.S.).

Early childhood education and care (ECEC) in the U.S. includes a wide range of part-day, full-school-day, and full-work-day programs, under educational, social welfare, and commercial auspices, funded and delivered in a variety of ways in both the public and the private sectors, designed sometimes with an emphasis on the “care” component of ECEC and at other times with stress on “education” or with equal attention to both. Although ECEC scholars and advocates are increasingly convinced of the need to integrate all these program types, categorical funding coupled with diverse societal values continue to support the differences. The result is a fragmented ECEC system, of wide-ranging quality and with skewed access, but with some movement in recent years toward the integration of early childhood education and care.

In what follows, we will identify and define the major program types, the context for current policy and program development, and the major issues.

Definitions

These definitions were drawn from Sheila B. Kamerman and Shirley Gatenio-Gabel, ECEC: “An Overview of the Current Policy Context” Debby Cryer & Richard M. Clifford, eds. Early Childhood Education & Care in the USA. Baltimore: Brooks, 2003 , a version of the background paper prepared for the OECD Thematic Review of ECEC policies and programs.

The programs discussed here include preschools (kindergartens, pre-kindergartens, compensatory education programs, and nursery schools operated under education auspices), child care centers (often defined as programs in non-residential settings that provide education and/or care to children and include organized group programs such as Head Start) and family child care homes (both regulated and unregulated “child minding”). Parental care, relative care, occasional baby sitting (child minding) and care provided in a child’s own home are not included in this paper nor are programs only for children with special needs.

More Specifically

Kindergartens are preschool programs for the year before primary school entry, largely for 5 year olds. They may be half day or full school day. In 1965, only eighteen states in the U.S. funded public kindergarten; by 1970, eighty percent of five year olds attended public kindergarten and, in 2000, all states funded some sort of kindergarten, most universal. Kindergarten is a near universal experience now for American children, with about 98 percent of children attending kindergarten prior to first grade at least a half day, an essential introduction to primary school. About sixty percent attend a full school day program (Education Commission of the States, 2007; NCES, 2000). However, program content varies greatly across states.

Preschools (or nursery schools in US Census Bureau reports) include the range of programs offered under public and private education auspices or providing compensatory education under special legislation and are largely half-day or cover the normal school day (usually about 6 hours, e.g. 9:00am – 3:00 pm). By 1998 twenty eight states even funded some form of public pre-kindergarten education. (Kagan, 2005 ), and about the same number served 3 year olds. Only five states served more than 10 percent of that group in addition to child care centers and Head Start (see below). According to Barnett in his review of the research (2007) “Research clearly shows that high-quality preschool education improves later school success, employment and earnings. It has lessened crime and delinquency and unhealthy behaviors like smoking and drug use. In economic terms, high-quality preschool has returned to the individual and the public up to $17 on every $1 invested.” Head Start, the compensatory preschool program begun in 1965, is a federally funded preschool program, largely half-day, targeted on poor children and serving 3–4 year olds primarily. It provides comprehensive education, health, nutrition, social and other services and enrolled almost 1 million children in 2004, about half of those eligible for the program, 12 percent of the nation’s 4-year olds and 8 percent of the 3-year olds. In 2004–05, $6.8 billion were spent on Head Start.

Center-based child care typically refers to full-day programs under social welfare auspices or free-standing and independent programs that offer care corresponding to the traditional working hours (e.g. 9:00 am to 5:00 pm or 7:00 am to 6:00 pm), and are open five days a week for the full year. Although most centers provide care to children aged 3–5 years, some provide care for infants and toddlers (1–2 years of age) as well as those aged 3–5. The boundary between preschool and center programs is fuzzy, at best. At their discretion, some child care centers may care for school-age children as well in their after-school programs. Almost all centers are regulated or licensed in some way by the states with regard to health and safety standards, staff-child ratios, maximum number of children per group, nutrition and have at the least annual inspections.

Family child care refers to care for several children (other than the provider’s own) in the caregiver’s own home. About 11 percent of children under age 5 (and under age 3), with employed mothers, were cared for in this arrangement. States regulate family child care homes through licensing or registration on one or more of the following criteria: square footage for activities, staff-child ratios, pre-service training requirements, criminal backgrounds, and immunization requirements. Licensing typically requires providers to meet minimum health, nutrition and safety standards, limit the number of children in a home; and sometimes requires programmatic standards. Registration, by comparison, requires or encourages providers to self-identify themselves to the state and certify that they comply with state requirements. Registration typically involves fewer inspections than licensing. Family child care may provide care during standard hours or during irregular hours (e.g., nights or weekends). Group family day care homes are private homes that provide care for sometimes as many as 12 children, may be required to employ at least one other adult to assist in the care of the children, and are more likely to be licensed than family day care homes. The number of hours and days of care provided are negotiated between the parent and provider in these home-based settings, but are generally available to accommodate the needs of full-time working parents, full-year. Some states specify the maximum number of infants and toddlers that a provider can care for in their home.

ECEC policies currently include the whole range of government actions (federal, state, and sometimes local) to influence the supply and/or demand for ECEC and program quality. These government activities include: direct delivery of ECEC services; direct and indirect financial subsidies to private providers of education and care such as grants, contracts, and tax incentives; financial subsidies to parents/consumers of ECEC such as grants and tax benefits to permit or facilitate access to services or to permit parents to remain at home and withdraw from the labor force at the time of childbirth or adoption for a brief period of time; and the establishment and enforcement of regulations.

ECEC Policy and Program Context

Generally, ECEC policies cover children from birth through state-designated compulsory school age. Compulsory school age is determined by the individual state and ranges from age five through eight years. Elementary (primary) school is compulsory for all children but it is at the state’s discretion whether or not kindergarten (the year before primary school begins) enrollment is mandated. Fourteen states and the District of Columbia, require children to attend kindergarten (Education Commission of the States, 2007). The other 36 states mandate the local school districts to provide kindergarten but it is the parents’ decision whether or not to enroll their child. Parents also have the option of enrolling their children in privately sponsored kindergartens. Only 10 states are required to offer full-day kindergarten.

There is no debate, at present, regarding whether compulsory school age should be changed or even made fully consistent nationally. However, there is debate with regard to expansion of prekindergarten services and/or the length of the prekindergarten and kindergarten days and which level of government should have responsibility for regulation and the setting of program standards.

For most children in ECEC programs, entry into a formal early childhood program would be when children are between three and five years old. Because of growing evidence that early intervention can be effective in compensating for early deprivation, mitigating and preventing disabilities in the future, and helping prepare young children for subsequent schooling -and because more women with children under age 3 are entering the workforce- there have been increased resources dedicated recently to providing services to children under age 3. In addition to care and education, these services may include health and nutritional screenings and may be coupled with family support services for parents including parent education, nutritional classes, various social service supports, and job training. There are specialized programs, also, which work with at risk populations, such as teens or substance abusers even prior to the birth of the child in preparation for parenting. Programs whose primary objective is to support the work efforts of parents accept children from three months of age (the maximum length of the federally mandated post-childbirth parental or family leave) through school age.

Federalism: A Barrier to National Policy

The U.S. has no coherent national ECEC policy. The primary responsibility for education is at the level of the states, not the Federal government, creating a barrier to the development of a national system of ECEC. The federal government, through the Congress, plays an important role in formulating ECEC policies and goals and facilitates the states’ and localities ‘major roles in the actual implementation of programs to suit the particular needs and preferences of their regions. The federal government’s policy making efforts have primarily focused on making services available to children who are at risk, due to economic, biological, social, or psychological circumstances or combinations of these; providing child care services as an incentive for mothers receiving social assistance to gain entry to the labor force.

At the state level, policy decisions are made with regard to eligibility, extent of the supply and availability of services, allocation of services and benefits, scope and quality of services, including health and safety standards. At present, many state legislatures are taking a leading role in the development of ECEC policies, making larger investments in preschool programs and in programs that respond to the work responsibilities of poor families, especially those who are or are at risk of welfare (social assistance) dependency.

Historical Roots

As in most other advanced industrialized countries, ECEC programs in the U.S. evolved out of diverse historical streams including child protection, early childhood education services for children with special needs, and services to facilitate mothers’ labor force participation. The “official” history of ECEC in the U.S. begins with two developments: (1) day nurseries (child care centers), first established in the 1830s under voluntary auspices and designed to care for the “unfortunate” children of working mothers; and (2) nursery schools, developing from the early education programs in Massachusetts also first established in the 1830s. Day nurseries expanded subsequently in response to pressures created by the rapid industrialization and massive immigration which took place in the latter part of the century. They were custodial in nature, focusing primarily on basic care and supervision of the children. During war times—the Civil War, World War I, and World War II—these programs increased in numbers, only to decline when war ended. Kindergartens and nursery schools expanded slowly during the 19 th century and experienced a significant increase only in the mid 1960s and early 1970s when a confluence of factors led to the significant expansion of both program types.

Factors Affecting ECEC Developments

Labor market policy, public (social) assistance policy, education policy, child welfare policy, and child development research all have had and have a role in the expansion of ECEC policies and programs.

Chief among these developments is the dramatic rise in the labor force participation of women, especially married mothers. The rise in the number of single mother households has added to the demand, especially for full-day programs, since lone mothers are more likely than married mothers to work full time and female-headed families have been a rapidly growing family type.

A second major factor shaping ECEC policies at present is the so-called “welfare reform” legislation of 1996, and the provisions of the new public assistance legislation for poor lone mothers and children. The Personal Responsibility and Work Opportunity Reconciliation Act of 1996 (PRWORA), requires that poor women with children aged 3 months and older “engage” in work within two years of claiming assistance and limits life-time receipt of assistance to a maximum of five years. These requirements mean that by far most poor lone mothers are now expected to work even when they have infants. One result has been increased Congressional recognition of the need for child care services, even if quality attributes and early education curricula have not received comparable attention.

Growing interest in primary “school readiness” is a third factor that has generated interest in ECEC in recent years. Research demonstrating the links that early learning experiences have with later school achievement, emotional and social well-being, fewer grade retentions, and reduced incidences of juvenile delinquency, are all factors associated with later adult productivity, and suggest the value of increased “investment” in ECEC (Barnett, 1995 ; Berrueta, 1984 ; Lazar, 1983 ; Yoshikawa, 1995 ; Currie, 2000 ; Brooks-Gunn, 2003 ; Hechman & Masterov, 2007 ). From this perspective, ECEC is increasingly viewed as a cost efficient and cost effective strategy whose benefits are reaped both during the school careers of each child, in their later life, and in the future economy.

Conflicting Values/Divergent Purposes

American society has long been conflicted in its attitude towards women and their proper roles and in its attitude towards government and the family and their appropriate roles. This tension emerges repeatedly in discussions regarding ECEC policies. Poor single mothers are expected to work outside the home and, despite a very different reality, there are many who still believe that middle class mothers should remain at home. Government’s involvement in the rearing of children is still viewed by some as trespassing into the private lives of its citizens.

ECEC responds to the changing work roles and composition of families, helps to equalize life opportunities for children in low-income families, assists in the assimilation of immigrants, and aids in enhancing child development and child wellbeing generally. Early on, publicly provided ECEC was designed to accommodate the social needs of vulnerable children, the educational needs of all young children, and the needs of working parents. Child care and early education developed separately, historically, and are still not well integrated. Through the years the two major functions of care and education have remained separate and often viewed as conflicting. One result has been the development of a wide and disparate range of ECEC programs of varying quality.

The Public/Private Mix

As with regard to most social services in the U.S., the private sectors (both non-profit and for-profit) play a major role in ECEC. For example, of all five year olds enrolled in kindergarten in 2003, 83 percent attended public kindergarten programs and 17 percent attended private programs. About half the children in nursery schools are in private schools. More important, private providers continue to dominate the delivery system: Family day care is almost all private. Of the three-year olds in preschool programs, most are in private programs but by age five, the overwhelming majorities are in public preschools.

Publicly-funded preschool programs typically serve children from disadvantaged families, while private preschool programs supported by parent fees are more likely to serve children from all backgrounds and the focus is more on the child than on providing support to the family.

Some employers, usually large firms, have become involved in ECEC typically by providing links with ECEC information and referral services, and to a lesser extent by becoming a provider of services to their employees. Such firms may offer employee subsidies or other benefits for child care, providing financial support to early childhood centers in the community, and participating in local or state collaborations to plan for future early childhood needs. Charitable foundations are important players in the policymaking arena through their funding of research and innovative programming; and religious organizations also play a significant role in ECEC service delivery.

Access and Coverage

In 2002, 11.6 million children or 63 percent of the 18.5 million infants, toddlers and preschool children under age 5, were receiving some type of care other than from their parents on a regular basis (U.S. Census, 2005a ). The type of care a family decides to place their child in is dependent on a family’s income, family structure and ethnicity, age of child, maternal education, maternal employment and attitudes toward early care. Where poor single mothers are concerned, or employed parents, the need for care may begin in infancy or even when the child is three months old, because the U.S. has only a brief (three months) and unpaid parental leave following childbirth. Footnote 2 Children of mothers who are college graduates were substantially more likely to attend nursery school (preschool and center-based programs) in 2003 than children whose mothers did not finish high school (64 percent compared with 34 percent). (U.S. Bureau of the Census, 2005b ). Similarly, in 2003, 62 percent of 3 and 4 year olds from families with incomes of $50,000 or more attended nursery school, compared with 41 percent of those from families with incomes less that $20,000.

Although kindergarten coverage is essentially universal now, largely for 5-year olds, for the year before entering primary school, states vary in their provision of full and part-day kindergarten programs. About half of all kindergartners now attend full (school) day programs (U.S. Census, 2005a ).

At four years of age, the proportion of children enrolled in center-based care rose to 69.2 percent,. Including kindergarten and primary school, almost 98 percent of 5 year olds are in some form of school or preschool) and of these, more than 75 percent are in kindergarten; the remainder are in primary school or center care.

Forty-four states now provide pre-kindergarten programs at least in some jurisdictions. Only three states, Florida, Georgia, and Oklahoma, however, approach offering a state-wide program of universal preschool for all four year olds.

Coverage for the Under 3s

About 60 percent of the under 3s had mothers in the labor force in 2006. Programs serving children under the age of three, generally focus on supporting the work efforts of parents. Yet despite this, ECEC programs serving children under the age of three are in short supply. Few states serve 3 year olds in pre-kindergarten programs, but 43 percent of 3 year olds are in center-based care. By the time a child reaches age three, parental preference for school- or center-based settings is striking.

In addition to child care programs, family support pr o grams, sometimes also included with other ECEC programs, offer drop-in child care, information and referral services, weekly or monthly home visits and parenting classes aimed at strengthening parenting skills, and so forth. They commonly serve families with children under the age of three (though they may include older children) and some strive to link programs for children with parental supports, such as job training and education. These programs target low-income groups primarily and involve a caseworker to link services that are provided by other community agencies. Typically, they rely on public funds and private foundation support and provide services at no charge to their client families. Also typically, these programs target families in or at risk of poverty, teen parenthood, welfare dependency or are in immigrant groups struggling with acculturation issues (Gomby, 1995 ).

Half of the infants born in 2001 were in some kind of regular non-parental child care arrangement at 9 months of age (Kreader, Fergusson, & Lawrence, 2005 ). Most parents of infants choose informal or in-home care. For children under the age of one year, 26 percent were cared for by a relative (often a grandmother), 11 percent were in family day care homes, and 9 percent in center-based care settings.

The age at which families first place their children in care depends on the work status of the mother, household income and maternal education. Families more dependent on a mother’s income are more likely to place infants in care at an earlier age and use more hours of care than families less dependent on maternal income. Poor mothers might place their infants in care even earlier than three months. Poor children who are enrolled in center-based programs receive care of the quality equal to affluent children. Poor children who do not enter care by their first birthday are more likely to come from large families, experience persistent poverty, and have mothers with the least education. In contrast, mothers who earn the highest incomes were most likely to place their children between 3 to 5 months and to use in-home non-relative care for the first 15 months (NICHD, 1999).

