reading difficulties research paper

Psychology: Research and Review

• Open access
• Published: 20 March 2021

Identification of struggling readers or at risk of reading difficulties with one-minute fluency measures

• Maíra Anelli Martins   ORCID: orcid.org/0000-0001-6946-6755 1 , 2 , 3 &
• Simone Aparecida Capellini 2 , 3 , 4  

Psicologia: Reflexão e Crítica volume  34 , Article number:  10 ( 2021 ) Cite this article

18k Accesses

5 Citations

2 Altmetric

Metrics details

To identify readers who are struggling or at risk of reading difficulties, reference standards in oral reading fluency (ORF) are used to conduct an assessment that is based on a widely reported method known as curriculum-based measurement (CBM), which itself is based on 1-min fluency measures. The purpose of this study was to evaluate students’ ORF (with a 1-min fluency measure) to characterize their fluency and to determine references of appropriate development in reading at the 50th percentile.

For this study, a database of readings made available by the Learning Studies Research Laboratory was used. This database consisted of 365 readings by elementary-school students from the third to fifth grades in two cities in the interior of the state of São Paulo from two different public school systems that use the same teaching methodology. The data consisted of digital audio recordings of the passage “The Umbrella” (text suitable for schooling levels) of the Protocol for Assessment of Reading Comprehension procedure. For this procedure, three steps were performed: step 1—listening to the 365 readings and assessing the scores for the number of words read correctly per minute; step 2—the calculation of the mean and percentiles for each grade; and step 3—the adaptation of the reference table to indicate students eligible to receive reading fluency intervention.

Third-year students who correctly read 86 or more words per minute, fourth-year students who correctly read 104 or more words per minute, and fifth-year students who correctly read 117 or more words per minute were considered students who had made adequate progress in reading.

It was possible to classify students based on the 1-min fluency measures, with reference intervals of words read correctly per minute per school year (for the third, fourth, and fifth years) for those who were making adequate progress in reading and reference intervals for those who were considered readers who were struggling or at risk of reading difficulties.

Little research has been conducted in Brazil on measures to assess reading fluency (Gentilini et al, 2020 ; Andrade, Celeste, & Alves, 2019 ; Moutinho, 2016 ; Pacheco & Santos, 2017 ; Peres & Mousinho, 2017 ), and a search for research on reading fluency in official documents of the Brazilian Ministry of Education (Martins, 2018 ) also reveals that such measures are not a type of assessment that is widely known or applied by teachers within the classroom. Nonetheless, research has continually indicated the importance of developing oral reading fluency (ORF; reading with appropriate rate, accuracy, and prosody) as a vital and necessary skill for the overall development of proficient reading (Machado, Santos, & Cruz, 2019 ; Rasinski & Young, 2017 ).

In addition to the lack of Brazilian research widely exploring this theme, the low performance data of Brazilian students in reading indicates that these students also face difficulties in learning this highly complex activity, including the many who do not become proficient, effective readers. It is noted that this is a recurring problem that affects students and, consequently, concerns educators. As is clear from the evaluations conducted throughout the national territory (large-scale evaluations), the problem has continued throughout the years and affects even the regions with the best educational indexes or socioeconomic status.

Measures assessment of reading oral fluency

The method widely publicized as curriculum-based measurement (CBM) is a curriculum-based progress-monitoring method for measuring growth in specific areas of basic knowledge and skills and assessing the effects of instructional programs (response to intervention). Curriculum-based assessment, as a longstanding assessment practice asserting that learning assessments should be based on what has been taught, has become popular in the field of special education. Thus, the CBM method is described as curriculum-based, as it is used within the context of the school curriculum (Deno, 1985 ).

The CBM method proposes simple measures for the assessment of academic competence that can be applied quickly by teachers. These measures help provide an overview of each student’s academic development; furthermore, when these simple measures are applied systematically over time, they can be used to track a student’s potential difficulties (Fuchs, 2017 ).

For example, to identify struggling readers, reference standards for ORF are used, which, based on the CBM assessment method initially proposed by Deno ( 1985 ), enable reading analysis in just 1 min (e.g., the number of words read correctly per minute–WCPM). The most widely used assessment of ORF, which focuses on two of the three components of fluency (rate and accuracy), simply requires the student to read a grade-appropriate passage, which they have not seen previously, for 1 min. At the end of 1 min, errors are subtracted from the total words read, and then the WCPM score is calculated (Hasbrouck & Tindal, 2006 ).

Thus, the method was developed to create procedures for measuring progressive development in a simple, reliable, and valid way. These procedures enable teachers to frequently and repeatedly measure students’ progress in basic reading, spelling, writing, and expression skills (Rasinski, 2004 ).

Regarding reading fluency assessment, it is recommended that the scoring of the number of words read correctly per minute (WCPM) and the number of words read incorrectly per minute (WIPM) be performed with three passages of the same difficulty level to then calculate the mean score. Thus, the WCPM measure can serve to screen for academically at-risk students, assign placement in remedial and special education programs, monitor student progress, improve teaching programs, and predict performance in high-risk assessments (Hasbrouck & Tindal, 2006 ; Rasinski, 2004 ).

A series of discussions began in the last decade in Brazil on the question of the “wait to fail to act” model, which highlighted the importance of the early identification of learning difficulties. There are also discussions about the broadening of knowledge about the advantages of early identification and scientific evidence-based assessment and screening methods (Almeida, Piza, Toledo, Cardoso, & Miranda, 2016 ; Batista & Pestun, 2019 ; Brito, Seabra, & Macedo, 2018 ; Justi & Cunha, 2016 ; Mayeda, Navatta, & Miotto, 2018 ; Nicolau & Navas, 2015 ; Palles da Silva & Guaresi, 2019 ; Rodrigues & Ciasca, 2016 ; Silva & Capellini, 2017 ; Silva & Capellini, 2019a ; Silva & Crenitte, 2016 ).

According to Elliott, Huai and Roach ( 2007 ), several factors contribute to the prevalence of the “wait to fail to act” model, such as the fact that educators understand that there is a certain heterogeneity of development and learning among students and seek to allow appropriate time for this development. By doing so, they are also allowing students a fair chance of progressing without early determination of the problem. Another factor for the prevalence of this action model is the fact that few large-scale screening instruments are time efficient and technically simple for teachers to apply.

In the Brazilian literature, early screening instruments are recent and focus primarily on metalinguistic skills, such as the “Early Identification and Reading Problems Protocol” (Capellini, César, & Germano, 2017 ), the “Evaluation of Cognitive-Language Skills Protocol: Professional and Teacher’s Book” (Capellini, Smythe, Silva, 2017 ) and the “Protocol for Cognitive-Language Skills Assessment of Students in Early Literacy” (Silva & Capellini, 2019b ). These instruments assess skills considered predictive of literacy, such as reading and writing skills; arithmetic; auditory and visual processing; metalinguistic skills; and processing speed with the rapid automatic naming test. Some tests evaluate mathematical logical reasoning, for example, the “Cognitive-Language Skills Assessment Protocol.”