There is no agreed on definition of -or standards concerning- quality of ECEC programs across both school-based pre-kindergarten programs and center-based and Head Start programs. Indicators of quality in centers continue to include: staff: child ratios; group size; caregiver qualifications (education and training), staff salaries; and turnover rates — among the dimensions of quality that can be counted and regulated, and staff child interactions and relationships among those variable that require direct observation.

Despite research demonstrating that high quality early childhood care and education can be beneficial to children, research has also demonstrated that the majority of children in the United States are placed in low quality care, some of which may be detrimental to the long-term development of children (Helburn, 1995 ; NICHD, 1998 ; Whitebook, 1989 ). Some states set high quality standards and monitor programs closely, while others place quality control at the local level. The scope and depth of programming varies greatly both across and within states, from comprehensive programs promoting health, social and cognitive development to others providing limited opportunities for social interaction and developmental stimulation. In some states, prekindergarten programs are administered by the state’s department of education and in others governance is deferred to local school districts, thus adding further to the variation. Some programs have responded to the needs of working families by extending hours, coordinating with other programs for a full-day of programming, or parents have made arrangements for children to be transported to other private programs. Transferring young children from one program to another creates further complexities and is less preferred (Mitchell, Ripple, & Chanana, 1998 ).

According to the 2006 State Preschool Yearbook, about one million children participated in state pre-kindergarten programs in 2005–2006. Barnett et al. ( 2006 ) note that the quality of these preschools ranges from excellent to poor and, as we have already seen, funding and access vary from state to state. Preschool quality improved in recent years as more states adopted comprehensive learning standards for their pre-kindergarten programs. Nonetheless, quality continues to vary across states. For example, 20 states did not require pre-kindergarten teachers to have completed a Bachelor’s degree. Ten states did not require teachers to have had special training for ECEC programs. And per child spending for pre-kindergarten was significantly lower than for grades K — 12 in primary school, with pre-K teachers being paid significantly less that for primary school.

The different histories, sources and levels of public investment perpetuate a false dichotomy in polices for ECEC programs. Federal funding for ECEC totaled more than $17 billion in 2005. It should be noted, however, that fees paid by parents for ECEC cover about 70 percent of the operating costs of these programs in the U.S.

The major federal sources of child care funds include the following : The Child Care and Development Fund (CCDF) provides funding to the states to subsidize the child care expenses of working parents whose family income is less than 85 percent of the state median income, as well as for activities related to the improvement of the overall quality and supply of child care in general. Federally it is administered by the Administration for Children and Families (ACF) in the Department of Health and Human Services (DHHS). At the state level, it is administered by the agency responsible for social service/welfare administration or employment related activities. In 2006, over $5 billion was appropriated for this block grant, matched by state funds totaling $2.2 billion and the transfer of funds from “welfare” (the Temporary Assistance to Needy Families program) of almost $1.2 billion (Child Care Bureau, 2007).

The Child and Dependent Care Tax Credit in the Internal Revenue Code is a nonrefundable tax credit for expenses related to the care of a dependent child less than 13 years old, or a mentally or physically incapacitated spouse or dependent. In 2006, the maximum credit for one dependent was 35 percent of the first $3,000 spent on the care of one child and $6,000 for two or more. In 2005, the tax credit was valued at $2.7 billion. The tax credit is administered by the U.S. Department of Treasury, Internal Revenue Service.

Head Start funds direct grants to local programs providing comprehensive early childhood development, educational, health, nutritional, social and other services to primarily low-income preschool-aged children and their families. Most Head Start programs are part-day through the school year, though some local grantees coordinate with other programs to provide full-day care. Head Start is federally administered by the Administration on Children and Families (ACF) at DHHS. In 2005 it was funded at $6.9 billion, and served about 900,000 children, largely three and four year olds. A small number of children under age three are now enrolled in an Early Head Start program.

The Social Services Block Grant (SSBG, Title XX of the Social Security Act) provides grants to states for social services, which most states draw on for at least a portion of their ECEC services. The grants are federally administered by ACF at DHHS at about $400 million in 2005.

The Child and Adult Care Food Program provides federal subsidies for breakfasts, lunches, suppers, and snacks meeting federal nutrition requirements that are served in licensed child care centers, schools, and group and family day care homes to children age 12 or under. It is administered by the U.S. Department of Agriculture’s Food and Nutrition Service and was funded at $2.1 billion in 2005.

Several other federal programs such as the Individuals with Disability Education Act (IDEA) provide funding for ECEC as well. IDEA established an entitlement to special education services for children ages three through 21 with disabilities.

Local school districts may also use other categorical federal funds to support preschool education and school-age child care in districts serving a high percentage of low-income children. Once such program, Even Start, provides grants to schools for family centered education to help parents of educationally disadvantaged students’ ages one through seven become full partners in their children’s education. Funding is also available from the 21 st Century Community Learning Centers program for grants to rural and inner city public schools to address educational and community needs during after school hours, weekends, and summers.

Administrative Responsibilities

The Administration for Children and Families (ACF), within the federal Department of Health and Human Services (HHS) is responsible for federal programs which promote the economic and social well being of families, children, individuals, and communities. One agency in ACF is the Child Care Bureau which was established in January 1995 to administer federal child care programs to states, territories and tribes for low income children and families. The Bureau has initiated a variety of activities to improve the quality, availability and affordability of child care across the country. Education dollars flowing into early education programs in schools are administered by the U.S. Department of Education. Among its priorities are to supplement and complement the efforts of states, the local school systems, the private sector, public and private nonprofit educational research institutions, community-based organizations, parents, and students to improve the quality of education.

Most programs that channel federal funds to state governments are administered by their state counterparts to the federal agencies. Some states have established interagency collaborations similar to that on the federal level to enhance the coordination of early childhood education and policy.

Outside of government there are hundreds, perhaps even thousands, of private advocacy, think-tanks, research, outreach, university, foundation, and public policy institutions in the United States interested in early childhood education and care policies. Periodically, experts are convened at a national forum to debate issues related to early childhood education and care. Experts at these institutions interact with government officials on a formal and informal basis at privately and publicly sponsored conferences, public hearings, and throughout the legislative and budgetary process. The efforts at the federal level are mirrored in the individual states and in metropolitan areas.

Conclusions

Interest in and participation in out-of-home, non-parental child care has increased dramatically in the U.S. over the last few decades, as has policy attention and public funding. The pressures from employed mothers with young children continue to rise, and underscore the need for more accessible, affordable, and better quality ECEC services. The U.S. has carried out more extensive and more rigorous research on the impact of this dramatic change in how young children are reared and cared for than any other country. The hoped-for outcomes now include: the productivity of the current and future workforce; the prevention and reduction of social problems such as welfare dependency, juvenile delinquency, teen pregnancy, and school failure; support for the work, efforts of welfare-dependent and poor parents to help them achieve economic self-sufficiency; enhancing the development of young children; and helping parents fulfill their roles as nurturers and teachers to their children by providing skill training (Kamerman, 2001 ). International ECEC developments, especially in the European Union and in other OECD countries have far outpaced what exists in the U.S.

Preschool for 5 year olds in the form of kindergarten and a one year preparation for primary school is now taken for granted as being a universal experience, and increasingly covering a full school day. Preschool for 4 year olds is moving in this direction, albeit beginning with disadvantaged children first, and a debate continues as to whether public support should aim for universal coverage, or remain limited to the poor. Preschool for the 3 year olds is beginning to gain more attention, but infant and toddler care is still very limited, and largely in the form of informal care; and in contrast to other industrialized countries does not include a paid and job-protected parental leave as an option for infant care. Footnote 3 Federal funding has increased significantly since the mid-1990s, but is still inadequate to meet the need for decent quality, affordable care, and remains largely categorical. We know what high quality ECEC is and how important it is, yet most programs reflect at best, mediocre quality. Staff is often not in receipt of appropriate training, and when they are, may still not be paid adequately. Most important, of greatest concern, is the fragmented delivery system, still largely private and so divided between “care” and “education”, that even. Data on access, coverage, and funding is difficult to disaggregate.

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This paper reports an overview of contemporary research on early childhood mathematics teaching and learning presented at recent mathematics education research conferences and papers included in the special issue (2020–4) of ZDM Mathematics Education . The research covers the broad spectrum of educational research focusing on different content and methods in teaching and learning mathematics among the youngest children in the educational systems. Particular focus in this paper is directed to what lessons can be drawn from teaching interventions in early childhood, what facilitates children’s mathematical learning and development, and what mathematical key concepts can be observed in children. Together, these themes offer a coherent view of the complexity of researching mathematical teaching and learning in early childhood, but the research also brings this field forward by adding new knowledge that extends our understanding of aspects of mathematics education and research in this area, in the dynamic context of early childhood. This knowledge is important for future research and for the development of educational practices.

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1 Introduction

Early childhood mathematics education is a rich field of study and practice that includes the provision of stimulating activities and learning environments, organized and orchestrated by teachers, care-takers and other professionals with the aim of offering young children experiences that extend their knowledge and development of mathematical concepts and skills. Generally, early childhood mathematics education involves children aged 3–6 years, but in many countries even the youngest toddlers go to early childhood centres. Therefore, contemporary research on early mathematics education focuses on children from birth until they enter formal schooling in the first grade. To develop this field of research, a strong foundation of theory and methodology is necessary, along with consideration of the practical settings of young children’s learning as well as the societal needs and relevant educational policy frameworks. Moreover, from a didactical perspective, it also requires consideration of the essence of the mathematics to be taught to young children.

High-quality research grounded in theory is necessary for all areas of mathematics education, in order to move forward and contribute to the generation of new knowledge from which the educational practice can benefit. Since there is much evidence that later development in mathematics is laid in the early years (e.g., Duncan et al. 2007 ; Krajewski and Schneider 2009 ; Levine et al. 2010 ), such high-quality research is especially critical for early childhood mathematics education. Research involving young children entails certain challenges that cannot simply be solved by adopting research designs that are used with older students. The aim of gaining deep knowledge of how young children’s mathematical understanding can be fostered places high demands on research methods. As early as 40 years ago, Donaldson ( 1978 ) stated that children act differently in their everyday situations than they do in experiment situations, and this has been confirmed by many others since then. Thus, gaining knowledge about teaching and learning mathematics in the early years requires research that is conducted in various learning environments and that acknowledges that these learning environments are complex, multifaceted, and dynamic.

Research in mathematics education is a relatively recent scientific discipline beginning in the last century (Kilpatrick 2014 ). Investigating young children’s mathematical learning and teaching became part of this discipline much later. Early childhood mathematics has long been the research field of developmental psychology and cognitive sciences. From the studies of mental abilities and thinking in mathematical problem-solving carried out in these disciplines, we have gained knowledge about the influence of working memory and attention span (e.g., Ashcraft et al. 1992 ; Passolunghi and Costa 2016 ; Stipek and Valentino 2015 ), as well as about the role of innate abilities of numerical awareness in children’s mathematical performance (e.g., Butterworth 2005 ; Wynn 1998 ). Yet, these studies lack a deeper investigation of the mathematics that is performed and how it is developed by children. Neither do such investigations address why certain mathematical competencies are important or why some activities stimulate their development and others do not. Contrary to psychological research, mathematics education research has a didactic perspective, which means that it is linked to the perspective of the learning child, the teaching teacher, and the environment offering learning opportunities in which the teaching and learning take place. Above all, didactic research distinguishes itself from psychological research because it deals explicitly with the question of what the mathematics is in early childhood activities, both within and outside formal education.

2 A brief overview of the current field of early mathematics education research

As shown by the many publications on teaching and learning of mathematics in early childhood that have been released in the past few years, this area of mathematics education research has increasingly become a mature discipline. The same is reflected by the special interest groups, working groups, and research fora dedicated to mathematics education in the early years. No self-respecting conference today can afford not to pay attention to the area of early mathematics, and there are now also communities and conferences that focus exclusively on early childhood mathematics education. All these communities and conferences are the epicentres where the latest developments in this field are brought together. To set the scene for research on early childhood mathematics teaching and learning, without it being complete, we first provide a brief overview of recently presented and discussed early mathematics education research. As an orientation point for this overview, we used what has recently been presented by researchers at three international meetings.

2.1 CERME 11 thematic working group (TWG) on early years mathematics

A conference that already has a considerable track record for including early childhood mathematics as a fixed part of its programme is the biennial conference of the European Society for Research in Mathematics Education (ERME). This conference started in 2009 with a Thematic Working Group (TWG) on Early Years Mathematics. Since then, the number of participants in this group has grown consistently. In 2019, this TWG (that is, TWG13) consisted not only of European researchers but also attracted participants from Canada, Japan, and Malawi. The most dominant theme presented there involved studies of children’s emerging number knowledge. Many of these presentations were traditional in design, including giving children tasks that had to be solved both individually when the children were interviewed and when they worked in groups in a classroom setting. Based on these studies, researchers formulated descriptions of the children’s knowledge. Sometimes, learning trajectories could be generated from these empirical observations. However, within this TWG several examples of studies with more innovative designs and research settings were also presented, including different modes of exploring and expressing numbers, which can extend our knowledge of early childhood mathematics education. An example of such research is Bjørnebye’s ( 2019 ) study, in which a dice game including elements of multiple representations and embodiment of counting strategies opened up the possibility of observing how children’s actions and responses reflect their understanding. Other studies investigated how affordances of manipulatives and applications encouraged children to develop new ways of thinking about numbers either by working in a digital environment (Bakos and Sinclair 2019 ) or by using their fingers to represent numbers (Lüken 2019 ; Björklund and Runesson Kempe 2019 ).

A characteristic of the research community gathered at CERME11 TWG13 is that the participants generally had in common an interest in better understanding the mathematical thinking of the child. Therefore, it was considered crucial that research establish clues for how to recognize mathematical thinking in the early years. For this purpose, Sprenger and Benz ( 2019 ) used eye-tracking data, as this platform was considered to contribute to the analysis of children’s perception of structure in the process of determining quantities. Yet, what Sprenger and Benz discovered is that data from technological devices still need to be interpreted, and that other expressions of children’s perceptions and reasoning are necessary assets for drawing valid conclusions.

A further important issue that was present at CERME11 TWG13 was related to teaching practice. Specifically, several presentations addressed the questions of how mathematics education should be orchestrated in early childhood education and what opportunities to learn should be offered to children. For example, Breive ( 2019 ) investigated the link between inquiry-based education and open-ended problem-solving, and the role of the teacher in orchestrating such conditions for mathematical exploration. In her paper, Breive described the teachers’ behaviour in terms of the degrees of freedom offered to the children with respect to their actions related to the mathematical content and context. Based on the data she collected, Breive concluded that teachers’ ways of acting, and the accompanying learning opportunities, should be given more attention within early mathematics education research. Similarly, Vogler ( 2019 ), who observed teacher–child group interactions, concluded that so-called indirect learning (which can be found as a common approach in many preschool settings) may induce an obstacle to learning mathematics embedded in activities if there is not a mutual understanding of what learning content is the aim of the activity. In line with these two studies, other researchers who focused on teachers’ interactions with children also highlighted critical issues for educational practice and supported further research inquiries.

Another source for learning about the latest developments in early childhood mathematics education research is the POEM conferences (Mathematics education perspective on early mathematics learning between the poles of instruction and construction). The latest conference, POEM4, was held in 2018. The presentations published in the conference proceedings (Carlsen et al. 2020 ) all, in one way or another, reflect the question “In what way—and how much—should children be ‘educated’ in mathematics before entering primary school?” This was also the recurring question in the discussions between the participating scholars. Among the contributions, three themes stood out: children’s mathematical reasoning, early mathematics teaching, and parents’ role in children’s mathematical development. There was a strong interest in children’s reasoning abilities and strategies in problem-solving. For example, Tsamir et al. ( 2020 ) investigated how children express their understanding of patterning. For this purpose, the researchers provided preschoolers with patterns to be copied and compared, while observing their strategies. Children’s strategy use was also observed in relation to play situations. Bjørnebye and Sigurjonsson ( 2020 ) observed them in teacher-led outdoor games, while Lossius and Lundhaug ( 2020 ) observed child-initiated play activities. Some researchers used their observations of children’s encounters with mathematical content for theoretical discussions on how to understand children’s meaning-making, for example by taking the semiotic mediation perspective (e.g., Bartolini Bussi 2020 ) or through the lens of attentional processes (Verschaffel et al. 2020 ).

With respect to early mathematics teaching, at POEM4 it was discussed that teachers’ educational work largely concerns how to empower children in the learning process, assuming that children have agency in their learning (Radford 2020 ). Some of the presented studies (e.g., Palmér and Björklund 2020 ) specifically chose children's perspectives and problematized how seriation was made a content for learning in a children’s story. They showed how different manipulatives and tools used in teaching have different implications for what is made possible for the children to learn. A critical but essential notion was expressed by Tzekaki ( 2020 ), who underlined that whether children act and think mathematically and learn mathematical concepts depends on what is defined to be mathematical thinking and acting. In line with this perspective, Keuch and Brandt ( 2020 ) and Bruns et al. ( 2020 ) also raised the issue that teachers’ and student teachers’ knowledge of mathematics in early childhood education affects their readiness to exploit the content in ways that facilitate children’s mathematical learning.

The issue of the knowledge of mathematics in early childhood was also addressed in papers on the role of parents in children’s learning of mathematics. Parents are recognized as young children’s first educators, contributing to their mathematical understanding and skills. One example of this research focus is Lembrér’s ( 2020 ) study. In order to know what experiences children bring with them into preschool education and thus might inform their encounter with mathematics, she investigated what parents value in the mathematics activities in which their children are engaged at home.

2.3 ICME-13 monograph “Contemporary research and perspectives on early childhood mathematics education”

The ICME-13 Monograph “Contemporary research and perspectives on early childhood mathematics education” (Elia et al. 2018 ) is the third source for becoming informed about the state of the art in the field of teaching and learning mathematics in early childhood. This book, which has its foundations in the ICME-13 (International Congress on Mathematical Education) Topic Study Group 1 (TSG1) “Early childhood mathematics education” held in 2016, contains chapters on a broad range of topics grouped into five key themes: pattern and structure, number sense, embodied action and context, technology, and early childhood educators’ professional issues and education.

Within these themes, the domain-overarching theme of pattern and structure played a prominent role. As Mulligan and Mitchelmore ( 2018 ) showed in a series of studies, children’s awareness of mathematical structures turned out to be crucial for acquiring mathematical competence. Particularly children’s structuring skills were found to be critical to developing coherent mathematical concepts and relationships. These findings are in line with Lüken and Kampmann’s ( 2018 ) intervention study with first graders, in which 5 months of explicit teaching of pattern and structure during regular mathematics lessons resulted in significant differences between pre- and post-test arithmetic achievement scores in the intervention group. Moreover, the intervention was most beneficial to the low-achieving children.

The research within the theme number sense examined a large variety of different aspects of number development. For example, there was a study about children’s enumeration skills when making lists for designating and representing collections of objects (Dorier and Coutat 2016 ). Also, attention was paid to the use of numerical finger gestures and other bodily-based communication in order to facilitate the learning process (Rinvold 2016 ), children’s spontaneous focusing on numerosity (SFON) (Rathé et al. 2018 ; Bojorque et al. 2018 ), and the link between writing skills and number development (Adenegan 2016 ). Furthermore, an exploration of children’s ability to operate with numbers revealed that 5-year-olds were able to solve multiplication and division problems when they were presented in familiar contexts (Young-Loveridge and Bicknell 2016 ).

In the theme embodied action and context , Karsli’s ( 2016 ) video-ethnographic research in a pre-kindergarten classroom showed that young children’s hand and body movements hold rich potential for engaging them in mathematics, and underlined the importance of early childhood teachers’ attention to the embodied ways in which children engage with mathematics, with potential for creating teachable moments. Other studies investigated children’s engagement in the context of play. In Henschen’s ( 2016 ) study free play was examined, while Nakken et al. ( 2016 ) compared free with guided play, of which the latter resulted in the children exhibiting deeper mathematical thinking, and engagement with more specific mathematical concepts. Anderson and Anderson ( 2018 ) broadened the scope by investigating children’s learning of mathematics in their home environment. Thom’s ( 2018 ) and Elia’s ( 2018 ) research on geometrical and spatial thinking in early childhood offered further insights into the crucial role of the body and other semiotic resources (language, drawings, and artefacts) by which young children develop and communicate spatial-geometrical thinking. A general conclusion within this theme was that the limited ways in which young children are invited to engage with geometrical, spatial, and measurement concepts undervalue the embodied, gestural, in-context nature of their mathematical thinking.

The theme technology specifically addressed the integration of technology into early childhood mathematics teaching and learning both at school and at home. The focus was mostly on touch-screen tablet-based applications. Because this new technology significantly differs from the traditional physical aid materials, professional development is needed to help educators identify and implement effective uses of these applications. To learn more about the role of the educator (teacher or parent) in the child’s interaction with the software, Baccaglini-Frank ( 2018 ) carried out an analysis of student-software-teacher relations, revealing how the teacher’s goal of helping the children experience success actually limited their development of numerical abilities. The use of technology also opened a window to a new perspective in early childhood mathematics, namely by exposing young children to advanced mathematics such as understanding symmetric transformation (Fletcher and Ginsburg 2016 ) and dealing with large numbers (also in symbolic form) and ordinality (Sinclair 2018 ).

In the theme early childhood educators’ professional issues and education , Cooke and Bruns ( 2018 ) provided a comprehensive overview of the various contributions in TSG1, for which they proposed to distinguish conditions at three levels that influence opportunities for young children to develop mathematical understanding and skills. At the macro level, curricula provide a framework (aims, content to learn, and activities) for mathematics teaching and learning in early childhood, with varying views. Several papers mentioned the tensions regarding new curricula and frameworks that may impose mathematical content rather than allowing the child to develop understanding of mathematical concepts through play. At the meso level, with focus on the teachers’ competence, all involved papers agreed as to the importance that the teacher possess a fundamental understanding of mathematics as the basis for high-quality early mathematics education. However, different studies used different conceptualizations and instruments to measure teachers’ mathematical competence. The micro level refers to the mathematics educational programmes and materials, as well as to the required training for teachers to develop their ability to effectively select and implement such programmes that address children’s mathematical needs (Fritz-Stratmann et al. 2016 ).

In sum, the common themes that stand out from the three international meetings are children’s learning through play, and concerns regarding how to apply content-focused teaching, with or without technology. We found that a great deal of the research is on children’s mathematical thinking and learning, including two main areas concerning children’s emerging number knowledge and children’s learning of patterns. It is noteworthy that in both areas, how children perceive structure or how they manifest structuring abilities were analysed in several of the studies. There were also a number of studies that focused on how finger patterns, gestures, or bodily-based communication may facilitate children’s learning of numbers.

Children’s learning through free or guided play is also a main issue that was discussed. Teachers’ guiding interaction with children in play was shown to contribute more to deeper mathematical thinking and engagement with specific mathematical content. How teaching affects children’s learning opportunities in preschool was furthermore of great concern in several of the studies. A conclusion drawn from this research is that teachers’ ways of acting and the learning opportunities created for children should be given more attention. In what way, and how much, children should be educated before entering primary school remains a central issue.

3 The contributions of this special issue

In this special issue of ZDM Mathematics Education (Issue 2020–4), contemporary research on early childhood mathematics teaching and learning is discussed by researchers from all over the world. The initiative emanated from the 42nd PME conference in Umeå, Sweden (July 2018), where we had the opportunity to organize a Research Forum in which researchers involved in the field of early childhood mathematics education gathered to present and discuss theoretical and methodological challenges and outcomes of studies on learning and teaching arithmetic skills in early years (Björklund et al. 2018 ; Van den Heuvel-Panhuizen 2018 ). The conclusion of the Research Forum was that early childhood mathematics education research is key, but that more efforts are needed to bring together the state of the art within this field as a foundation for moving early childhood mathematics education research forward. This special issue again provides a window into the contemporary field of research on early childhood mathematics teaching and learning. To discuss what this special issue adds to this field and reflect on the challenges that lie ahead for research on early childhood mathematics education, in the next section we synthesize the themes that emerge from the 15 papers included in this special issue. Each theme highlights the papers’ shared knowledge and contributions to research methods. Many papers are related to several themes, but for our discussion we chose those papers that predominantly belong to a particular theme. In total, we identified three recurring themes: the early interventions and their effects, the facilitating factors for learning and development, and the mathematical key concepts that can be observed in children. Together, these themes bring to the fore aspects that are essential for understanding the learning and teaching of mathematics in the early years.

3.1 What lessons can be drawn from interventions?

Research shows that children’s development of mathematical skills and knowledge is often influenced by socio-economic and curricular factors, and by social interaction in both short- and long-term perspectives (Pruden et al. 2011 ). Thus, there is a raised awareness of the impact early childhood education may have on reducing differences in conditions for learning and on increasing and securing equal opportunities for a good foundation in learning for all children. Based on their meta study of early mathematics education research, Duncan et al. ( 2007 ) stated that early intervention counts and numerous references to the same study indicate that this is an important standpoint in research. Why else indulge in the challenging task of researching learning among the youngest in our education systems, if one does not believe that efforts made through teaching are significant for children’s wellbeing and lifelong learning path?

Research on teaching and learning mathematics often shares a common research design in which interventions are implemented (designed, conducted, and the outcomes assessed) with the aim of finding ways to improve teaching practice for the benefit of the learning child, and often to reduce socio-economic inequality. Intervention studies can be objects of research in different ways, focusing on the children’s learning outcomes or the teaching practices. Nevertheless, the goal is to enhance learning through improved teaching. In the papers in this special issue we find efforts to implement well-designed interventions, explicitly focusing on how to teach. Some implement and analyse fine-grained differences in (teaching) actions and the effects on children’s attention to certain content (Paliwal and Baroody 2020 ; Mulligan et al. 2020 ), while others study the effects of attentiveness to children’s experiences and knowledge and the related choices of tasks (Clements et al. 2020 ; Grando and Lopes 2020 ). Nevertheless, essential to studying intervention success or failure is how learning outcomes are measured and interpreted, which is also an important aspect of early childhood mathematics education research (Li et al. 2020 ).

How teaching is framed to present mathematical content to young children, in order for it to be meaningful to them, and in order to be attentive to children’s experiences and knowledge, is investigated and discussed by Grando and Lopes ( 2020 ). Through narratives provided by early childhood teachers, they find insights into how teachers chose to frame the subjects of statistics and probability in ways that engaged children and were responsive to the children’s own experiences, rather than using materials provided by textbooks. Unconventional teaching methods whereby teachers turned their mathematics classroom into a space of creative insubordination are discussed in this paper in relation to the opportunities they offer children to become equipped with critical thinking. The authors argue that the specific content—statistics and probability—demands problematizing activities and experimentation with uncertain outcomes of problems in order to develop probabilistic thinking. This study highlights an essential issue in didactical research: that the content to be taught is not indifferent to how the teaching is designed. The study particularly raises concerns that the design of teaching cannot be random but rather has to be linked to the educational environment and the students attending that particular environment. Consequently, the generalizability of intervention programmes and teaching methods has to be taken into serious consideration if they are to be implemented in different educational settings.

Clements et al. ( 2020 ) set out to investigate the efficacy of implementing an intervention programme in which instructions and progression are grounded in a research-based learning trajectory. Even though the programme itself had previously been found to have positive outcomes for preschool children’s mathematics learning, the goal of the current study was to investigate how to teach in the most successful way. For this purpose, the authors used the same programme but adapted the choices of the tasks’ difficulty level to the children’s current knowledge levels. How to teach was then related to what to teach individual children. Results indicate that skipping difficulty levels to shorten the steps to the learning goals was not successful. This thorough investigation of teaching by adapting the complexity of the content to the child’s ability to learn best what is intended draws attention to the delicate work of teaching in early childhood education. The study supports child-centred approaches that are sensitive to the individual needs and potential of the child, while simultaneously aiming for the learning goals set by the curriculum.

While Clements et al. investigated the effects of an intervention programme covering broader numerical knowledge, Paliwal and Baroody ( 2020 ) aimed to investigate what conditions for learning the cardinality principle are most effective and how subitizing abilities impact on cardinality knowledge achievement. Their efforts were directed towards a fine-grained analysis of how to teach this aspect of the number concept, and what learning processes different approaches elicit in children. What stands out in their study is that they used a highly advanced research design, which allowed them to examine the effects of different ways of directing children’s attention to seeing numbers’ cardinality. In their paper, they point out the importance of directing children’s attention to various ways of seeing numbers’ cardinality, as follows: as a constructing act by adding units to get a number; as an act starting from naming the whole set with a counting word and then differentiating the added units by counting; and a third condition, attending only to single units in a counting act. Thus, their intervention was designed with explicit rigour as to what was made possible for the children to experience, and their investigation concerned the learning outcomes of the different conditions. While this attention in Paliwal and Baroody’s study to the different conditions can at first glance be considered subtle and far from the instruction children encounter in their mathematics education, the study offers insight into the importance of teachers’ awareness of their way of directing children’s attention to certain meanings of the content.

In another paper focusing on the effects of an intervention programme, Mulligan et al. ( 2020 ) analysed children’s written answers to pattern tasks in order to identify differences and changes in their structural awareness. They found a positive effect on the children’s development of awareness of mathematical pattern and structure (AMPS), and showed how the levels changed as an effect of a 37-week intervention programme. Mulligan et al. add to the field of early childhood mathematics knowledge of a particular ability (structural awareness), how it can be identified among young children, and also how the ability changes over a prolonged period of time (during an intervention), which may provide insight into what children actually learn while taking part in an intervention programme.

Children’s learning is of course at the centre of attention in intervention studies, and Li et al. ( 2020 ) pay explicit attention to how to interpret results from a pre- and post-diagnostic test. In their study, Li et al. investigated the development of mathematics problem-solving skills among kindergarteners by analysing their responses to a cognitive diagnostic test. As in most large-scale analyses, it can be shown in quantitative terms how children develop in producing correct answers that indicate growth in knowledge within certain domains that are tested for. However, Li et al. take a step further in their inquiry and illustrate how two children who scored similarly on the cognitive diagnostic test before an intervention had made different progress during the intervention period. Li et al. suggest that the reason for this difference may lie in how children understand and approach tasks, indicating different understanding even though similar answers are produced. Quantitative measures alone do not reveal such differences. The study thus shows the significance of paying attention to how children reason in order to solve a task. Based on their study, Li et al. recommend that children’s learning outcomes from participating in interventions be seen in the light of how the effects of interventions are measured, as it is observed that some developed skills do not endure over time and similar outcomes among children may conceal different learning paths.

3.2 What facilitates children’s learning and development?

Today, it is undisputed that the development of mathematical skills and the teaching of emerging skills in the early years are essential for mathematics education and developmental progress in the long term (Aunio and Niemivirta 2010 ; Duncan et al. 2007 ; Krajewski and Schneider 2009 ). However, in contrast to this perspective, a recent overview of the long-term effects of preschool mathematics education and interventions (Watts et al. 2018 ) challenges this almost taken-for-granted assumption, as most early interventions have a substantial fadeout effect. Thus, there is a need to revisit our current knowledge of teaching and learning, and scrutinize what seems to make a difference. Some of the papers in the special issue particularly consider this issue in their efforts to ascertain what facilitates children’s mathematical learning and development, and focus on influential aspects found in play settings (Reikerås 2020 ; Tirosh et al. 2020 ), verbal communication in teaching practices (Hundeland et al. 2020 ), and the home numeracy environment (Rathé et al. 2020 ).