Likewise, there has been a movement in Brazilian research in recent years to describe the importance of reading fluency measures, especially those related to using a chronometer for timing as measures for screening difficulties, in addition to the development of instruments to assist in this assessment. Alves et al. ( 2019 ) described such issues in the most recent publication of the LEPIC® software, which proposes a semiautomatic and instantaneous reading fluency analysis to assess and assist in diagnostics or to monitor reading skills. This analysis focuses on the importance of evaluating parameter fluency, which may include indicators of reading problems such as dyslexia. Another instrument recently developed by Brazilian researchers is a collection of passages in sequential order according to difficulty level and suitable for elementary-school students from the first through fourth grades, called the “Reading Fluency Performance Assessment” (Martins & Capellini, 2018 ).

Additionally, on 22 February 2018, the More Literacy Program (PMAlfa) was created via MEC Ordinance No. 142, a strategy by the Ministry of Education that aims to strengthen and support school units in the process of increasing the literacy of elementary-school students enrolled in the first and second grades; the program fulfills the criteria established in the Common National Curriculum Base (CNCB). The objective of the program is to perform reading, writing, and math evaluations. For the first time, a formal program of the Brazilian government will evaluate the fluency and accuracy in the reading ability of students in the second grade of elementary school. The assessment is performed individually and uses a proprietary application suitable for smartphones or tablets.

However, despite efforts to create adequate assessment procedures for ORF, research into the characterization of ORF in this population is still incipient. Pacheco and Santos ( 2017 ), for example, evaluated three groups of readers in relation to reading fluency who were classified into three groups: group I–second-grade readers with little reading experience and expectation of low reading fluency; group II–second-year high school readers with the expectation of having slightly more reading experience and moderate fluency; and group III–readers with a higher education level. However, the relatively small sample consisted of 12 participants (four participants in each group), and the reading rate was evaluated by using the number of words read compared to the total reading time measured in seconds, considering a total reading time of 180 s (3 min).

In another study (Moutinho, 2016 ), 46 sixth-grade students from public and private schools were evaluated by measuring the WCPM in 1 min from three different passages. However, the article focused on describing the accuracy errors, i.e., the number and type of WIPM, while data for the WCPM are not presented. Other researchers evaluated 55 students from the third to the seventh grades with the number of words per minute, reading four different types of passages, and analyzing student performance in each (Dellisa & Navas, 2013 ).

Some researchers have also conducted reading fluency assessment with elementary students, as in a study that evaluated 32 students in ninth grade and calculated the speed of words read per minute (using the formula of total number of words from the passage, divided by the time in seconds spent to complete the reading, and multiplied by 60) (Komeno, Ávila, Cintra, & Schoen, 2015 ). Furthermore, in another recent study, researchers characterized the ORF by 232 middle-grade students from the sixth to the ninth grades from public and private education. The study provided an estimate of the expected values for each grade surveyed by reading an easy passage based on the 1-min oral fluency assessment, with scores for words read per minute and WCPM (Andrade et al., 2019 ).

While only a small number of studies for elementary and middle students exist, even fewer studies evaluate reading fluency in high school students or adults. One research study evaluated 88 students in the second grade of high school. The CBM method was followed by selecting a passage compatible with students’ age and grade and comprising subjects corresponding to the basic curriculum studied in the classroom. Students read three different passages, lasting 1 min each, for the subsequent calculation of the number of WCPM (Oliveira, Amaral, & Picanço, 2013 ). Only one study evaluating reading fluency in adults was found, in which the sample consisted of 30 adolescents and adults who were evaluated by measuring the number of words per minute (Peres & Mousinho, 2017 ).

The assessment of ORF conducted through WCPM scores presents 30 years of validation research indicating that this is a valid and reliable measure that reflects a student's overall performance in reading development during the first years after literacy (Morris et al., 2017a , b ; Tindal, 2017 ; Valencia et al., 2010 ). Reading fluency benchmarks have been used both for screening and for monitoring reading development, and research in these fields seeks to answer questions such as “How is student performance compared to their peers?” and “Who are the students struggling with reading?” This practice of frequent assessment enables early intervention and the planning of activities that focus on the skills already acquired and those that still require further attention.

Benchmarks in ORF have been established by American researchers and collected from a range of students, from those identified as talented or otherwise exceptionally skilled to those diagnosed with reading disabilities, such as dyslexia. The largest sample of the ORF benchmark was collected from schools and districts in 23 states in the USA for over 4 years. Based on their vast experience in interpreting ORF data, it was established that a score of 10 words above or below the 50th percentile should be interpreted as an expected score, meaning that students are making satisfactory reading progress (Hasbrouck & Tindal, 2006 ).

Given the implications that ORF benchmarks would have for Brazilian education, a study to determine a fluency reference through appropriate assessment material would be of great relevance. This benchmarking considers the indication of a median score (50th percentile), with scores of 10 words above or below this median indicating students who have made appropriate reading progress, to assist in assessment and to create parameters for selecting students for interventional programs who are struggling readers or at risk for developing difficulties in reading proficiency later.

The purpose of this study was to evaluate the ORF of students from the third to the fifth grades (with a 1-min fluency measure) to characterize their fluency and determine references of appropriate development in reading at the 50th percentile and those below this reference.

This is a quantitative, descriptive-explanatory study. The dependent variable is a 1-min fluency measure. The independent variable is student grade.

General procedures and database

This study was approved by the Ethics Committee of the Faculdade de Filosofia e Ciências of Sao Paulo State University–UNESP-Campus de Marília-SP under protocol 2.550.190–CAAE 50201915.9.0000.5406.

For this study, a database of readings made available by the Investigation Learning Disabilities Laboratory (in Portuguese: Laboratório de Investigação dos Desvios da Aprendizagem–LIDA), registered by a research group of the National Counsel of Technological and Scientific Development (CNPq), called “Language, Learning, Education,” was used. All information related to the sample of students comprising our database was made available by the members of this group.

The readings database made available consists of 365 readings from elementary-school students from the third to the fifth grades in two cities in the interior of the state of São Paulo (in a medium- and a small-sized Brazilian city, Southeast Region of Brazil) from two different public school systems with the same teaching methodology. In the city of Marília-SP, there are 51 schools with regular elementary education in urban locations, in basic education, with 2221 students enrolled in the third year, 2119 students enrolled in the fourth year and 2033 students enrolled in the fifth year according to the School Census/(Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira – INEP, 2018 ).

In the city of Garça-SP, there are 14 schools with regular elementary education in urban locations, in basic education, with 478 students enrolled in the third year, 436 students enrolled in the fourth year and 401 students enrolled in the fifth year according to the School Census/(Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira – INEP, 2018 ). The schools were selected through convenience sampling (simple convenience sample). The students participating in the studies did not have a history of repeating grades; they were monolinguals and native speakers of Brazilian Portuguese. The data were digital recordings of participants reading the passage “The Umbrella” (text suitable for schooling levels) from the procedure “Protocol for Assessment of Reading Comprehension” (Cunha & Capellini, 2014 ).

Of the 365 readings, 98 were third-grade students (48.9% female), 130 were fourth-grade students (49.2% female), and 137 were fifth-grade students (51.8% female) (participants were elementary-school students ranging from 7 to 11 years old).