Hundeland et al. ( 2020 ) raise the question of how children learn to use and understand the canonical language of mathematics, and study this aspect in terms of mathematical discourses taking place in kindergarten teaching sessions. They take a sociocultural stance (see Vygotsky 1987 ), seeing communication as the link between internal communication (thinking) and external communication (interaction). Therefore, children’s opportunities to contribute ideas and arguments are vital for their (mathematical) learning processes. Earlier research has also shown that care-takers’ talk influences not only children’s vocabulary but also, for instance, their spatial problem-solving (Pruden et al. 2011 ). The deeper knowledge that the study by Hundeland et al. ( 2020 ) provides regarding the quantity and quality of mathematical talk in which children are involved, offers us better opportunities also to organize supportive and stimulating conditions for knowledge growth.

What differs in the study by Hundeland et al. compared to most others with similar research questions is their focus on the kind of interaction that the mathematical discourse induces, which, based on the chosen sociocultural theoretical framework, should be crucial for positive learning outcomes. However, what they study and compare is the impact on the mathematical discourse that a certain in-service training has. This places mathematics in the spotlight of mathematics education research. While psychological and cognitive research provides us with important knowledge of mental processes and developmental advancement, studies like the one by Hundeland et al. have a clear direction towards understanding, and not least improving, the conditions for children’s learning and development, either by implementing teachers’ professional development or through curriculum improvements.

It is commonly agreed that young children’s learning is often situated in play. In a large-scale observation study, Reikerås ( 2020 ) conducted a thorough examination of the kind of play in which toddlers engage, for the purpose of learning how play skills may be related to early mathematical skills. It was found that competencies that allow the child to be active in solitary and parallel play, as well as children’s ability to initiate and remain in a play activity, correlated positively with the toddlers’ mathematical skills. The kind of play skills that showed the highest correlation with mathematical skills was their competence to interact in play. General social play skills thus seem to have an impact on mathematical learning, but Reikerås’ study cannot reveal how these are connected or any causal effects. An effort to better understand the interaction going on in toddlers’ play is made by Tirosh et al. ( 2020 ), investigating the challenges toddlers may face as they practise one-to-one correspondence in a playful context, and how different individuals participate in the playful mathematical context. Here, interaction and social skills become one issue with an impact on the learning opportunities arising in the play.

In many cases, the messy context of children’s play is a methodological challenge. It is not possible to control influencing variables to the same extent as in an experimental design. On the other hand, findings from the messy settings are more likely to bring to the fore aspects that were not anticipated, which raises new questions for research and theory development. Design research supports this kind of knowledge contribution, as several cycles are conducted, each developed based on insights from the previous cycle. These cycles adhere to children’s initiatives such as practising one-to-one correspondence in a setting the table task by putting one spoon inside each cup instead of placing one spoon beside each cup (see Tirosh et al. 2020 ); thus, the child is expressing an understanding of the concept, but is expressing it differently than how the task suggests. This highlights the importance of directing attention to instructions used in research studies, and particularly to the language of mathematics and the spatial aspects of props used in a task, related to the possibilities involved as young children interpret and execute a task.

Children take part in cultural life, where today numerical aspects are an inevitable part of the everyday environment. Nevertheless, there are differences in the extent to which children attend to these aspects, and consequently in how they learn the meaning of numbers, graphical representations of numbers, and how to use numbers. A common assumption is that home numeracy environment is a strong factor (LeFevre et al. 2009 ; Skwarchuk et al. 2014 ), which is reflected not least in the abundance of studies regarding socio-cultural background and demographic factors as a pre-cursor for learning progress. Rathé et al. ( 2020 ) put the common assumption to the test—that home environment has an influence on children’s progress in mathematical development—by comparing young children’s tendency to focus spontaneously on numeracy and numerical symbols in their home numeracy environment. Concerning this specific directionality to numbers, which is assumed to have an impact on children’s arithmetic skills in later years (see McMullen et al. 2015 ), based on their study they propose that the home numeracy environment does not seem to have any significant impact.

3.3 What mathematical key concepts can be observed in children?

A great deal of research in the field of early childhood mathematics education studies what mathematics children understand and how this understanding evolves. This knowledge is crucial in designing teaching that contributes to more advanced thinking and problem-solving strategies that support conceptual growth. Therefore, children’s utterances and how they act are the centre of interest for many researchers. Also, in this special issue, much attention is paid to the mathematical key concepts that can be attributed to children’s thinking, resulting in papers addressing children’s understanding of similarity in mathematical objects (Palmér and Van Bommel 2020 ), their understanding and use of structures (Sprenger and Bentz 2020 ; Kullberg and Björklund 2020 ), their understanding of the concept of cardinality and ordinality (Askew and Venkat 2020 ), and the underlying structure of their quantitative competencies (Van den Heuvel-Panhuizen and Elia 2020 ).

Children’s expressions, and how they are allowed to express themselves, are critical for our understanding of the learning of mathematics. Children’s problem posing is one aspect that can tell us about their understanding of mathematics (Cai et al. 2015 ). In the special issue, this is particularly addressed in the paper by Palmér and Van Bommel ( 2020 ), who investigated children’s understanding of similarity in mathematical objects. They analysed how children themselves created tasks in three-dimensional geometry that were similar to a previous problem-solving task they had worked on. It is suggested that this finding sheds light on the children’s interpretation of the specific mathematical features of the original task.

How children perceive structure has been shown to play an important role in how they, for example, determine a number of objects or solve an arithmetic problem (Ellemor-Collins and Wright 2009 ; Resnick 1983 ). In line with these earlier studies, Sprenger and Bentz ( 2020 ) investigated how 5-year-olds perceive structures in visually presented sets. By having the children determine the number of eggs in a 10-egg box while using an eye-tracking device (and recording the children’s utterances and gestures), they were able to analyse the children’s gaze when determining the cardinality of the set, and thereby gain insight into the process of perception. The eye-tracking data showed, for example, that many of the children were able to see structures (e.g. 4 + 1 or 3 + 2) and use them to determine a quantity without having to count all the objects. The authors argue that children’s ability to perceive structures in sets and use them to determine cardinality is central for their further arithmetic learning, as how children perceive sets (e.g., as individual objects, as a composite whole, or in structured part-whole relations) affects the strategies they use for solving arithmetic tasks.

Similar ideas are found in the study by Kullberg and Björklund ( 2020 ), who studied 5-year-olds’ use of finger patterns to structure number relations while solving an arithmetic problem. They identified two major ways of structuring the task: only structuring, and counting and structuring. In the group that both structured using their fingers and counted on some fingers, some ways were found to be more powerful. Children who solved the arithmetic task (3 + _ = 8) by creating a finger pattern of eight raised fingers and simultaneously identifying (‘seeing’) the missing part (5) on two hands (3 + (2 + 3) = 8) were more successful in solving arithmetic tasks, even in a later follow-up assessment. It is suggested that a possible reason for this later success is that these children were able to see numbers as parts included in other numbers, which has been found in earlier research (Resnick 1983 ) to be important for developing arithmetic skills.

Baccaglini-Frank et al. ( 2020 ) also argue that the appropriate use of fingers can contribute to developing children’s number sense. They studied how 4-year-olds interacted (verbally and using finger patterns) when using the application TouchCounts. The app combines multi-touch with audile, visual, and symbolic representation, and several solution strategies are possible, affording the simultaneous experience of, for example, finger patterns on the screen, with the number both seen and spoken. In their paper the authors emphasize how multimodal affordances may encourage children to use different strategies in response to different tasks, and thus experience a broad range of abilities related to number sense, including both cardinality and ordinality.

Askew and Venkat ( 2020 ) examined children’s understanding of the concept of cardinality and ordinality in connection with their awareness of additive and multiplicative number relations. To investigate this topic, first graders (6- and 7-year-olds) in South Africa were asked to position the numerals 1–9 on a bounded 0–10 number line. The children were able to do this in the correct order, with the fewest errors at the upper and lower ends of the number range. Furthermore, evidence was found that awareness of ordinality and that of cardinality develop alongside each other. However, the logarithmic scale, predicted in earlier research, which is considered to indicate a multiplicative structuring of number relationships, was not confirmed in the South African data. Instead, when the numerals grew larger the intervals became more stretched out rather than compressed. In fact, the children’s responses were closer to the linear model, which is considered to indicate an additive structuring of number relationships. Also, the use of unit sizes that did not take into account the length of the number line, together with the underestimation of the position of 5 on the 0–10 line, offered limited evidence of the children’s awareness of the multiplicative structure of the cardinality of numbers. More research is needed to disclose the deep interconnections between children’s understanding of cardinality and ordinality, and their understanding of multiplicative and additive number relations.

Another effort to unravel the complex nature of children’s early number understanding was carried out by Van den Heuvel-Panhuizen and Elia ( 2020 ), investigating the structure of the quantitative competence repertoire of kindergartners. Based on a literature review, they arrived at a model consisting of two constituent parts: quantification (the ability to connect a number to a given collection of objects) and quantitative reasoning (the ability to think and operate with quantities). Quantification was split up into counting and subitizing, and quantitative reasoning into additive and multiplicative reasoning. Although this model is partly in line with models found in earlier research, it also extends previously developed models by including multiplicative reasoning. Data were collected in the Netherlands and Cyprus. A series of confirmatory factor analyses showed that the hypothesized four-factor model fitted the empirical data of the Netherlands, but not those of Cyprus, which clearly challenges the model’s generalizability. A comparison of the component performances in the Dutch sample revealed that, in accordance with other studies, the lowest scores were found for multiplicative reasoning and that the competence of subitizing seems to develop before counting. This was partly confirmed by a statistical implicative analysis at item level. Although this analysis resulted in different implicative chains in the two countries, in both samples the multiplicative reasoning and conceptual subitizing items were found at the top of the chain and the counting and perceptual subitizing items at the end. Also, more research is necessary here, particularly concerning the generalizability of the model to other countries.

4 Future directions for research on early mathematics teaching and learning

After the Research Forum at PME42 we concluded that to move early childhood mathematics education research forward, more efforts are needed to bring together the state of the art within this field. Thus, we proposed a special issue on the theme Research on early childhood mathematics teaching and learning for the purpose of opening up further discussion and inquiry. In this article, the 15 papers included in the special issue are synthesized and discussed in terms of their contribution to the current field of research in early mathematics teaching and learning along with recent research presented at international mathematics education research conferences. Naturally, these do not cover the worldwide field of research, but they at least give a general idea of the current research interests and challenges.

All the papers in this special issue address aspects of early mathematics education and its underlying theories and research methodologies. They share common interests and challenges concerning how to gain knowledge of the youngest children’s mathematical development, and they identify prosperous teaching approaches. Our appeal to researchers participating in the special issue was to cover the broad span of mathematical ideas that are relevant in early childhood education. Nevertheless, we see a strong direction towards research on the learning and teaching of number concepts and basic arithmetic. This is in line with Alpaslan and Erden ( 2015 ) review of early mathematics research published in 2000–2013 in high-ranked scientific journals in the field of mathematics education, in which the most frequently reported research topics were number systems and arithmetic. The same trend is also found in the research addressed in the latest meetings of ICME, ERME, and POEM. We believe further research should widen this scope, and consider and investigate mathematical topics that are currently less highlighted. There is a need for deeper insight into what mathematics means to young children, and also how the foundations can be laid for the domains of spatial and geometric thinking and measurement, as well as for the domains of structures and patterns, data handling, problem-solving and mathematical reasoning.

Moving an educational field forward, however, is not solely based in covering a broad field of content. To strengthen the field, we need to scrutinize the research designs and methods that are used and the knowledge that is generated. Here, new technologies may open up opportunities for designing tools for investigating children’s competencies. However, this initiative goes beyond choosing digital tools or concrete building blocks; it concerns children’s opportunities to express themselves within different environments and make use of tools and manipulatives that may reveal new insights into their competencies and open up for innovative research questions to be posed. What is made available to experience surely has an impact on children’s expressions of knowledge. And expressions in both words and gestures are important keys here to interpreting the youngest children’s knowledge and skills. We can see this in the recent ICME, ERME, and POEM meetings’ presentation of a large variety of research designs and in the papers of this special issue. Many innovative research designs have been developed that allow thorough investigation of children’s mathematical competence and understanding. What we see, for example, is that subtle differences in expression (e.g. gaze, finger use, or ways of posing questions) reveal new and important insights for developing knowledge of children’s mathematical learning. These innovations in methodology allow for the thorough investigation of key features of learning mathematics that go beyond the broad content areas and highlight how mathematical aspects such as cardinality, ordinality, and number structure are experienced by children. Several of the papers in the special issue particularly attend to these aspects, and do so by creating and using new methodologies and technologies.

The consensus in the field of early mathematics education, reflected in the papers and conference presentations, is strong concerning the impact of early interventions on children’s opportunities to thrive as mathematics learners. From longitudinal studies, we know that early knowledge and skills seem to follow through the child’s development; that is, weak mathematical skills in early childhood years are likely to predict weak mathematics performance in later school years (Reikerås and Salomonsen 2019 ; Hannula-Sormunen et al. 2015 ). This means that early intervention and knowledge of how to offer all children a good start for their mathematical learning are essential to the field of early childhood mathematics education. However, it cannot be assumed that simply participating in education, whether it is framed as free or guided play or problem-solving, or stimulating interactive environments, will result in successful learning outcomes, even though most interventions do have a positive impact and most children develop their knowledge to some extent (Wang et al. 2016 ). Common research objectives, therefore, concern intervention implementation, and analyses of children’s learning outcomes from participating in differently designed activities. These studies are of high importance, as they connect the teaching to the learning and provide insights into what seem to be key aspects in the teaching practice. Nevertheless, researching interventions is delicate work, and it is essential to maintain scientific rigor in the design and analysis. Because early childhood education most often takes place in dynamic settings, the conditions under which children learn vary greatly. This diversity is observed in many studies in which children’s engagement in play, both self-initiated and guided, is used as data for analysing their mathematics competencies and learning of mathematics. This phenomenon means that the conditions offered to explore mathematical concepts and principles should be critically examined, along with how learning from interventions is measured and valued. There is a need to determine what works, what seems critical, and what aspects serve as particular challenges. In research, also special attention has to be given to the nature of the teaching practices. What we learn from intervention studies, both those included in the special issue and those in other contemporary research, is the importance of situating research in the current field of knowledge and the context in which the research is conducted. Each study broadens the picture of the teaching–learning relationship, which is by no means one-directional. There are many aspects to consider that potentially influence this relationship, and all of them cannot be included in one study alone.

Early childhood mathematics education research often attends to the opportunities and conditions that are offered for learning. There is no doubt that children’s activities and interaction with others, already from an early age, offer many opportunities to learn mathematical concepts and basic principles, but our ability to discern what children actually learn from the mathematical learning environments offered to them places high demands on the interpretation process. How to understand the processes going on in play and interaction, and what impacts the children’s learning outcomes—what is made possible to learn—often remains an unsolved issue, as the interaction between teacher and children is dynamic, and particularly as play is multidirectional in nature. Studies of interaction in both formal and informal contexts are nevertheless important, as they are conducted in the complex of social and cultural settings that do influence, through norms and individuals’ experiences, what is possible for children to learn.

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Björklund, C., van den Heuvel-Panhuizen, M. & Kullberg, A. Research on early childhood mathematics teaching and learning. ZDM Mathematics Education 52 , 607–619 (2020). https://doi.org/10.1007/s11858-020-01177-3

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Nursery and Non-Nursery Children’s Development Research Paper

Introduction, project description, conclusion and recommendations.

There is general agreement that pre-schooling has a direct effect on the children’s ability to acquire literacy, scientific, and numeracy knowledge which are crucial in cognitive development. There have been increased focus on early childcare and pre-school policies; this has resulted in the movement which urges parents to take their children to nursery. Despite the policies, there are no conclusive studies that have sought to determine the extent to which the nursery school care affects children’s development. Therefore, there is a need for a study to explore whether there are any developmental differences between nursery and non-nursery school children. The target age for the study is children aged between two and three years.

The purpose of the project is to analyze if there are positive effects among the children going to nursery. This will be imperative because the information obtained can be used to inform the parents and policymakers on the merits or lack of it for the nursery childcare.

Project Description / Method

The project is a quantitative study method in which 60 study participants were recruited. The participants are the parents of children aged between 2 and 3. The participants were divided into two groups in which thirty parents had children who go to the nursery while the remaining thirty included parents of children who were not yet enrolled in the nursery. The parents were provided with questionnaires that probed the different aspects of children’s development.

Sampling was by use of both simple random and snowball in which parents with the kids going to the nursery were identified from the school and given questionnaire while those not going were reached through the snowball method. The findings of the study established that there were significant differences. The children going to nursery school showed improved social, communicative, and cognitive development compared to the non-nursery children.

Parents should be encouraged to take their children to the nursery to enhance their development and prepare them for primary schooling.

Topic Overview

In many countries across the globe, there is a notable emphasis on pre-school education. In the U.S., 42% of 4-year-olds normally attend publicly funded pre-schools, and there is a substantial number attending private pre-schools (Yoshikawa et al., 2013). Generally, there has been vigorous debate on the merits of taking children aged between 2 to 4 years to the nursery; however, in most cases, the discussions are not informed by conclusive research evidence. As such, the following paper considers the positive impacts of preschool childcare and whether there are negative influences associated with not taking the child to the nursery. The study is expected to give up-to-date and non-partisan evidence to support or discount the debate.

Background/Literature Review

Early childhood education has gone through drastic changes since the 1990s. In the past, it used to be considered as part of the preparation for the compulsory school; however, today that has changed because some inconclusive research findings point to some positive transformations for the young children aged between two and five years. High-quality nursery care has a longer implication on the development of the child as a learner (Yoshikawa et al., 2013). Different theory frameworks have been applied to explain the changes in terms of cognitive or psychoanalytic developments. A case in point is the Erikson’s Development Theory and Bandura’s Theory.

Erikson’s development theory

Erikson’s theory centers on psychosocial stages of development; the theory was significantly influenced by Feuds Theory on the topography of personality (McLeod, 2008). The theory is divided into eight stages that take place from early childhood to early adulthood, i.e., from infancy to 18 years. Successful completion of each stage leads to a better personality and helps the individual to acquire the basic virtues that relate to the particular developmental point; therefore, one stage endows the youngster with characteristics that are critical in resolving the requirement of the next stage. This signifies that a failure to complete one stage can negatively affect the subsequent developmental stage.

In the review of the children’s development, these stages could be best realized if the child is put in an environment that promotes holistic development (McLeod, 2008). For instance, about children aged between 2 and 3 years, the two significant psychosocial crises they need to address as per the theory are the second and the third stages. The second stage is autonomy versus shame at the ages between 1.5 and 3 years and it is marked by the child acquiring the basic virtue of ‘will’ if he/she completes the stage.

The other stage is the third stage in which the psychosocial crisis at hand is the initiative versus guilt. This stage takes place for children aged between three and five years. This is the period characterized by most parents deciding to take their children to pre-school. According to the provisions of the theory, children are supposed to acquire ‘purpose’ as a basic virtue. To achieve the desired virtues, Burger (2010) emphasizes the need for the children to be put in the right environment.

In this effect, the theory gives a critical view of the various stages of the development that can be applied to understand the needs of the children right from infancy. This is very relevant for every child as they search for their identity. Even though the theory does not advocate for nursery schools, the main emphasis is on providing the child with the best environment that will enhance positive development.

In contemporary times, many parents are involved with different work activities and not have adequate time to monitor the development of their children and expose them to the right socialization processes. The nurseries provide the opportunity for the child to grow in an environment that focuses on holistic development in terms of -social and learning abilities that are key to the future of the child. This does not necessarily point that the developmental stages as pointed in the theory can be developed only at the nursery. Children who are not disadvantaged in their home environment, cognitive and language development can still take place (Weiland & Yoshikawa, 2013).

In a report on the role of pre-school in Australia, Productivity Commission (2014) stated that “nurturing, warm and attentive carers are the most critical attributes of quality in any child care setting, especially for younger children” (p.4).

Concerning Erikson’s theory, the second stage, which is autonomy vs. shame or doubt, denotes the need for the caregivers to ensure a delicate balance. The child should not be assisted in every task because self-control is required but carefully to avoid the loss of self-esteem. This stage applies to children who are between two and three years. The nursery care setting allows the young kids to interact with their peers by playing, and hence allow the child to develop important social skills at an early age. Also, the children interact with trained professionals who monitor and assign them tasks that are relevant to the child’s developmental stage. Proper care at the stage will lead to the child becoming more secure and confident, and hence sets a good foundation for their future.

The third stage is the initiative vs. guilt, which is a transition from the second stage and takes place between the ages of 3 and 5 years. The stage is characterized by vigor action; the children can actively interact with other kids and identify friends. A key feature is that the children are more playful and can organize their play activities such as making games and arranging stack cards. These are signs of cognitive development, and there is a need for a caretaker who can guide the children at the stage to build their learning capabilities (Goodman & Sianesi, 2005).

Bandura’s social learning theory

In theory, Bandura’s argument is on behaviorist development based on operant conditioning and classical conditioning. The theory stipulates that mediating processes take place when there is a stimulus and a response and behavior are learned from a particular environment through observational learning. In the context of the children’s development, children learn by observing the behavior of the people they interact with. The youngsters may be confined at home or nursery. The perspective of classic conditioning or operant conditioning implies that children will have differences based on the environment they are exposed to during their early years (Bandura, 2001).

The environment provides the models from which the children can encode their behavior. Similarly, the behavior learned is reinforced by the internal or external factors which come into conduct with the child. In essence, at the ages of two and three years, children need to be conditioned to a learning environment that will influence their future. As such, in the review of the role of the pre-school in the development of the children, Goodman and Sianesi (2005) pointed out the learning environment at nursery reinforces learning abilities for the children and creates a foundation from which they can internalize some aspects such as language acquisition. It is important to note that the conditioning processes relate to the ‘identification of self’ as pointed out by Feud in explaining the internalization of behavior.

Regarding the mediation process learning, Bandura’s theory holds the view that all humans are, information processors. As such, the cognitive process is an important precursor of observational learning. The theory proposes four critical meditational processes that determine how the child develops. The processes include attention, retention, reproduction, and motivation. Attention relates to the extent a child is exposed to a given behavior.

Retention entails the formation of the memory of the behavior. Therefore, at the third stage of reproduction, Bandura stipulates that that social learning does not take place immediately and hence the need to put the child in an environment in which the desired behavior can be reproduced. It is through the full development of the processes that the child starts to develop a critical evaluation. Just like the case of Erikson’s theory, the environment of growth determines how well the child fully acquires the processes.

According to Weiland and Yoshikawa (2013), there is evidence of developmental benefits noted among children who attend quality child care at the ages of 1-3 years; however, there is no evidence of long-term benefits to such learning. This is because some studies find positive effects, some negative and others no effect. The variances in the findings have been attributed to the age differences and the varying qualities of child care. The current study focuses on a particular age group; therefore, the results are not likely to be affected by age variance.

Aim/s and objective/s / hypothesis

The study objectives include:

  • To find out whether children who go nursery are more developed psychosocially than the children who do not.
  • To find out the effects nursery has on the development of the children.
  • Hypothesis: H 0 . There is no positive benefit for taking children aged between 2 and 3 years to nursery school.

To collect reliable data for this study, the research method employed was quantitative. The quantitative method was used to carry out the study; it provided empirical data that was used to test the null hypothesis. The quantitative data were collected from parents who have children aged between two and three years. The sample size used for the study was 60 parents. This sample was divided into two groups of 30 parents each.

The first group comprised of the parents of children who attend nursery while the second group was for parents whose children were not going to nursery. The main reason for dividing the sample was to provide data that can be comparatively analyzed to establish whether there are developmental differences between the children. The following subsections provide details of how the research was conducted and the rationale applied in carrying out the research.

Sampling Procedure and Sample Size

Sampling is the process of selecting a subset of the target population from the sample frame (Creswell, 2013). One of the key factors that enhance any kind of study is to ensure that a representative sample is selected. This requires a proper definition of the study population and specification of the sturdy frame and the sampling method to be applied. In the present study, the target population is the children; however, they cannot provide the required data so their parents are used as the key study participants to provide the required information. Therefore, the sampling frame is the parents with children aged between two and three years.

Two sampling procedures were used. The procedures were used based on the context of the study to ensure that objective inference could be drawn from the data collected. For the parents with children going to nursery schools, a simple random sampling method was used to identify the 30 parents with children in Inspire Children Nursery. The simple random method is a probability method that gives study participants an equal chance of being included in the study.

The method reduces inclusion bias. Even though the simple random method was used to select the parents to participate in the study, it is important to note that the location, which is Inspire Children Nursery, was purposely selected. The reason for getting the parents from the same learning center was to avoid the variations that have been identified in earlier studies due to different learning environments. It is important to note that differences in the quality of care have been one of the issues that led to the lack of conclusive findings on the role of the nursery in the development of children aged below five years.

In the second group, the sampling procedure used to include parents in the study was snowball sampling. Snowball sampling is a non-probability method which is based on a referral process. In this case, one study participant is used to identify other people who may be incorporated into the study. It is a chain-like process; therefore, one parent of a non-nursery going child was be identified and asked to refer the researcher to another parent.

The rationale for selecting the parents as the main sources of data was due to the experience they have with their children. Also, a sample size of 60 people ensured that diverse information on the children’s development could be deduced.

Data Collection

There are varied methods for collecting, in most cases the selection of the data collection method is influenced by the nature of the study and the type of the variable that is supposed to be measured (Creswell, 2013). In the present study, primary sources of data were used. The sources are the original materials or centers that have first-hand data. The primary sources give direct experiences about the phenomenon being investigated. For the study, the primary sources were the parents because they are best placed to provide objective information that relates to the growth and development of their children.

Instruments for Data Collection

The data collection instrument used in this study was the Ages and Stages Questionnaires (ASQ) and the social demographic questionnaire. The ASQ depended on the age of the child while the social demographic questionnaire collected general information that pertained to the child and the parent. Even though the ASQ questionnaires differed based on age, one thing in common was that they probed the development of the child. It is through these questionnaires that the parents were supposed to provide objective data about their children.

Data Analysis

The data collected from the parents was raw and needed to be operationalized to discover the trends relating to the topic under review. As a result, there was the necessity of a data analysis process. Data analysis comprises of applications that are used by the researcher to synthesize the data to make it easy to draw correlations. In the present study, the analysis was required to examine whether there existed differences between the children going and those not going to nursery. Therefore, the tool used to analyze the quantitative data was SPSS.

Ethical Considerations

In any study, ethical considerations are crucial as they ensure that the study does not negatively infringe on the rights of the people involved. Study ethics entail the behavior that stipulates the relationships between the stakeholders in the research. The main reason for ethics is to make sure that the participants’ reputation is not injured or the research processes do not have adverse consequences. The ethical considerations in any study are philosophical and are influenced by the nature of the study and the prevailing societal norms. In any research, key stakeholders include the researcher, the users of the results, and the participants. In the case of the present study, sensitive data about the development of the children will be collected.

The parents may not be willing to give some of the information if confidentiality is not assured. Therefore, there is a likelihood of ethical issues in the research approach. To address the issues, ethical clearance was obtained from the authorities. Clearance is important as it ensures that a study is confined to the intended purpose and that the study participants are protected from possible misuse of the data they provide. Besides, the parents participating in the study were also required to give written consent.

As noted, for a study to be authentic there is the need to employ procedures that will ensure that the research findings are valid and reliable as the two form the basis for data interpretation. In the study, the primary focus was to determine whether there were developmental differences between children aged between 2-3 years who go to the nursery and their counterparts who do not. The reason for the selection of these age groups is because the years are the basis for the development of the academic and social foundations for the young ones (Burger, 2010). Also, in most jurisdictions, this is the minimum age for starting pre-school.

Therefore, the study procedure applied was first to seek ethical clearance from the concerned authorities. After the clearance had been given, the appropriate data collection tool was prepared and evaluated to determine whether it could collect reliable and credible data. In this case, the research instrument was the ASQ.

The next step entailed the identification of the study participants and seeking their consent to participate in the study. All the study participants were required to fill a social demographic questionnaire. The questionnaire gave overview information about the parent and the child. The variables captured by the social demographic questionnaire were the age of the participants, nationality, income, occupation, the average time the child spends with the parents, and the general information on the likes and dislikes of the child.

For the parents with the kids going to nursery, the parents were identified from the children attending Inspire children Nursery and were expected to collect their questionnaires from the nursery. For the other group of parents, they were identified through a referral process. The duration for answering the questionnaires was approximately 15 minutes. This process ensured that all the questionnaires were answered and returned for the subsequent analysis. The data collected was then entered into a computer for SPSS analysis.

It is important to note that this study excluded children with any form of disability either physical or mental. The rationale for the exclusion is because such children have individualized special needs; this implies that comparison can be drawn with other children without disabilities. Also, for children with disabilities, the needs vary considerably. It is important to note that there was no discrimination in terms of gender representation. Either male or female parent could be admitted into the study. Also, there was no age limit for the parents. The application of the outlined procedures ensured that the desired information was collected, which aided in providing the answers to questions that seek to find out the benefits of the nursery in the development of the child.

Summary of Findings

It is evident from the findings that children who go to the nursery performed better than their peers in terms of the parameters that were assessed. A case in point, the review of the parents’ responses showed that a high percentage of the children aged 3 years performed better on the parameters that were being tested compared to their counterparts who did not go to nursery. Some of the parameters in which nursery children showed higher performance included communication, socialization, and the ability to memorize some simple tasks. For instance, the copying ability for nursery children was relatively higher compared to the non-nursery children.

These findings relate to the dictates of the two theories in the literature review section. For example, Bandura’s operant conditioning and classic conditioning in which children learn from the models they are exposed to. The implication is that the children in the nursery are exposed to other kids who also act as peer models and the professional caretakers who can condition the children to certain developmental processes.

According to the analyzed data, the children who attend the nursery can perform better on cognitive tests. Also, the children had better communicative abilities, higher social competence, and less impulsive. The other positive effect reported is that the children were more cooperative when dealing with the caregivers. The findings also showed that children’s cognitive abilities for those in the Nursery were better developed compared to those who did not go.

The results did cut across the ages; for instance, enhanced the ability to memorize some tasks was reported among the nursery children aged between two and three years. The differences were pronounced among the children aged three years. For those with 24 months, the children going to nursery also performed better in the dimensions tested. However, the differences were not as much pronounced as for the three-year-olds. The findings attest to the fact that Nursery has a positive impact on the development of the child; it enhances holistic development in the various domains of the child.

Recommendations

For a long time, the association between the children’s attending nursery and they’re psychosocial development has been a major issue intriguing parents and policymakers. The findings of the current study provided a direction that the parents can rely on to make informed decisions about measures to take to ensure that their children get the best in the early years of life. Bearing in mind that there are past conclusive studies that have shown that the development of the brain is uniquely sensitive from birth to the school-going age, parents need to take measures to ensure they capitalize on the developing brain.

This is the stage that is the foundation for self-regulation, social interaction, and cognitive learning. This implies that at the early development stages, children need high-quality care to condition them to better physical, mental, and social development.

It is also evident that nursery education may have a direct effect on the cognition, emotional, and social development of the child and impacts positively on the school progress. Therefore, it is recommended that measures should be taken to encourage parents to take children to quality care nurseries which will lay a firm foundation for their holistic development. Secondly, there is a need for policymakers to increase their investments in the pre-schools to ensure that public nurseries are initiated across the country. The nurseries should provide quality care just as in the high-end private centers.