According to the latest results published (Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira, 2015-2017 ) by the Socioeconomic Level Indicator (Inse) of basic education schools in Brazil, developed by the National Institute of Educational Studies and Research Anísio Teixeira (Inep), in the Basic Education Assessment Directorate (Daeb), the schools from which the analyzed data were obtained have an average Inse (absolute value 58.46 and 57.47), with an average rating (group 5).

The inclusion and exclusion criteria used by the laboratory researchers in the data collection of the reading audio bank are described. The inclusion criteria for the sample selection were as follows: informed consent form signed by the parents or guardians for the students; students with no history of neurological or psychiatric illnesses, uncorrected auditory and visual impairments, and cognitive performance within normal, according to the description at the school records and teachers’ reports. The exclusion criteria for the sample selection were the presence of genetic or neurological syndromes in the students, students who did not present a satisfactory reading domain level for the observation of the variable proposed in the study, and students who presented recording errors in their respective audio files.

Specific instruments and procedures

The passage used was “The Umbrella” (history appropriate for the educational level) from the procedure “Reading Comprehension Assessment Protocol” (Cunha & Capellini, 2014 ). The choice for using this protocol occurred due to its careful assessment and development, since its issues were built from the rules for the psychometric tool development described by The Federal Council of Psychology. The Council is an official body that studies and establishes criteria and rules in Brazil for the construction of evaluation tools that ensures their accuracy and validity, and defines, as reliable procedures, those whose accuracy is understood as their level of consistency and their ability to reach the objectives for which they were built as their validity.

The protocol consists of four passages, two narratives, and two expository narratives. A medium-length (297 words) narrative passage was chosen. The choice of a passage with a narrative gender protocol occurred because the students had been more commonly exposed to such passages since childhood and throughout the education process, which would simplify the fluency evaluation and avoid the interference of any cultural issues of the passage in the reading results of the students of different schooling levels.

The choice of protocol also occurred because it presents passages that were selected to reach students from the third, fourth and fifth grades at representatively similar levels of difficulty for all school years, making it possible to apply a single passage in all school years.

Although the procedure is an instrument for assessing reading comprehension, due to the objectives of this study, only the reading recordings were used to assess fluency, while the multiple-choice questions were not applied.

The equipment used in the recordings was a Karsect microphone headset, which was unidirectional since the microphone picks up sounds with greater intensity and orients towards where it is directed, reducing the intensity of the external noise. The microphone was connected to an HP notebook with an Intel Pentium processor, 3 GB memory, and a 32-bit operating system. Recordings were made with an original HP software application and were saved as .wav files.

The collections were carried out by the researchers of the mentioned research group, following the guidelines for individual application. Each reading of the entire passage was recorded, taking an average of 5 min total for each individual recording session in spaces reserved for the researchers in the schools during class hours.

To analyze the readings on digital media, the following steps were planned and performed:

Step 1 : The rate was scored by listening to 365 digital recordings and assessing the WCPM scores, which was performed according to the reading error classification used by Begeny, Capellini, and Martins ( 2018 ) and by other researchers (Valencia et al., 2010 ). In this approach, the types of errors that are marked as WIPM are mispronounced words, words substituted with others, words omitted, words read out of order, addition or omission of word endings, and hesitation (words on which the student paused more than 3 s, after which he or she is told the word, and it is marked as incorrect. If necessary, the student is told to continue with the next word).

The following items indicate all situations that are marked as WCPM: words pronounced correctly, self-corrections, words decoded slowly but ultimately read correctly, repeated words, words mispronounced due to dialect or regional differences, and words inserted. To quantify errors, scoring rules are also proposed for certain situations: lines or multiple words omitted; when one or more lines are not read (four or more omitted words in sequence), they are not considered errors, although those words are excluded from the WCPM (such that this rule is applied whenever a student skips four or more words within a sentence). If the student skips one, two, or three consecutive words, each word should be counted as an error (WIPM). Regarding hyphenated words that can exist independently, each morpheme separated by a hyphen counts as an individual word if the two parts exist independently when the hyphen is removed, such as “Guarda-chuva ” [Umbrella in Portuguese] (counts as two words but is only marked incorrect when the student misreads), as opposed to the word “ anglo-China ” (considered as one word, regardless of which or both are misread).

Step 2 : The data thus obtained were tabulated and processed with Microsoft Excel® 2010. Data were analyzed through descriptive statistics (mean, standard deviation, and percentiles). Percentiles 5, 10, 25, 50, 75, 90, and 95 were calculated for each grade. Stratifying these percentiles helps to understand the different levels of difficulty that students may present.

Step 3 : The reference table was adjusted for the selection of students eligible to receive reading fluency interventions or programs. For this, the minimum reference threshold was the 25th percentile, and the maximum reference limit was the 50th percentile. The reference to the 25th percentile represents an approximate limit on the minimum level of ORF that a student should present to benefit from a fluency program. This reference was developed through years of research and related interventions (Begeny et al., 2018 ; Field, Begeny, & Kim, 2019 ).

Thus, it was determined that in the present research, WCPM intervals (maximum and minimum limits) would be established to select students who were not making adequate reading progress based on the ORF standard published by Hasbrouck and Tindal ( 2006 ).

The results regarding the reading fluency assessment measure as a procedure for selecting struggling readers or at risk of developing reading difficulties (grades 3 to 5) are summarized in Tables 1 and 2 .

From the data presented in Table 1 , students in the third year who read 86 or more WCPM, in the fourth year who read 104 or more WCPM, and in the fifth year who read 117 or more WCPM are considered students who are making adequate progress in reading. As shown in Table 1 , the lower the student scored beneath the 25th percentile, the more difficulties with reading the student will present, and the higher the student scored above the 50th percentile, the better the student’s performance.

Considering the standards proposed by Hasbrouck and Tindal ( 2006 , p. 639), in which students who read more than 10 WCPM above the 50th percentile present appropriate reading progress (unless there are other indicators for concern), the WCPM was established for Brazilian students (Table 2 ).

The reference intervals were calculated from the readings by the 365 students, considering that those who presented a WCPM score between the 25th and 50th percentiles did not make satisfactory progress in their reading fluency and taking the 25th percentile as the minimum reference limit and the 50th percentile as the maximum reference limit (Table 2 ). Students with WCPM scores at the 25th percentile or below are unlikely to benefit from a fluency-based intervention because they likely need assistance with decoding, phonics, and/or phonemic awareness.

Measures such as the number of WCPM offer numerous advantages for use in the context of ORF assessment. This measure has already been proven to be valid and is a quick and simple measure; it can be easily implemented in educators’ routines, either within the school routine or with professionals in their clinics. The reliability coefficient of this study could not be used if the test used because a single item test was used (number of words read correctly). If used as a screening measure for students at risk of reading difficulties, it should be performed by teachers from the third grade, since it is from this series that all students are expected to have passed the literacy phase and to move from the phase of learning to read to the phase of reading to learn. Consequently, within just a few hours, a teacher can evaluate their entire class because the assessment is performed quickly, which would also enable frequent assessments, which would, in turn, enable the monitoring of students’ progress in their fluency (Hasbrouck & Tindal, 2006 ; Rasinski, 2004 ; Rasinski & Young, 2017 ).