It is important to note that the current study focused only on one center; therefore, there may be variances if different nurseries with differing quality are studied. Thirdly, there is a need for awareness creation to all parents to embrace taking their children to the nursery immediately they reach two years. This is because it exposes the children to a favorable environment managed by professionals who monitor and aid the youngster in the psychosocial development.

Finally, there is also the need for further studies to explore the programs that result in high-quality care in the nursery schools; hence, provide a holistic overview of factors that policymakers should put into consideration.

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IvyPanda. (2024, January 28). Nursery and Non-Nursery Children's Development. https://ivypanda.com/essays/nursery-and-non-nursery-childrens-development/

"Nursery and Non-Nursery Children's Development." IvyPanda , 28 Jan. 2024, ivypanda.com/essays/nursery-and-non-nursery-childrens-development/.

IvyPanda . (2024) 'Nursery and Non-Nursery Children's Development'. 28 January.

IvyPanda . 2024. "Nursery and Non-Nursery Children's Development." January 28, 2024. https://ivypanda.com/essays/nursery-and-non-nursery-childrens-development/.

1. IvyPanda . "Nursery and Non-Nursery Children's Development." January 28, 2024. https://ivypanda.com/essays/nursery-and-non-nursery-childrens-development/.

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This paper is in the following e-collection/theme issue:

Published on 19.3.2024 in Vol 26 (2024)

Long-Term Effectiveness of a Multi-Strategy Choice Architecture Intervention in Increasing Healthy Food Choices of High-School Students From Online Canteens (Click & Crunch High Schools): Cluster Randomized Controlled Trial

Long-term effectiveness of a multi-strategy choice architecture intervention in increasing healthy food choices of high-school students from online canteens (click & crunch high schools): cluster randomized controlled trial.

Authors of this article:

Author Orcid Image

Original Paper

  • Tessa Delaney 1, 2, 3 , PhD   ; 
  • Jacklyn Jackson 1, 2, 3 , PhD   ; 
  • Christophe Lecathelinais 1, 2, 3 , DESS   ; 
  • Tara Clinton-McHarg 4 , PhD   ; 
  • Hannah Lamont 1, 2, 3 , BNutrDiet (Hons)   ; 
  • Sze Lin Yoong 5 , PhD   ; 
  • Luke Wolfenden 1, 2, 3 , PhD   ; 
  • Rachel Sutherland 1, 2, 3 , PhD   ; 
  • Rebecca Wyse 1, 2, 3 , PhD  

1 School of Medicine and Public Health, University of Newcastle, Wallsend, Australia

2 Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia

3 Hunter Medical Research Institute, New Lambton Heights, Australia

4 Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia

5 Faculty of Health, School of Health and Social Development, Global Centre for Preventive Health and Nutrition, Institute for Health Transformation, Deakin University, Melbourne, Australia

Corresponding Author:

Tessa Delaney, PhD

School of Medicine and Public Health

University of Newcastle

Locked Bag 10

Wallsend, 2287

Phone: 61 294617441

Email: [email protected]

Background: School canteens are a recommended setting to influence adolescent nutrition due to their scope to improve student food choices. Online lunch ordering systems (“online canteens”) are increasingly used and represent attractive infrastructure to implement choice architecture interventions that nudge users toward healthier food choices. A recent cluster randomized controlled trial demonstrated the short-term effectiveness (2-month follow-up) of a choice architecture intervention to increase the healthiness of foods purchased by high school students from online canteens. However, there is little evidence regarding the long-term effectiveness of choice architecture interventions targeting adolescent food purchases, particularly those delivered online.

Objective: This study aimed to determine the long-term effectiveness of a multi-strategy choice architecture intervention embedded within online canteen infrastructure in high schools at a 15-month follow-up.

Methods: A cluster randomized controlled trial was undertaken with 1331 students (from 9 high schools) in New South Wales, Australia. Schools were randomized to receive the automated choice architecture intervention (including menu labeling, positioning, feedback, and prompting strategies) or the control (standard online ordering). The foods purchased were classified according to the New South Wales Healthy Canteen strategy as either “everyday,” “occasional,” or “should not be sold.” Primary outcomes were the average proportion of “everyday,” “occasional,” and “should not be sold” items purchased per student. Secondary outcomes were the mean energy, saturated fat, sugar, and sodium content of purchases. Outcomes were assessed using routine data collected by the online canteen.

Results: From baseline to 15-month follow-up, on average, students in the intervention group ordered significantly more “everyday” items (+11.5%, 95% CI 7.3% to 15.6%; P <.001), and significantly fewer “occasional” (–5.4%, 95% CI –9.4% to –1.5%; P =.007) and “should not be sold” items (–6%, 95% CI –9.1% to –2.9%; P <.001), relative to controls. There were no between-group differences over time in the mean energy, saturated fat, sugar, or sodium content of lunch orders.

Conclusions: Given their longer-term effectiveness, choice architecture interventions delivered via online canteens may represent a promising option for policy makers to support healthy eating among high school students.

Trial Registration: Australian Clinical Trials ACTRN12620001338954, https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380546 ; Open Science Framework osf.io/h8zfr, https://osf.io/h8zfr/

Introduction

Adolescents internationally are prone to having poor quality diets [ 1 - 3 ], which are associated with a higher risk of obesity, poor mental health and well-being, and an increased risk of chronic diseases during adulthood [ 4 ]. In particular, data from the most recent national survey of Australian high school children (aged 12-17 years) found that on average 5.7 (SE 0.2) to 6.6 (SE 0.7) serves of discretionary food choices are consumed per day, contributing to 38%-41% of total daily energy intake [ 5 ]. Adolescence represents a transitional life stage, which often coincides with increased autonomy regarding food choices and eating behaviors. Healthy eating interventions that can reach the adolescent population during this key stage are required [ 6 ], as dietary behaviors during adolescence have been shown to track throughout the life span [ 7 ].

High schools are an ideal setting to deliver interventions to improve adolescent nutrition, as they offer ongoing and widespread access to this traditionally hard-to-reach population [ 8 ]. Students have also been shown to consume up to 40% of their daily food intake during school hours, and in Australia over 60% of high school students purchase food at least once per week from their school canteen. However, the foods most commonly purchased from this setting are “less healthy,” discretionary foods high in energy, fat, salt, and sugar [ 9 ].

Interventions that incorporate choice architecture strategies (eg, provision of information, changing default options, and using incentives) [ 10 ] are effective in improving adolescent diet-related outcomes. A recent systematic review found that out of 137 included choice architecture interventions that aimed to modify child or adolescent diet-related outcomes, 74% were effective [ 10 ]. Despite this, of the 137 studies, only 9 were conducted in high schools and while 6 of the 9 studies (67%) were shown to be effective, all of the interventions were short in duration (average 10 weeks) and none assessed long-term effectiveness [ 11 ].

Online lunch ordering systems (henceforth referred to as “online canteens”), where students select and preorder their lunch using the web or mobile apps, are common in Australian schools [ 12 ]. Online canteens represent the optimal infrastructure to implement choice architecture strategies that support students in selecting healthier foods. The research team recently conducted the “Click & Crunch High Schools” cluster randomized controlled trial (RCT). The trial assessed the short-term (2-month) effectiveness of a multi-strategy choice architecture intervention embedded into an online canteen in increasing the relative healthiness of foods purchased at lunch by high school students. At a 2-month follow-up, relative to controls, intervention students purchased significantly more items classified as “everyday” (healthy +5.5%, P <.001) and significantly fewer items classified as “should not be sold” (unhealthy –4.4%, P <.001) [ 13 ]. Although these initial results are promising, evidence suggests that the effects of behavioral interventions can attenuate over time [ 14 , 15 ]. As such, an assessment of the longer-term impact of the intervention on high school students’ lunch purchases is required to better understand how it contributes to long-term behavior change.

Given digital intervention for public health nutrition is still an emerging field, limited studies have been conducted to assess the sustainability of effective interventions. For example, a 2021 umbrella review of 11 systematic reviews of digital interventions to promote healthy eating in children reported that the effectiveness of such interventions in the medium-term and long-term was not well studied [ 16 ]. The research targeting adolescents and high school students is sparser still. As this trial [ 13 ] was the first to investigate the effectiveness of embedding choice architecture strategies into online canteen ordering systems in high school students, this longer-term follow-up represents a novel contribution to the public health nutrition literature regarding the sustainability of digital health interventions for this underresearched group.

Therefore, this study aims to assess the long-term effectiveness (baseline to 15 months) of the “Click & Crunch High Schools” intervention on increasing the relative healthiness of school canteen lunch purchases by high school students.

A description of the trial methods has been previously published [ 13 ]. The original trial methods and 2-month follow-up were prospectively deposited on the Open Science Framework on October 23, 2020 [ 17 ]. The 15-month follow-up was not preregistered however it was conducted per procedures and outcomes as previously registered.

Study Design

This cohort study was conducted as a parallel-group, cluster RCT. Consenting high schools that were using an existing online canteen hosted by Flexischools (InLoop Pty Ltd; a commercial online canteen provider and partner on this research) and located in NSW Australia were randomized to receive either a multi-strategy choice architecture intervention delivered via the online canteen infrastructure or a usual practice control (ie, standard online canteen). Outcome data were collected over 8 weeks at baseline (October-December 2020), 2 months (the period immediately following intervention commencement, February-April 2021; results previously published) [ 13 ], and again at 15-months postintervention commencement (February-April 2022). This paper reports the 15-month findings.

Sample and Recruitment

School canteen managers from eligible schools were contacted by mail and telephone to invite study participation. A total of 9 (4 intervention and 5 control) government and nongovernment (ie, independent or catholic) schools located in NSW Australia that enrolled high school students (aged ~12-18 years), and used Flexischools as their online canteen provider were eligible to participate in the 15-month follow-up. Schools were ineligible for the trial if they had participated in another unrelated “online canteen” research program conducted by the team or were a catholic school located within a diocese in which ethical approval had not been obtained.

As per prespecified eligibility criteria, students were ineligible for inclusion if; they were in grade 12 at baseline data collection as they were unlikely to be still attending school at the follow-up data collection period; or if they had placed recurring lunch orders set before the intervention period as these orders would not have been exposed to the intervention.

Randomization and Blinding

Following recruitment, an independent statistician block randomized schools (in blocks of 2 and 4) using a random number function in Microsoft Excel. Randomization was stratified by school sector (eg, government vs nongovernment), as evidence suggests there are differences in the availability of healthy food between the school sectors [ 18 ]. Schools were unable to be blinded to their group allocation. However, the intervention was applied centrally, and only students at intervention schools could access the intervention strategies via the online ordering system. All student purchasing data was centrally collected by the online provider, reducing any risk of intervention contamination between the groups.

Intervention

The “Click & Crunch High Schools” intervention is described in full elsewhere [ 13 ]. The intervention was underpinned by the principals of choice architecture and sought to encourage the purchase of healthier (ie, “everyday”) items from the school’s online canteen menu. All intervention strategies were integrated into the schools’ existing online canteen and were displayed to students at the point of purchase. All student users of the online canteen at eligible high schools had access to the intervention strategies. The intervention was in place for approximately 15 months (February 2021 to April 2022) until after the 15-month follow-up data collection period. Intervention strategies (see Figure 1 ) are described in the following sections.

nursery school research paper

Menu Labeling

All menu items were classified as either “everyday,” “occasional,” or “should not be sold” based on the criteria outlined in the NSW Healthy School Canteen Strategy. Menu items were labeled with a small colored symbol: a green circle was added next to “everyday” foods, an amber circle was added next to “occasional” foods, and a red circle was added next to “should not be sold” (“caution”) foods. A “menu label key” appeared at the top of the page (eg, “Everyday- best choice for healthy happy students”; “Occasional- choose in combination with Everyday”; “Caution- consider switching, low nutritional value”).

Positioning

“Everyday” menu items and healthier food categories (eg, fruit, salad, and sandwiches) were positioned prominently (ie, first) in the online menu. Research suggests items placed in the middle of menu lists are two times less likely to be purchased than those at the beginning or end [ 19 ]. Therefore, the least healthy “should not be sold” items were placed in the middle and “occasional” items were placed last in menu category lists, respectively. Further, “occasional” or “should not be sold” items with multiple flavors (eg, potato crisps) required the user to first “click” on the item before the full list of flavors appeared (eg, plain, salt and vinegar, and chicken).

Before each lunch order was finalized within the online ordering system, users were shown a personalized summary of the healthiness of their lunch order. The summary included a pie graph displaying the proportion of items in their order that was “everyday,” “occasional,” and “should not be sold,” and a tailored message based on the proportion of “everyday” items in the order (eg, if <99% of items were “everyday”: “Try adding some ‘Everyday’ items for a more balanced meal.” If 100% of items were “everyday”: “Excellent choice! 100% ‘Everyday’ items”).

When “occasional” or “should not be sold” hot food items were chosen they included a prompt to add a fruit or vegetable snack and water. Healthier menu categories (eg, fruit, salad, and sandwiches) included an appealing image and positive purchase prompt (eg, “This is a good choice”).

To support canteen managers’ understanding of the NSW Healthy School Canteen classification system which underpinned the menu labeling, each canteen manager in the intervention group received a “menu feedback report.” The report included feedback comparing the online canteen menu to the recommendations of the NSW Healthy School Canteen Strategy and provided suggestions on how to improve the relative availability of “everyday” items on the menu.

Intervention Fidelity

Once every term during the intervention period (approximately every 10 weeks), a member of the research team monitored each school’s online canteen menu via the Flexischools website. They checked that all menu items, including any new items, were correctly classified according to the NSW Healthy School Canteen Strategy, and that the intervention strategies were applied accordingly. If any menu items were found to be unlabeled or incorrectly labeled, the research team would notify Flexischools and provide instructions for how to apply the intervention strategy correctly.

Control schools did not receive any of the intervention strategies, and were only provided access to the standard online ordering system.

Data Collection and Outcomes

Student purchasing data were automatically collected and stored by Flexischools. Data were collected over 3 distinct 8-week periods, with baseline occurring from October to December 2020 and long-term follow-up occurring 15 months after the intervention commenced (February-April 2022). The 2-month follow-up was the primary trial end point (data collected immediately following intervention commencement, February-April 2021), and has been previously published [ 13 ].

Primary Trial Outcomes

The primary trial outcomes at the 15-month follow-up were identical to those at the 2-month follow-up and included the mean percentage of all online lunch items purchased per student that were classified according to the NSW Healthy School Canteen Strategy as (1) “everyday,” (2) “occasional,” and (3) “should not be sold.” The NSW Healthy Canteen Strategy classifies foods as “everyday” based on their alignment with the core foods groups within the Australian Dietary Guidelines (eg, fruit, vegetables, dairy and alternatives, lean meat and alternatives, and grains) [ 20 ]. Menu items classified as “occasional” or “should not be sold” are considered “noncore” or discretionary foods that are mostly high in energy, saturated fat, sugar, and salt. Further information on the NSW Healthy School Canteen strategy including the nutrition criteria underpinning the strategy are reported elsewhere [ 20 ].

Each canteen menu item was classified against the strategy by a research dietitian using detailed item information (ie, brand, product name, service size, flavor, or recipe) obtained from the canteen manager via telephone or email. Following this, a statistician was able to apply the menu item classification (eg, “everyday”) to the automatically collected purchase data supplied by Flexischools (eg, fresh fruit equaled “everyday”).

Secondary Trial Outcomes

Energy, saturated fat, sugar, and sodium content of online lunch orders.

Secondary outcomes included the mean total energy (kJ), saturated fat (g), sugar (g), and sodium (mg) content of online lunch orders. Using previously established procedures, the dietitian generated the nutrition profile for each menu item by using data from food product databases (for commercially packaged menu items [ 13 , 21 , 22 ]) or FoodWorks (version 9; Xyris Software; for menu items requiring a recipe). The statistician then applied the nutritional profile of each menu item to the student purchasing data provided by Flexischools.