For reference values, the data obtained in this study served to identify students who were making adequate reading progress and those who could benefit from a fluency program. Among the academic skills considered central to reading success, fluency reveals not only its importance in assessing and screening key components but also in intervention response strategies and models for absorbing the demand encountered after the screening and early identification of reading difficulties (Kostewicz et al., 2016 ).

Considering the Brazilian studies on the characterization of ORF, we note that despite their small number (Andrade et al., 2019 ; Dellisa & Navas, 2013 ; Komeno et al., 2015 ; Moutinho, 2016 ; Oliveira et al., 2013 ; Pacheco & Santos, 2017 ; Peres & Mousinho, 2017 ), the results help to predict and compare student performance. It is necessary to advance the description of the results to create fluency references so that they can be used to screen for students with general reading difficulties, according to each region of the country. It is emphasized that due to the continental dimensions of the Brazilian national territory, there are considerable cultural and educational differences among regions.

Therefore, the method of assessing a measure of ORF in given passages can be used to assess student progress in reading fluency competence; to predict and compare students’ performance with peers or benchmarks (since their performance is compared over time) as well as conduct individual assessments; set annual goals; assess the effectiveness of intervention programs; develop standards for the class, school, and/or region; identify students at risk of dyslexia or in need of further intervention; and serve as the initial source of data collection in the response-to-intervention model (Mendonça & Martins, 2014 ).

Implications

There are public policy problems that involve this issue of early identification in Brazil, as there are no projects or actions directed at absorbing the demand of learning disabilities within the school itself. This difficulty makes the implementation of a screening process for early identification more difficult, since once these students with difficulties have been identified, there is a corresponding need for interventions, such as intervention response models together with the need for a complete structural and practical change within the classroom to modify the deeply rooted tradition of “waiting to fail to take action” (Elliott et al., 2007 ). However, as observed in a recent program created by the Ministry of Education (More Literacy Program–PMAlfa), new ways of implementing the screening of reading difficulties and continuing teacher education to ensure that they master the methodologies for progress monitoring and evaluation of student performance are beginning to appear.

It is also important to underscore that recent research has focused on the development of instruments and materials suitable for this type of evaluation and progress-monitoring, such as passages that are appropriate for the grade level and classified according to their difficulty, that not only allow the modification of the “waiting to fail to act” tradition but also allow suitable fluency assessment applications with materials that not only accelerate but also facilitate evaluation (such as software and applications) (Alves et al., 2019 ). This approach also means that three passages of the same level of difficulty can be offered (as a collection of sequential passages) to the students for assessment (Martins & Capellini, 2018 ), with sets of three passages to be applied throughout the school year to facilitate the monitoring of student progress.

Despite its limitations, this study extended the literature (Andrade et al., 2019 ; Dellisa & Navas, 2013 ; Komeno et al., 2015 ; Moutinho, 2016 ; Oliveira et al., 2013 ; Pacheco & Santos, 2017 ; Peres & Mousinho, 2017 ) as part of the research movement to obtain ORF subsidiary reference data for professionals in the health-education interface. However, it is necessary to note that one limitation of this study is the number of samples used. To complement this study and other Brazilian research in this context, new research is needed that increases the number and the representativeness of the sample of Brazilian readers who struggle.

From this study, it was possible to evaluate and characterize the reading fluency of Brazilian students. It was also possible to establish reference intervals for the assessment of ORF, which can be used to screen struggling readers or students at risk who present or may develop reading difficulties.

Therefore, similar research should be carried out and expanded to create measurement parameters related to ORF, which will help teachers make decisions about which paths need to be constructed or improved to assist those students who are presenting difficulty in this learning process.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Curriculum-based measurement

• Oral reading fluency

Words read correctly per minute

Words read incorrectly per minute

More Literacy Program

Common National Curriculum Base

Almeida, R. P., Piza, C. J., De Toledo, M. A., Cardoso, T. S. G., & Miranda, M. C. (2016). Prevenção e remediação das dificuldades de aprendizagem: Adaptação do modelo de resposta à intervenção em uma amostra brasileira. Revista Brasileira de Educação , 21 (66), 611–630. https://doi.org/10.1590/S1413-24782016216632 .

Article   Google Scholar  

Alves, L. M., Cunha, L. O., Santos, L. F., Melo, F. S. M. C., Reis, V. O. M., & Celeste, L. C. (2019). Análise tecnológica da fluência leitora: Validação do software Lepic® nos anos iniciais do Ensino Fundamental. Neurociências (Rio de Janeiro) , 15 , 33–41.

Google Scholar  

Andrade, A. J. L., Celeste, L. C., & Alves, L. M. (2019). Caracterização da fluência de leitura em escolares do Ensino Fundamental II. Audiology - Communication Research , 24 , e1983. Epub March 28. https://doi.org/10.1590/2317-6431-2018-1983 .

Batista, M., & Pestun, M. S. V. (2019). O Modelo RTI como estratégia de prevenção aos transtornos de aprendizagem. Psicologia Escolar e Educacional , 23 , e205929. Epub December 02, 2019. https://doi.org/10.1590/2175-35392019015929 .

Begeny, J. C., Capellini, S. A., & Martins, M. A. (2018). HELPS-PB: Programa de fluência de leitura para escolares: Manual do instrutor. (English translation: HELPS in Brazilian Portuguese: A Reading fluency program for children; Teacher’s Manual) . Helps Education Fund http://www.helpsprogram.org/ .

Brito, G. R., Seabra, A. G., & Macedo, E. C. (2018). Implementação do modelo de resposta à intervenção em uma classe de 5° ano do ensino fundamental da rede pública de ensino: relato de experiência. Revista Psicopedagogia , 35 (106), 82–93 Recuperado em 13 de junho de 2020, de http://pepsic.bvsalud.org/scielo.php?script=sci_arttext&pid=S0103-84862018000100010&lng=pt&tlng=pt .

Capellini, S. A., César, A. B. P. C., & Germano, G. D. (2017). Protocolo de identificação precoce e dos problemas de leitura - IPPL. Book Toy.

Capellini, S. A., Smythe, I., & Silva, C. (2017). Protocolo de avaliação de habilidades cognitivo-linguísticas: Livro do profissional e do professor. Book Toy.

Cunha, V. L. O., & Capellini, S. A. (2014). PROCOMLE: Protocolo de Avaliação da Compreensão de Leitura . Book Toy.

Dellisa, P. R. R., & Navas, A. L. G. P. (2013). Avaliação do desempenho de leitura em estudantes do 3° ao 7° anos, com diferentes tipos de texto. CoDAS , 25 (4), 342–350. https://doi.org/10.1590/S2317-17822013000400008 .

Article   PubMed   Google Scholar  

Deno, S. L. (1985). Curriculum-based measurement: The emerging alternative. Exceptional Children , 52 (3), 219–232. https://doi.org/10.1177/001440298505200303 .

Elliott, S. N., Huai, N., & Roach, A. T. (2007). Universal and early screening for educational difficulties: Current and future approaches. Journal of School Psychology , 45 (2), 137–161. https://doi.org/10.1016/j.jsp.2006.11.002 .

Field, S. A., Begeny, J. C., & Kim, E. K. (2019). Exploring the relationship between cognitive characteristics and responsiveness to a tier 3 reading fluency intervention. Reading & Writing Quarterly , 35 (4), 374–391. https://doi.org/10.1080/10573569.2018.1553082 .

Fuchs, L. S. (2017). Curriculum-Based Measurement as the emerging alternative: three decades later. Learning Disabilities Research & Practice , 32 (1), 5–7. https://doi.org/10.1111/ldrp.12127 .

Gentilini, L. K. S.,  Andrade, M. E. P.,  Basso, F. P., Salles, J. F., Martins-Reis,V. O., & Alves, L. M. (2020). Desenvolvimento de instrumento para avaliação coletiva da fluência e compreensão de leitura textual em escolares do ensino fundamental II. CoDAS, 32 (2), e20190015. Epub March 02, 2020. https://doi.org/10.1590/2317-1782/20192019015

Hasbrouck, J., & Tindal, G. A. (2006). Oral reading fluency norms: a valuable assessment tool for reading teachers. The Reading Teacher , 59 (7), 636–644 www.jstor.org/stable/20204400 .

Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira – INEP (2018). Censo Escolar. Recuperado de https://academia.qedu.org.br/censo-escolar/

Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira – INEP. Indicadores educacionais . 2015-2017. Recuperado de http://portal.inep.gov.br/indicadores-educacionais

Justi, C. N. G., & Cunha, N. (2016). Tarefas de nomeação seriada rápida: rastreando a dificuldade de leitura. Psicologia: Teoria e Pesquisa , 32 (4), e32425. Epub June 22, 2017. https://doi.org/10.1590/0102.3772e32425 .

Komeno, E. M., Ávila, C. R. B., Cintra, I. P., & Schoen, T. H. (2015). Velocidade de leitura e desempenho escolar na última série do ensino fundamental. Estudos de Psicologia (Campinas) , 32 (3), 437–447. https://doi.org/10.1590/0103-166X2015000300009 .

Kostewicz, D. E., Kubina, R., Selfridge, K. A., & Gallagher, D. L. (2016). A Review of Fixed Fluency Criteria in Repeated Reading Studies. Reading Improvement, 53 (1), 23–41.

Machado, A. P. G., Santos, I. M., & Cruz, D. S. (2019). Diagnóstico de leitura de estudantes: interfaces entre automaticidade e compreensão leitora. Revista Ponto de Vista , 8 (1), 47–61 https://periodicos.ufv.br/RPV/article/view/9203 .

Martins, M. A. (2018). Programa de fluência de leitura para escolares do 3° ao 5° ano: tradução, adaptação e aplicação (Doctoral dissertation). Retrieved from https://repositorio.unesp.br/handle/11449/152976

Martins, M. A., & Capellini, S. A. (2018). Avaliação do desempenho em fluência de leitura - ADFLU. Book Toy.

Mayeda, G. B. G., Navatta, A. C. R., & Miotto, E. C. (2018). Intervenção fonológica em escolares de risco para dislexia: revisão de literatura. Revista Psicopedagogia , 35 (107), 231–241 Recuperado em 13 de junho de 2020, de http://pepsic.bvsalud.org/scielo.php?script=sci_arttext&pid=S0103-84862018000200010&lng=pt&tlng=pt .

Mendonça, R. F. F., & Martins, A. P. L. (2014). Identificação de alunos em risco de apresentarem dislexia: Um estudo sobre a utilização da monitorização da fluência de leitura num contexto escolar. Revista Brasileira de Educação Especial , 20 (1), 09–20. https://doi.org/10.1590/S1413-65382014000100002 .

Morris, D., Trathen, W., Gill, T., Schlagal, R., Ward, D., & Frye, E. M. (2017). Assessing reading rate in the primary grades (1–3). Reading Psychology , 38 (7), 653–672. https://doi.org/10.1080/02702711.2017.1323057 .

Morris, D., Trathen, W., Perney, J., Gill, T., Schlagal, R., Ward, D., & Frye, E. M. (2017). Three DIBELS tasks vs. three informal reading/spelling tasks: A comparison of predictive validity. Reading Psychology , 38 (3), 289–320. https://doi.org/10.1080/02702711.2016.1263700 .

Moutinho, M. G. (2016). Erros de precisão na fluência em leitura oral de alunos do sexto ano do ensino fundamental de 4 escolas de Belém-Pará. Revista Escrita (PUCRJ. Online) , 21 , puc-rio.br/-17. https://doi.org/10.17771/PUCRio.escrita.25994 .

Nicolau, C. C., & Navas, A. L. G. P. (2015). Assessment of skills that predict reading success in 1st and 2nd grade children of elementary school. Revista CEFAC: Atualizacão Cientifica em Fonoaudiologia e Educacão , 17 (3), 917 Retrieved from https://link-gale.ez87.periodicos.capes.gov.br/apps/doc/A497053671/AONE?u=capes&sid=AONE&xid=d720db83 .

Oliveira, E. R., Amaral, S. B. G., & Picanço, G. (2013). Velocidade e precisão na leitura oral: Identificando alunos fluentes. Nonada: Letras em Revista , 2 (21), 1–14.  http://www.redalyc.org/articulo.oa?id=512451671025 .

Pacheco, V., & Santos, A. J. (2017). A fluência e compreensão leitora em diferentes níveis de escolaridade. Confluência , 1 (52), 232–256 http://llp.bibliopolis.info/confluencia/rc/index.php/rc/article/view/172 .

Palles da Silva, L., & Guaresi, R. (2019). Proposta de instrumento para rastreio de dificuldades de aprendizagem em alunos das séries iniciais. Revista Virtual Lingu@ Nostr@ , 6 (1), 68–76 Recuperado de http://linguanostra.net/index.php/Linguanostra/article/view/127 .

Peres, S., & Mousinho, R. (2017). Avaliação de adultos com dificuldades de leitura. Revista da Associação Brasileira de Psicopedagogia , 34 (103), 20–32 http://pepsic.bvsalud.org/scielo.php?script=sci_arttext&pid=S0103-84862017000100003&lng=pt&tlng=pt .

Rasinski, T. V. (2004). Assessing reading fluency. In Pacific Resources for Education and Learning .

Rasinski, T. V., & Young, C. (2017). Effective instruction for primary grade students who struggle with reading fluency. Inclusive Principles and Practices in Literacy Education (International Perspectives on Inclusive Education) , 11 , 143–157. Emerald Publishing Limited. https://doi.org/10.1108/S1479-363620170000011010 .

Rodrigues, S. D., & Ciasca, S. M. (2016). Dislexia na escola: identificação e possibilidades de intervenção. Revista Psicopedagogia , 33 (100), 86–97 http://pepsic.bvsalud.org/scielo.php?script=sci_arttext&pid=S0103-84862016000100010&lng=pt&tlng=pt .

Silva, C., & Capellini, S. (2019a). Indicadores cognitivo-linguístico em escolares com transtorno fonológico de risco para a dislexia. Distúrbios da Comunicação , 31 (3), 428–436. https://doi.org/10.23925/2176-2724.2019v31i3p428-436 .

Silva, C., & Capellini, S. A. (2017). Comparison of performance in metalinguistic tasks among students with and without risk of dyslexia. Journal of Human Growth and Development , 27 (2), 198–205. https://doi.org/10.7322/jhgd.118823 .