Weekly Canteen Revenue From Online Orders

Purchasing data that were automatically collected by Flexischools were used to calculate the mean weekly revenue from all student online lunch orders for the weeks that the canteen was operational at baseline and long-term follow-up. This outcome was assessed to explore any potential adverse effect of the intervention (eg, a reduction in canteen revenue due to the application of the intervention strategies).

School Characteristics

At baseline, school characteristics including the number of student enrollments, year range, sector (eg, government vs nongovernment), school type (combined primary and high school students’ vs high school only), and postcode were obtained from the government “MySchool” website. As the number of high school student enrollments for combined schools was not available on the “MySchool” website, this data was collected directly from the school.

Canteen Characteristics

Canteen characteristics including operating days per week, frequency of use, and student grade data were obtained from the student purchasing data supplied by Flexischools.

Menu Composition (Pre-Post Intervention)

Using the methods outlined above, a research dietitian assessed the proportion of items on each school’s online menus that were classified as “everyday,” “occasional,” and “should not be sold.” This is reported by intervention and control groups at baseline and 15-month follow-up.

Statistical Analysis

All outcome data were analyzed in SAS (version 9.3; SAS Institute) under an intention-to-treat (ITT) approach whereby all student lunch orders and schools were analyzed based on the groups they were originally allocated. All nutrition outcomes included data from the student cohort (grades 7-11) that had placed at least one order during the baseline period.

Primary and secondary outcomes were assessed using separate linear mixed models by comparing differences between intervention and control groups over time (baseline to 15 months) through the inclusion of a group-by-time interaction fixed effect. All models included a random intercept for schools (to account for potential school-level clustering), a nested random intercept and random time effect for students (to account for repeated measurements between time points), and fixed effects for the school sector and SEIFA (Socio-Economic Indexes for Australia). All available data (baseline, 2 months, and 15 months) were incorporated into the model.

Consistent with previous publications, the denominator for the unit of analysis for primary trial outcomes was the total number of individual items purchased for each student over the three 8-week data collection periods (baseline: October-December 2020; 2 months: February-April 2021; 15 months: February-April 2022).

Differences in the average weekly revenue (a school-level outcome) were assessed using linear mixed models and included data from all students who had placed any order during any of the data collection periods. School and canteen characteristics were previously reported in the 2-month outcome paper and are included here for context.

Given no differences were observed by subgroups (student grade, frequency of canteen use, or school sector) at the primary trial end point (2 months), no subgroup analyses were conducted at the 15-month follow-up.

Sample Size

No sample size calculation was performed for long-term follow-up, sample size estimates were calculated a priori based on the primary trial end point of 2 months [ 13 ]. The original sample size required the participation of 10 schools (222 students per school) to ensure a mean detectable difference of 13% of everyday items with 80% power, an intraclass correlation coefficient of 0.05, and an α of .05 at 2-month follow-up.

Ethical Considerations

The ethical approval for the conduct of this study was provided by the Human Research Ethics Committee of the University of Newcastle (H-2017-0402), and State Education Research Approval Process (SERAP 2018065), as well as relevant Catholic School Dioceses.

The baseline characteristics of the sample are presented in Table 1 . At baseline, on average, control schools had higher student enrollments compared with intervention schools (mean enrollments 800, SD 318 vs 496, SD 226). All other baseline characteristics were similar between groups (no significance testing was performed). For example, all school canteens operated 5 days per week, the majority of schools were located in areas of most socioeconomic advantage, and the majority of students were in grades 7 to 9. The number of participants and orders at baseline and 15-month follow-up can be seen in Figure 2 . While 1331 students from 9 schools provided data at baseline, 332 (25%) students did not place an online order at the 2-month follow-up, and an additional 268 (20%) students did not place an online order at the 15-month follow-up. Of these 268 students, 70 had completed high school (ie, students that were in grade 11 at baseline were no longer at school 15 months later). There were no statistically significant differences between intervention and control participants being lost to follow-up ( P =.08).

a NSW: New South Wales.

b Nongovernment schools were Catholic and independent schools.

c Based on publicly available school statistics (MySchool 2020) or verbally from schools (combined schools only).

d Socio-Economic Indexes for Australia 2016, based on the postcode of the school locality and dichotomized at the NSW median.

e Based on Flexischools purchasing data.

f As classified by a dietitian according to the New South Wales Healthy School Canteen Strategy.

nursery school research paper

Primary Outcomes

The primary outcomes were the average proportion, per student, of “everyday,” “occasional,” and “should not be sold” online lunch items purchased. Relative to controls, over time from baseline to 15-month follow-up, students in the intervention group ordered on average significantly more “everyday” items (+11.5%, 95% CI 7.3% to 15.6%; P <.001), and significantly fewer “occasional” (–5.4%, 95% CI –9.4% to –1.5%; P =.007) and “should not be sold” items (–6%, 95% CI –9.1% to –2.9%; P <.001) in an intention-to-treat (ITT) analysis ( Table 2 ).

a All models included a random intercept for school, a nested random intercept and random time effect for students, and fixed effects for the school sector and Socio-Economic Indexes for Australia. All available data were incorporated into the model (baseline, 2-months, and 15-months) to describe purchasing patterns over time.

b P <.05.

c All $ amounts are in Aus $. A currency exchange rate of Aus $1 = US $0.65 was applicable as of February 2024.

Secondary Outcomes

Average energy, saturated fat, sugar, and sodium content of online lunch orders.

There were no between-group differences over time (baseline to 15-month follow-up) in the average energy (+48.8 kJ, 95% CI –34.6 to 132.2; P =.25), saturated fat (–0.0 g, 95% CI –0.5 to 0.5; P =.99), sugar (+1.7 g, 95% CI –0.1 to 3.5; P =.07), or sodium (+0.35, 95% CI –36.2 to 36.9; P =.99) content of student lunch orders.

Weekly Online Canteen Revenue (Potential Adverse Effect)

While both intervention and control groups increased in revenue (a currency exchange rate of Aus $1=US $0.65 applies) over time (intervention-group baseline: Aus $896.10; intervention-group 15-month follow-up: Aus $1243.80; control-group baseline: Aus $769.60; control-group 15-month follow-up: Aus $1798.50), the increase in the intervention group was significantly lower than the increase in the control group (differential effect –Aus $673.40, 95% CI –Aus $1252.60 to –Aus $94.20; P =.03). To further qualify this effect, a post hoc exploratory analysis was undertaken to explore if students spent more money per order between intervention and control groups over time. The exploratory analysis found no difference in the average spend per student order by intervention and control groups over time (difference Aus $0.07, 95% CI –Aus $0.14 to Aus $0.28; P =.48).

Menu Composition

While no significance testing was performed, the proportion of “everyday,” “occasional,” and “should not be sold” items available on menus at baseline and 15-month follow-up were similar for the intervention and control schools ( Table 3 ).

Of the 4 intervention schools, 3 had 99% (1256/1269 items) of their menu labeled correctly during the 15-month intervention period. The remaining school removed all of their labels in the last 12 weeks of the intervention, resulting in 81% fidelity across the 15-month intervention period.

Principal Results

This is the first study to assess the long-term effectiveness of an intervention embedded within an online lunch ordering system for high school students and is one of few studies to assess the long-term effectiveness of food choice architecture interventions more broadly [ 10 , 23 , 24 ]. The Click & Crunch High Schools cluster RCT found that intervention students, relative to control, ordered significantly more healthy “everyday” items and significantly fewer “less healthy” items from baseline to 15-month follow-up. There were no between-group differences over time in the average energy, saturated fat, sugar, and sodium content of high school student online lunch orders. This study found that the online canteen revenue for both groups increased over 15 months, however, the revenue in the intervention group grew more slowly than the control group. These findings were surprising, given other trials in the school food setting have found no differences between groups in revenue [ 25 - 27 ].

Comparison With Prior Work

While there is limited research to draw direct comparisons of this study, systematic reviews of the school setting have found that very few studies have assessed the long-term effectiveness of nutrition interventions in high schools [ 24 , 28 ]. A systematic review by Mingay and colleagues [ 24 ] found that only 6 of 35 studies assessed the long-term effect (≥12 months) of school meal interventions on the selection or purchase of healthier foods by high school students. Similar to our study, the review found mixed evidence for studies that included multiple dietary outcomes (eg, nutrients vs food groups) in their assessment of long-term effectiveness. In contrast to our study, the review found that shorter interventions (<3 months) had a greater effect on dietary outcomes for high school students [ 24 ]. Contrary to these review findings, our study found that there was a greater magnitude of effect at 15-months compared to the 2-month follow-up (previously reported) [ 13 ]. For example, at 2 months the Click & Crunch High School intervention was effective in increasing “everyday” items (+5.5%, P <.001) and decreasing “should not be sold” (–4.4%, P <.001) items purchased by students, with no difference in the purchase of “occasional” items (–1.2%, P =.47) [ 13 ]. At the 15-month follow-up, the magnitude of effect was greater than that observed at 2 months and the decrease in “occasional” items purchased was now significant (15-months: everyday +11.5%, P <.001; occasional –5.4%, P =.007; should not be sold –6%, P <.001). The increase in effect size over time may in part be explained by the high intervention fidelity, the intervention type (choice architecture vs food provision), and the number of strategies employed in this trial. Furthermore, the greater length of time that students were exposed to the intervention may have increased the likelihood of habitual patterns in the purchasing of more healthy foods. The sustained intervention effectiveness may also be attributable to the precommitment involved with “preordering,” which may prevent impulse purchasing of “less healthy” foods due to hunger-based cues [ 10 ].

Although this is the first RCT to describe the long-term effectiveness of an online choice architecture intervention in the high school setting (enrolling students aged ~12-18 years) a similar pattern of results has been found in related food service settings [ 29 , 30 ]. For example, a longitudinal study undertaken with adults in a large hospital cafeteria found that a 2-year choice architecture intervention involving traffic light labeling, product placement, and promotion increased the sale of “healthy” items by 5% and decreased the sale of unhealthy items by 3% ( P <.001). In the primary school setting (aged 5-12 years), the same Click & Crunch intervention was found to be effective at improving healthy food purchases by primary school students at 18 months (+3.8% “everyday” and –2.6% “less healthy” items purchased) [ 29 ]. Such findings demonstrate the potential merit of the Click & Crunch intervention on improving the nutritional quality of both primary and high school student online lunch purchases over both the short and longer term and challenge the previously held notion that choice architecture interventions may attenuate over time due to their “novelty effect” or “label fatigue” experienced by end users [ 10 ].

Broader Implications of This Research

The findings of this trial may have broader relevance to the online food ordering systems more generally. The World Health Organization has identified the need to leverage online food delivery systems for public health benefits [ 31 ]. This is the first trial to embed public health nutrition strategies within online food ordering systems for adolescents. With the exponential rise in related meal delivery app use particularly by adolescents and young adults (aged >15 years) [ 32 ], these research findings are likely to be of interest to policy makers investigating how to leverage such systems for public health benefit.

Strengths and Limitations

This cluster RCT had several strengths, including the robust trial design, objectively collected purchase data, and the use of a real-world online lunch ordering system to deliver simple choice architecture strategies. Importantly, it is one of few studies assessing the long-term effects on food purchase or consumption of a choice architecture intervention and the first to do so in the high school setting. Despite this, this study had several limitations. In addition to those already discussed in the 2-month follow-up [ 13 ], this study did not assess intervention costs or acceptability which are key determinants of intervention scalability [ 33 ]. Therefore, to support public health decision-making regarding the scalability of these interventions, future research that explores the acceptability of the intervention to end users (high school canteen managers and students) and intervention costs including cost-effectiveness may be warranted. Furthermore, as this study did not find differences in nutrient outcomes (energy, saturated fat, sugar, and sodium), future research may be required to understand the differential effect of alternate menu labeling systems (eg, kJ labeling) on nutrient-based outcomes. Finally, as outlined in the 2-month follow-up [ 13 ], to achieve population-wide improvements in adolescent nutrition this intervention should be considered in addition to broader public health nutrition strategies that reach both users and nonusers of online canteens in the high school setting.

Conclusions

Despite the limitations, this is the first RCT to explore the long-term effectiveness of a choice architecture intervention embedded within an online canteen targeting high-school students and one of only a few choice architecture interventions delivered in the high-school setting. The findings suggest that there are long-term effects of up to 15 months after intervention commencement, including a significant increase in healthy “everyday” items and a significant reduction in less healthy “occasional” and “should not be sold” items. This provides valuable evidence about the potential long-term effect of choice architecture interventions delivered via online canteens on adolescent school lunch ordering and may be useful to policy makers interested in improving adolescent diet within the high school setting. Further research is required to determine the feasibility of disseminating such interventions to schools at scale, and if these effects transfer to other online food environments targeting different end users (ie, adults and health care workers) such as workplaces, hospital settings, and the fast food sector.

Acknowledgments

We wish to thank Flexischools, the research advisory group, and the participating schools, canteen managers, and canteen users. This research was funded by the National Heart Foundation of Australia (102809). RW is supported by a Heart Foundation Postdoctoral Fellowship (102156) and Cancer Institute NSW Early Career Fellowship (2021/ECF1355). LW receives salary support from a National Health and Medical Research Council Investigator Grant Fellowship (APP1197022). RS is supported by a Medical Research Future Fund Investigator Grant (APP1194768). SLY is supported by a National Heart Foundation Future Leader Fellowship (106654). The funders had no role in the conduct of the trial or the analysis or interpretation of findings. The provider (Flexischools) was selected through a competitive tender process. Flexischools is a commercial organization that provided the online canteen ordering infrastructure to schools that were included in this study. Flexischools had no role in this study’s design, data analysis, data interpretation, or writing of this paper.

Data Availability

The data sets generated during or analyzed for this study are available from the corresponding author on reasonable request, pending ethics approval.

Authors' Contributions

RW conceived this study. TD and RW developed the methodology. CL conducted the formal analysis. TD, TC-M, RW, and HL conducted research. CL, TC-M, and TD curated data. TD and JJ led the writing of this paper with all authors contributing to paper revisions. LW, SLY, RS, and RW provided supervision. RW acquired funding. All authors read and approved the final paper.

Conflicts of Interest

None declared.

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Abbreviations

Edited by A Mavragani; submitted 21.07.23; peer-reviewed by S Beresford; comments to author 25.09.23; revised version received 01.10.23; accepted 30.01.24; published 19.03.24.

©Tessa Delaney, Jacklyn Jackson, Christophe Lecathelinais, Tara Clinton-McHarg, Hannah Lamont, Sze Lin Yoong, Luke Wolfenden, Rachel Sutherland, Rebecca Wyse. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.03.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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Doing more, but learning less: the risks of ai in research.

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Artificial intelligence (AI) is widely heralded for its potential to enhance productivity in scientific research. But with that promise come risks that could narrow scientists’ ability to better understand the world, according to a new paper co-authored by a Yale anthropologist.

Some future AI approaches, the authors argue, could constrict the questions researchers ask, the experiments they perform, and the perspectives that come to bear on scientific data and theories.

All told, these factors could leave people vulnerable to “illusions of understanding” in which they believe they comprehend the world better than they do.

The paper published March 7 in Nature .

“ There is a risk that scientists will use AI to produce more while understanding less,” said co-author Lisa Messeri, an anthropologist in Yale’s Faculty of Arts and Sciences. “We’re not arguing that scientists shouldn’t use AI tools, but we’re advocating for a conversation about how scientists will use them and suggesting that we shouldn’t automatically assume that all uses of the technology, or the ubiquitous use of it, will benefit science.”

The paper, co-authored by Princeton cognitive scientist M. J. Crockett, sets a framework for discussing the risks involved in using AI tools throughout the scientific research process, from study design through peer review.

“ We hope this paper offers a vocabulary for talking about AI’s potential epistemic risks,” Messeri said.

Added Crockett: “To understand these risks, scientists can benefit from work in the humanities and qualitative social sciences.”

Messeri and Crockett classified proposed visions of AI spanning the scientific process that are currently creating buzz among researchers into four archetypes:

  • In study design, they argue, “AI as Oracle” tools are imagined as being able to objectively and efficiently search, evaluate, and summarize massive scientific literatures, helping researchers to formulate questions in their project’s design stage.
  • In data collection, “AI as Surrogate” applications, it is hoped, allow scientists to generate accurate stand-in data points, including as a replacement for human study participants, when data is otherwise too difficult or expensive to obtain.
  • In data analysis, “AI as Quant” tools seek to surpass the human intellect’s ability to analyze vast and complex datasets.
  • And “AI as Arbiter” applications aim to objectively evaluate scientific studies for merit and replicability, thereby replacing humans in the peer-review process.   

The authors warn against treating AI applications from these four archetypes as trusted partners, rather than simply tools , in the production of scientific knowledge. Doing so, they say, could make scientists susceptible to illusions of understanding, which can crimp their perspectives and convince them that they know more than they do.

The efficiencies and insights that AI tools promise can weaken the production of scientific knowledge by creating “monocultures of knowing,” in which researchers prioritize the questions and methods best suited to AI over other modes of inquiry, Messeri and Crockett state. A scholarly environment of that kind leaves researchers vulnerable to what they call “illusions of exploratory breadth,” where scientists wrongly believe that they are exploring all testable hypotheses, when they are only examining the narrower range of questions that can be tested through AI.

For example, “Surrogate” AI tools that seem to accurately mimic human survey responses could make experiments that require measurements of physical behavior or face-to-face interactions increasingly unpopular because they are slower and more expensive to conduct, Crockett said.

The authors also describe the possibility that AI tools become viewed as more objective and reliable than human scientists, creating a “monoculture of knowers” in which AI systems are treated as a singular, authoritative, and objective knower in place of a diverse scientific community of scientists with varied backgrounds, training, and expertise. A monoculture, they say, invites “illusions of objectivity” where scientists falsely believe that AI tools have no perspective or represent all perspectives when, in truth, they represent the standpoints of the computer scientists who developed and trained them.

“ There is a belief around science that the objective observer is the ideal creator of knowledge about the world,” Messeri said. “But this is a myth. There has never been an objective ‘knower,’ there can never be one, and continuing to pursue this myth only weakens science.”  

There is substantial evidence that human diversity makes science more robust and creative, the authors add.

“ Acknowledging that science is a social practice that benefits from including diverse standpoints will help us realize its full potential,” Crockett said. “Replacing diverse standpoints with AI tools will set back the clock on the progress we’ve made toward including more perspectives in scientific work.”

It is important to remember AI’s social implications, which extend far beyond the laboratories where it is being used in research, Messeri said.

“ We train scientists to think about technical aspects of new technology,” she said. “We don’t train them nearly as well to consider the social aspects, which is vital to future work in this domain.”

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First refuelling for Russia’s Akademik Lomonosov floating NPP

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The FNPP includes two KLT-40S reactor units. In such reactors, nuclear fuel is not replaced in the same way as in standard NPPs – partial replacement of fuel once every 12-18 months. Instead, once every few years the entire reactor core is replaced with and a full load of fresh fuel.

The KLT-40S reactor cores have a number of advantages compared with standard NPPs. For the first time, a cassette core was used, which made it possible to increase the fuel cycle to 3-3.5 years before refuelling, and also reduce by one and a half times the fuel component in the cost of the electricity produced. The operating experience of the FNPP provided the basis for the design of the new series of nuclear icebreaker reactors (series 22220). Currently, three such icebreakers have been launched.

The Akademik Lomonosov was connected to the power grid in December 2019, and put into commercial operation in May 2020.

Electricity generation from the FNPP at the end of 2023 amounted to 194 GWh. The population of Pevek is just over 4,000 people. However, the plant can potentially provide electricity to a city with a population of up to 100,000. The FNPP solved two problems. Firstly, it replaced the retiring capacities of the Bilibino Nuclear Power Plant, which has been operating since 1974, as well as the Chaunskaya Thermal Power Plant, which is more than 70 years old. It also supplies power to the main mining enterprises located in western Chukotka. In September, a 490 km 110 kilovolt power transmission line was put into operation connecting Pevek and Bilibino.

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Nvidia’s Jensen Huang: The incredible future of AI

nursery school research paper

Jensen Huang, the CEO of tech titan Nvidia, has a message for the world about artificial intelligence: You ain’t seen nothing yet.

Speaking to a standing room-only audience at the 2024 SIEPR Economic Summit, Huang predicted that in as little as five years AI will be able to pass every test a human takes — not just the legal bar exams that it can complete today, but also highly specialized medical licensing exams.

In about 10 years, he said, the computational capabilities of AI systems will be a million times bigger than they are today. Systems synthetically generating data will have greater capacity to continuously learn, infer, and imagine. Instead of only instantly answering questions, forthcoming AI systems will also have the ability to think critically through problems over longer periods of time.

“In the future, the way you interact with AI will be very different” from what can be done with ChatGPT and other AI models today, said Huang in a keynote question-and-answer session led by John Shoven , a SIEPR senior fellow, emeritus; and the Charles R. Schwab Professor of Economics, emeritus, in Stanford’s School of Humanities and Sciences.

But does this mean AI technology will be able to mimic the human mind? Huang said he wasn’t sure. There needs to be a consensus about what it means to say AI has achieved human intelligence.

In order to have true artificial general intelligence, he said, “you need to know what the definition of success is.”

The gift of pain and suffering

nursery school research paper

Having co-founded Nvidia more than 30 years ago, Huang now finds himself at the center of the tech universe. His company, whose market value hit $2 trillion last month (after reaching $1 trillion the previous June), has rocketed thanks to its sophisticated and hugely expensive semiconductor chips and its estimated market share of more than 80 percent in AI chips.

“We sell the world’s first quarter-million-dollar chip,” Huang noted, referring to Nvidia’s powerful graphical processing unit system that weighs 70 pounds, consists of 35,000 parts and has the computing capacity of a data center.

During his Summit appearance, Huang regaled attendees with his insights and now-familiar deadpan humor. Asked about his signature outfit of black leather jacket, black shirt, and black pants, Huang said they are among the few pieces of clothing that don’t make him itch.

When asked his advice for Stanford students aspiring to be successful entrepreneurs, Huang talked about the importance of low expectations and high resilience. Greatness, he said, comes from smart people who have suffered from setbacks. This is why, at Nvidia, he talks openly about pain and suffering “with great glee.”

“For all of you Stanford students,” he said, “I wish upon you ample doses of pain and suffering.”

Watch the full discussion.

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Downie and Underwood present keynotes at digital humanities symposium in Japan

Professor and Associate Dean for Research J. Stephen Downie and Professor Ted Underwood will present their research at the Digital Humanities International Symposium on March 13 and 15 in Japan.

On March 13, Downie and Underwood will be the keynote speakers at the symposium, " Connecting Humanities ," at Kyushu University in Fukuoka. The symposium will feature discussions on the construction and analysis of large-scale text data, the latest trends in humanities informatics, and the newly established Graduate School of Humanities and Information Sciences at Kyushu University.

  • Downie, who serves as co-director of the HathiTrust Research Center (HTRC), will present "Open Access Data for Open Community Development: TORCHLITE Project." This talk will share the Tools for Open Research and Computation with HathiTrust: Leveraging Intelligent Text Extraction (TORCHLITE) project, which creates text analysis tools, dashboards, and application programming interfaces to open the unique and valuable data of HathiTrust Digital Library.
  • Underwood will present "How Will Generative AI Change the Digital Humanities?" In this talk, he will show examples of projects, such as annotating large corpora and asking new questions about detective novels, and discuss the potential impact of generative AI in the humanities.

On March 15, Downie and Underwood will present keynotes at the symposium, " Literary Studies and Research Foundations in the Big Data Era ," at Hitotsubashi University in Tokyo. The focus of the symposium will be distant reading—applying computational methods to large amounts of literary data—and how the HTRC provides the research data infrastructure to support digital humanities researchers.

  • In his keynote, "Researcher-curated Worksets for Analysis, Reuse, and Dissemination (SCWAReD) Project," Downie will introduce the work of SCWAReD researchers who work with diverse and previously underutilized texts.
  • Underwood will present "Understanding Literary Change in the Era of Machine Learning," in which he will show how machine learning can be used not only to highlight aspects of novels, such as the gender roles of characters, but also to extend it to changes in literature.

Downie serves as principal investigator on the HathiTrust + Bookworm text analysis project, joint principal investigator for TORCHLITE, and co-principal investigator for SCWAReD. In addition to his contributions to digital libraries and digital humanities research, Downie is known for helping to establish a vibrant music information retrieval research community. He is founder and first president of the International Society for Music Information Retrieval (ISMIR). Downie holds a bachelor's degree in music theory and composition, along with master's and doctoral degrees in library and information science, all from the University of Western Ontario.

Underwood's research explores the patterns of literature that emerge over long periods of time when examining hundreds or thousands of books at once. He has authored three books about literary history, Distant Horizons (The University of Chicago Press Books, 2019), Why Literary Periods Mattered: Historical Contrast and the Prestige of English Studies (Stanford University Press, 2013), and The Work of the Sun: Literature, Science and Political Economy 1760-1860 (New York: Palgrave, 2005). Underwood earned his PhD in English from Cornell University.

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    Introduction. The transition to primary school is a critical period in the lives of children and their families. During this time, children experience a novel and qualitatively different environment with increased expectations (Pianta and Kraft-Sayre Citation 2003; Cowan et al. Citation 2005; Ramey and Ramely Citation 2010) that place increased demands on children's behaviours, cognitions ...

  8. The Persistence of Preschool Effects From Early Childhood Through

    Using data from the Early Childhood Longitudinal Study Kindergarten Cohort of 1998 (n = 15,070), this study used propensity scores to examine the short- and long-term academic and psychosocial benefits of preschool education for a diverse sample of middle-class children.Compared with children who attended informal care at age 4, preschool attendees consistently performed better on achievement ...

  9. Nursery Education: The Need for Research

    the government for research that would inform policy makers vis-a-vis the expansion of nursery education provision. Because of this, the present paper will consider some of the prin-ciples that could guide future research in this field, and against the background of existing knowledge will suggest the direction such research could take.

  10. Child Development Research

    This project was initiated at the WVU Nursery School. Young children engaged in a personal history project. Even with obvious developmental limitations to understanding past events, young children investigated occurrences of the past related to their families. Read More... One of our students' history projects incorporated swing dancing lessons!

  11. Early Childhood Education and Care in the United States ...

    Early childhood education and care (ECEC) in the US includes a wide range of part-day, full-school-day, and full-work-day programs, under educational, social welfare, and commercial auspices, funded and delivered in a variety of ways in both the public and the private sectors, designed sometimes with an emphasis on the "care" component of ECEC and at other times with stress on "education ...

  12. Parental perception of nursery school education

    PARENTAL PERCEPTION OF NURSERY SCHOOL EDUCATION . A Research Paper Presented to Dr. Lawrence L. Kavich Department of Educational Psychology and Foundations University of Northern Iowa In Partial Fulfillment of the Requirements for the Degree of Master of Arts in Education by . OMtlR BOZKURT . December 1982

  13. Research on early childhood mathematics teaching and learning

    This paper reports an overview of contemporary research on early childhood mathematics teaching and learning presented at recent mathematics education research conferences and papers included in the special issue (2020-4) of ZDM Mathematics Education. The research covers the broad spectrum of educational research focusing on different content and methods in teaching and learning mathematics ...

  14. Multiple perspectives on attachment theory: Investigating educators

    This paper presents findings from a study investigating the multiple perspectives of attachment theory and practice through the voices of early childhood educators. Attachment theory has influenced research, policy and practice over the last six decades, offering a framework for understanding risk and protective factors in early childhood.

  15. Nursery Rhymes: Its Effectiveness in Teaching of English among Pre

    Nursery rhymes are traditional songs or poetry written in simple sentences by unidentified poets that serve young children to listen, enjoy, and even sing the songs (De Mello et al., 2022 ...

  16. Early childhood care and education in the Russian Federation

    Background paper prepared for th Education for All Global Monitoring Rep Strong foundations: early childhood care Early childhood care and edu Russian Federation Maria S. Taratukhina, Marina N. Poly Tatyana A. Berezina, Nina A. Notk Roza M. Sheraizina, Mihail I. Borov 2006 This paper was commissioned by the Education for All Global M information to assist in drafting the 2007 report.

  17. Nursery and Non-Nursery Children's Development Research Paper

    The children going to nursery school showed improved social, communicative, and cognitive development compared to the non-nursery children. ... This research paper, "Nursery and Non-Nursery Children's Development" is published exclusively on IvyPanda's free essay examples database. You can use it for research and reference purposes to write ...

  18. 4281 PDFs

    Schools for children usually under five years of age. | Explore the latest full-text research PDFs, articles, conference papers, preprints and more on NURSERY SCHOOLS. Find methods information ...

  19. Nursery School Research Paper

    Nursery School Research Paper. 529 Words3 Pages. Blossom Hill Nursery School, an Experience in Infant Education The school of my choice is Liberty University in Lynchburg, Virginia considering that they teach with a Christian worldview. While I already contribute to my community and my church, having a teaching degree from Liberty University ...

  20. Enabling collaborative lesson research

    This paper will address this tension by interrogating a model of professional learning that integrates collaborative lesson research in a university and school design research project (Bakker, 2018). As teachers and teacher educators engaged in design research, we acknowledge and often live the difficulties implicit to university and school ...

  21. UNICEF

    Moved Permanently. The document has moved here.

  22. Journal of Medical Internet Research

    This paper is in the following e-collection/theme issue: Web-based and Mobile Health Interventions (2877) Information Seeking, Information Needs (408) Behavioural Surveillance for Public Health (175) Obesity and Nutrition as Public Health Problem (238) Innovations and Technology for Healthy Eating Education (384) Instruments and Questionnaires for Nutrition and Food Intake (157)

  23. Doing more, but learning less: The risks of AI in research

    The paper, co-authored by Princeton cognitive scientist M. J. Crockett, sets a framework for discussing the risks involved in using AI tools throughout the scientific research process, from study design through peer review. " We hope this paper offers a vocabulary for talking about AI's potential epistemic risks," Messeri said.

  24. (PDF) Practical Manual of Nursery Management

    A research trial comprising of twelve Eucalyptus clones initially screened for gall resistance was established at a spacing of 1m X 1m. at the Department of Forestry nursery, ASPEE College of ...

  25. First refuelling for Russia's Akademik Lomonosov floating NPP

    Rosatom's fuel company TVEL has supplied nuclear fuel for reactor 1 of the world's only floating NPP (FNPP), the Akademik Lomonosov, moored at the city of Pevek, in Russia's Chukotka Autonomous Okrug. The supply of fuel was transported along the Northern Sea Route. The first ever refuelling of the FNPP is planned to begin before the end of ...

  26. BETA GIDA, OOO

    Find company research, competitor information, contact details & financial data for BETA GIDA, OOO of Elektrostal, Moscow region. Get the latest business insights from Dun & Bradstreet.

  27. Nvidia's Jensen Huang: The incredible future of AI

    Jensen Huang, the CEO of tech titan Nvidia, has a message for the world about artificial intelligence: You ain't seen nothing yet. Speaking to a standing room-only audience at the 2024 SIEPR Economic Summit, Huang predicted that in as little as five years AI will be able to pass every test a human takes — not just the legal bar exams that it can complete today, but also highly specialized ...

  28. Downie and Underwood present keynotes at digital humanities symposium

    A paper by Professor Emerita Linda C. Smith, "Reviews and Reviewing: Approaches to Research Synthesis," is one of seven papers included in the relaunch of the Annual Review of Information Science and Technology (ARIST), a collection of peer-reviewed, comprehensive, and systematic reviews on topics relevant to information science.

  29. ELLOGISTIK, OOO Company Profile

    Find company research, competitor information, contact details & financial data for !company_name! of !company_city_state!. Get the latest business insights from Dun & Bradstreet.