Silva, C., & Capellini, S. A. (2019b). Protocolo de avaliação das habilidades cognitivo-linguísticas para escolares em fase inicial de alfabetização . Book Toy.

Silva, N. S. M., & Crenitte, P. A. P. (2016). Performance of children at risk for reading difficulties submitted to an intervention program. CoDAS , 28 (5), 517–525. Epub September 26, 2016. https://doi.org/10.1590/2317-1782/20162015274 .

Tindal, G. (2017). Oral reading fluency: Outcomes from 30 years of research. (Technical Report 1701). University of Oregon Center Behavioral Research and Teaching. U.S. Department of Education, Institute of Education Sciences. https://www.brtprojects.org/wp-content/uploads/2017/10/TechRpt_1701ORF.pdf

Valencia, S., Smith, A., Reece, A., Li, M., Wixson, K., & Newman, H. (2010). Oral reading fluency assessment: Issues of construct, criterion, and consequential validity. Reading Research Quarterly , 45 (3), 270–291 http://www.jstor.org/stable/27822888 .

Download references

Acknowledgements

The authors would like to thank the members of the Investigation Learning Disabilities Laboratory (LIDA) of Sao Paulo State University-UNESP for making available reading data in digital audios.

Results of this publication funding PhD by the first author by the National Council for Scientific and Technological Development-CNPq.

Author information

Authors and affiliations.

Speech and Hearing Sciences Department, Sao Paulo State University “Júlio de Mesquita Filho”, UNESP, Campus Universitário, Av. Hygino Muzzi Filho, 737, 17525-900, Marília, SP, Brasil

Maíra Anelli Martins

São Paulo State University “Júlio de Mesquita Filho”, UNESP, Investigation Learning Disabilities Laboratory (LIDA), Marília, SP, Brazil

Maíra Anelli Martins & Simone Aparecida Capellini

“Language, Learning, Education” CNPq Research Group, Marília, SP, Brazil

Full Professor of Speech and Hearing Sciences Department, São Paulo State University “Júlio de Mesquita Filho”, UNESP, Marília, SP, Brazil

Simone Aparecida Capellini

You can also search for this author in PubMed   Google Scholar

Contributions

MAM designed and executed the study, performed the data collection, and wrote the paper and final revision of the manuscript. SAC designed the study, assisted with the data analyses, critically reviewed the theoretical content, and revised the paper. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Maíra Anelli Martins .

Ethics declarations

Ethics approval and consent to participate.

All procedures performed in the studies involving human participants were in accordance with the ethical standards of the institutional and/or Brazilian research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. All patients signed the informed consent form to participate in the study, following all the necessary ethical recommendations inherent to a project developed with humans.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Martins, M.A., Capellini, S.A. Identification of struggling readers or at risk of reading difficulties with one-minute fluency measures. Psicol. Refl. Crít. 34 , 10 (2021). https://doi.org/10.1186/s41155-021-00174-z

Download citation

Received : 13 June 2020

Accepted : 01 March 2021

Published : 20 March 2021

DOI : https://doi.org/10.1186/s41155-021-00174-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Struggling readers
• Universal screening
• Academic screening
• Academic difficulties
• Reading research

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Perspective
• Open access
• Published: 31 March 2017

Helping children with reading difficulties: some things we have learned so far

• Genevieve McArthur 1 &
• Anne Castles 1  

npj Science of Learning volume  2 , Article number:  7 ( 2017 ) Cite this article

34k Accesses

22 Citations

65 Altmetric

Metrics details

• Human behaviour

A substantial proportion of children struggle to learn to read. This not only impairs their academic achievement, but increases their risk of social, emotional, and mental health problems. In order to help these children, reading scientists have worked hard for over a century to better understand the nature of reading difficulties and the people who have them. The aim of this perspective is to outline some of the things that we have learned so far, and to provide a framework for considering the causes of reading difficulties and the most effective ways to treat them.

Similar content being viewed by others

Reading skills intervention during the Covid-19 pandemic

Rapid online assessment of reading ability

Enhancing reading skills through a video game mixing action mechanics and cognitive training

Introduction.

Over 20 years ago, The Dyslexia Institute asked a 9-year-old boy called Alexander to describe his struggle with learning to read and spell. He bravely wrote: “I have blond her, Blue eys and an infeckshos smill. Pealpie tell mum haw gorgus I am and is ent she looky to have me. But under the surface I live in a tumoyl. Words look like swigles and riting storys is a disaster area because of spellings. There were no ply times at my old school untill work was fineshed wich ment no plytims at all. Thechers sead I was clevor but just didn’t try. Shouting was the only way the techors comuniccatid with me. Uther boys made fun of me and so I beckame lonly and mishroboll”. 1

Alexander’s experience is not unique. Sixteen per cent of children struggle to learn to read to some extent, and 5% of children have significant, severe, and persistent problems. 2 The impact of these children’s reading difficulties goes well beyond problems with reading Harry Potter or Snapchat. Poor reading is associated with increased risk for school dropout, attempted suicide, incarceration, anxiety, depression, and low self-concept. 3 , 4 , 5 , 6 It is therefore important to identify and treat poor readers as early as we possibly can.

Scientists have been investigating poor reading—also known as reading difficulty, reading impairment, reading disability, reading disorder, and developmental dyslexia (to name but a few)—for over a century. While it may take another century of research to reach a complete understanding of reading impairment, there are number of things that we have learned about reading difficulties, as well as the children who experience reading them, that provide key clues about how poor reading can be identified and treated effectively.

Poor readers display different reading behaviours

One thing that we have learned about poor readers is that they are highly heterogeneous; that is, they do not all display the same type of reading impairment (i.e., “reading behaviour”; 7 , 8 , 9 , 10 , 11 , 12 ). Some poor readers have a specific problem with learning to read new words accurately by applying the regular mappings between letters and sounds. 7 , 8 , 13 , 14 This problem, which is often called poor phonological recoding or decoding, can be detected by asking children to read novel “nonwords” such as YIT. Other poor readers have a particular difficulty with learning to read new words accurately that do not follow the regular mappings between letters and sounds, and hence must be read via memory representations of written words. 7 , 13 , 15 , 16 This problem, which is sometimes called poor sight word reading or poor visual word recognition, can be detected by asking children to read “exception” words such as YACHT. In contrast, some poor readers have accurate phonological recoding and visual word recognition but struggle to read words fluently. 17 , 18 , 19 Poor reading fluency can be detected by asking children to read word lists or sentences as quickly as they can. In contrast yet again, some poor readers have intact phonological recoding and visual word recognition and reading fluency, but struggle to understand the meaning of what they read. These “poor comprehenders” 20 can be identified by asking them to read paragraphs aloud (to ascertain that they can read accurately and fluently), and then ask them questions about the meaning of what they have read (to ascertain that they do not understand what they are reading). It is important to note that most poor readers have various combinations of these problems. 21 For example, Alexander’s spelling suggests that he would have poor phonological decoding (since he misspells words like playtimes as “plytims”) and poor sight word knowledge (since he misspells exception words like said as “sead”). Thus, poor readers vary considerably in the profiles of their reading behaviour.

Reading behaviours have different “proximal” causes

Another thing we have learned about poor readers is that the same reading behaviour (e.g., inaccurate reading of novel words) does not necessarily have the same “proximal cause”. A proximal cause of a reading behaviour can be defined as a component of the cognitive system that directly and immediately produces that reading behaviour. 22 , 23 , 24 Most reading behaviours will have more than one proximal cause. Reflecting this, several theoretical and computational models of reading comprise multiple cognitive components that function together to produce successful reading behaviour (e.g., refs 25 , 26 , 27 , 28 ). While these models vary in some respects, all include cognitive components that represent (1) the ability to recognise letters (e.g., S), letter-clusters (e.g., SH), and written words (e.g., SHIP), (2) the ability to recognise and produce speech sounds (e.g., “sh”, “i”, “p”) and spoken words (e.g., “ship”), (3) the ability to access stored knowledge about the meanings of words (e.g., “a floating vessel”), and (4) links between these various components. Impairment in any one of these components or links will directly and immediately impair aspects of reading behaviour. Thus, guided by theoretical and computational models, we have learned that a poor reading behaviour can have multiple proximal causes, and we have some idea about what those proximal causes might be. 10 , 11 , 12

Reading behaviours have different “distal” causes

We have also learned that even if two poor readers have exactly the same reading behaviour with exactly the same proximal cause, this reading behaviour will not necessarily have the same “distal cause”. A distal cause has a distant (i.e., an indirect or delayed) impact on a reading behaviour. 22 , 23 , 24 Distal causes reflect the fact that reading is a taught skill that unfolds over time and across development. It depends upon a range of more cognitive abilities, such as memory, attention, and language skills, to name but a few. Depending on children’s strengths and weaknesses in these underlying abilities, and how these abilities affect learning over time, children will have different profiles of developmental, or distal, causes of their reading impairment. Stated differently, there can be different causal pathways to the same impairment of the reading system.

To provide an example, as mentioned earlier, a common reading behaviour observed in poor readers is inaccurate reading of new or novel words, which can be assessed using nonwords such as YIT. Indeed, some researchers have described this as the defining symptom of reading difficulties. 29 According to theoretical and computational models of reading, one proximal cause of impaired reading of nonwords is impaired knowledge of letter-sound mappings. But what is responsible for this proximal cause of poor nonword reading? There are multiple hypotheses. The prominent “phonological deficit hypothesis” proposes a pervasive language-based difficulty in processing speech sounds that affects the ability to learn to associate written stimuli (e.g., letters) with speech sounds. 30 The “paired-associate learning deficit hypothesis” proposes a memory-based difficulty in forming cross-modal mappings across the visual (e.g, letters) and verbal domains (e.g., speech sounds) that affects letter-sound learning (e.g., ref. 31 ). And the “visual attentional deficit hypothesis” proposes an attention-based impairment in the size of the attentional window, affecting the formation of the sub-word orthographic units (e.g., letters) used in the letter-sound mapping process. 32 These three hypotheses illustrate why a single reading behaviour (e.g., poor nonword reading) with a common proximal cause (impaired knowledge of letter-sound mappings) might not have the same distal cause (e.g., a phonological deficit, a paired-associate learning deficit, or a visual attention deficit). These hypotheses also raise the possibility that the distal causes of poor readers’ reading behaviours may vary as much (if not more) than the proximal causes and the reading behaviours themselves.

Poor readers have concurrent problems with their cognition and emotional health

Another thing we have learned about poor readers is that many (but not all) have comorbidities in other aspects of their cognition and emotional health. Regarding cognition, studies have found that a significant proportion of poor readers have impairments in their spoken language. 33 , 34 , 35 , 36 , 37 , 38 , 39 Studies have also found that poor readers have atypically high rates of attention deficit disorder—a neurological problem that causes inattention, poor concentration, and distractibility (e.g., refs 40 , 41 , 42 ). Regarding emotional health, there is evidence that poor readers, as a group, have higher levels of anxiety than typical readers (e.g., refs 43 , 44 ). The same is true for low self-concept, which can be defined as a negative perception of oneself in a particular domain (e.g., academic self-concept; e.g., refs 45 , 46 ).

The fact that poor readers vary in their comorbid cognitive and emotional health problems—as well as in their reading behaviours, and the proximal and distal impairments of these behaviours—creates an impression of almost overwhelming complexity. However, it is possible to simplify this complexity somewhat using a proximal and distal schema. Specifically, comorbidities of poor reading might be categorised according to whether they represent potential proximal or distal impairment of poor reading—or possibly both. For example, a child’s current problem with spoken vocabulary might be considered a proximal cause of their poor word reading behaviour since, according to theoretical and computational models of reading, vocabulary knowledge may directly underpin word reading accuracy or reading comprehension. However, a child’s previous problem with spoken vocabulary, which may or may not still be present, might be considered a distal cause of their poor word reading: A history of poor understanding of word meanings might reduce a child’s motivation to engage in reading (distal cause), which would impair their development of phonological recoding and visual word recognition (proximal cause), and hence their word reading accuracy and fluency (reading behaviour). Thus, the proximal and distal schema can prove useful in clarifying the causal chain of events linking a reading behaviour to a potential cause.

The proximal and distal schema can also be useful in clarifying reciprocal or circular relationships between comorbidities of poor reading and reading behaviours. For example, if a poor reader has low academic self-concept (distal cause), this may stymie their motivation to pay attention in reading lessons (distal cause), which will impair their learning of letter-sound mappings (proximal cause), and hence their poor word reading (reading behaviour). At the same time, a reverse causal effect may be in play: A child’s poor word reading in the classroom (distal cause) may create a poor perception of their own academic ability (proximal cause) that lowers their academic self-concept (behaviour). Thus, the proximal and distal schema can be used to help develop hypotheses as to whether comorbidities of poor reading are proximal and/or distal causes or consequences of poor reading. Ultimately, of course, all of these hypotheses must be tested through experimental training studies.

Proximal intervention is more effective than distal intervention

Poor readers have inspired, and have been subjected to, an extraordinary array of interventions such as behavioural optometry, chiropractics, classical music, coloured glasses, computer games, fish oil, phonics, sensorimotor exercises, sound training, spatial frequency gratings, memory training, medication for the inner ear, phonemic awareness, rapid reading, visual word recognition, and vocabulary training, to name just a selection. It is noteworthy that while many of these interventions claim to be “scientifically proven”, few have been tested with a randomised controlled trial (RCT)—an experiment that randomly allocates participants to intervention and control groups in order to reduce bias in outcomes. RCTs are the gold standard method for assessing a treatment of any kind, and the method that must be used to prove the effectiveness of a pharmaceutical treatment.

In order to make sense of the chaotic variety of interventions that claim to help poor readers, it may again be helpful to use the proximal and distal schema outlined above to subdivide interventions into two types: “proximal interventions” that focus training on proximal causes of a reading behaviour that are proposed to be part of the cognitive system for reading (e.g., phonics training, vocabulary training) and “distal interventions” that focus on distal causes of a reading behaviour (e.g., coloured lenses, inner-ear medication). The idea of making a distinction between proximal and distal interventions is supported by the outcomes of a systematic review of all studies that have used an RCT to assess an intervention in poor readers. 47 These studies assessed the effect of coloured lenses or overlays, medication, motor training, phonemic awareness, phonics, reading comprehension, reading fluency, sound processing, and sunflower therapy on poor readers. One key finding of this review is that it only identified 22 RCTs, which is a small number of gold-standard intervention studies given the huge number of interventions that claim to help poor readers. A second key finding is that the majority of RCTs of interventions for poor readers have assessed the efficacy of phonics training, which trains the ability to use letter-sound mappings to learn to read new or novel words. A third key finding is that only one type of intervention produced a statistically reliable effect. This was phonics training, which focuses on improving a proximal cause of poor word reading (i.e., letter-sound mappings). In contrast, interventions that focused on distal causes of poor reading did not show a statistically reliable effect in poor readers. The outcomes of this systematic review suggest that interventions that focus on phonics—a proximal cause of reading behaviour—are more likely to be effective than interventions that focus on a distal cause. In other words, the “closer” the intervention is to an impaired reading behaviour, the more likely it is to be effective.

Translating what we know (thus far) into evidence-based practice

At first glance, what we have learned (so far) about poor readers and reading difficulties paints a picture of such complex heterogeneity that it is tempting to throw one’s hands up in despair. And yet, somewhat paradoxically, it is this very heterogeneity that provides some important clues about how to maximise the efficacy of intervention for poor readers. First, the fact that poor readers vary in the nature of their reading behaviours suggests that the first step in identifying an effective intervention for a poor reader is to assess different aspects of reading (e.g., word reading accuracy, reading fluency, and reading comprehension). There are numerous standardized tests provided commercially (e.g., the York Assessment for Reading Comprehension available from GL Assessment) 48 or for free (e.g., the Castles and Coltheart Word Reading Test—Second Edition (CC2) available at www.motif.org.au ) 49 that can be used to determine if a child falls below the average range for their age or grade for reading accuracy, fluency, or comprehension. In our experience, a teacher who has appropriate training in administrating such tests can carry out this first step effectively.

Second, the fact that poor readers’ reading behaviours can have different proximal causes suggests that the next step is to test them for the potential proximal causes of their poor reading behaviours. This is where cognitive models of reading are a useful roadmap, providing an explicit account of the key processes directly underpinning successful reading behaviour. Again, this can be done using standardized tests that are available commercially (e.g., the Peabody Picture Vocabulary Test Fourth Edition available from Pearson) 50 or for free (e.g., the Letter-Sound Test available at www.motif.org.au ). 51 And well-trained teachers can administer these tests.

Third, the fact that poor readers vary in the degree to which they experience comorbid cognitive and emotional impairments suggests that it would be useful to assess poor readers for their spoken language abilities, attention, anxiety, depression, and self-concept, at the very least. This knowledge will reveal if they need support in other areas of their development, or if their reading-related intervention needs to be adjusted to accommodate their concomitant impairment in order to maximise efficacy. Trained speech and language therapists typically carry out the assessment of children’s spoken language; neuropsychologists are experts in assessing children’s attention; and clinical psychologists have the expertise to assess children’s emotional health.

Once a poor reader’s reading behaviours, proximal impairments, comorbid cognitive, and emotional health problems have been identified, it should be possible to design an intervention that is a good match to their needs. According to the systematic review conducted by Galuschka et al. 47 , current evidence suggests that this intervention should focus on the proximal impairment of a child’s reading behaviour, rather than a possible distal impairment. Two more recent controlled trials 52 , 53 and a systematic review 54 further suggest that it is possible to selectively train different proximal impairments of poor reading behaviours in order to improve those behaviours. The outcomes of these studies and reviews tentatively suggest that proximal interventions can be executed by a reading specialist or a highly-sophisticated online reading training programme.

In sum, over the last century or so, we have learned important things about reading difficulties and the people who have them. We have learned that poor readers display different reading behaviours, that any one reading behaviour has multiple proximal and distal causes, that some poor readers have concomitant problems in other areas of their cognition and emotional health, and that interventions that focus on proximal causes of poor reading behaviours may be more effective than those that focus on distal causes. This knowledge provides some clues to how we might best assist children with reading difficulties. Specifically, we need to assess poor readers for (1) a range of reading behaviours, (2) proximal causes for each poor reading behaviour, and (3) comorbidities in their cognition and emotional health. It should be possible to design an individualised intervention programme that accommodates for a poor reader’s comorbid cognitive or emotional problems whilst targeting the proximal causes of their poor reading behaviour or behaviours. This approach, which requires the co-ordinated efforts of teachers and specialists and parents, is no mean feat. However, according to the scientific evidence thus far, this is the most effective approach we have for helping children with reading difficulties.

The Dyslexia Institute. As I See It (Walker Books, 1990).

Shaywitz, S. E., Escobar, M. D., Shaywitz, B. A., Fletcher, J. M. & Makuch, R. Evidence that dyslexia may represent the lower tail of a normal distribution of reading ability. N. Engl. J. Med. 326 , 145–150 (1992).

Article   CAS   PubMed   Google Scholar  

Daniel, S. S. et al. Suicidality, school dropout, and reading problems among adolescents. J. Learn. Disabil. 39 , 507–514 (2006).

Article   PubMed   Google Scholar  

McArthur, G., Castles, A., Kohnen, S. & Banales, E. Low self-concept in poor readers: prevalence, heterogeneity, and risk. Peer. J. 4 , e2669 (2016).

Article   PubMed   PubMed Central   Google Scholar  

Carroll, J. M., Maughan, B., Goodman, R. & Meltzer, H. Literacy difficulties and psychiatric disorders: evidence for comorbidity. J. Child Psychol. Psychiatry 46 , 524–532 (2005).

Christie, C. A. & Yell, M. L. Preventing youth incarceration through reading remediation: issues and solutions. Read. Writ. Quart. 24 , 148–176 (2008).

Article   Google Scholar  

Castles, A. & Coltheart, M. Varieties of developmental dyslexia. Cognition 47 , 149–180 (1993).

Goulandris, N. K. & Snowling, M. Visual memory deficits: a plausible cause of developmental dyslexia? Evidence from a single case study. Cogn. Neuropsychol. 8 , 127–154 (1991).

Jones, K., Castles, A. & Kohnen, S. Subtypes of developmental dyslexia: recent developments and directions for treatment. ACQuiring Knowledge Speech Lang. Hear. 13 , 79–83 (2011).

Google Scholar  

McArthur, G. et al. Getting to grips with the heterogeneity of developmental dyslexia. Cogn. Neuropsychol. 30 , 1–24 (2013).

Peterson, R., Pennington, B. & Olson, R. Subtypes of developmental dyslexia: testing predictions of the dual-route and connectionist frameworks. Cognition 126 , 20–38 (2013).

Ziegler, J. C. et al. Developmental dyslexia and the dual route model of reading: Simulating individual differences and subtypes. Cognition 107 , 151–178 (2008).

Manis, F. R., Seidenberg, M. S., Doi, L. M., McBride-Chang, C. & Petersen, A. On the bases of two subtypes of development dyslexia. Cognition 58 , 157–195 (1996).

Temple, C. M. & Marshall, J. C. A case study of developmental phonological dyslexia. Br. J. Soc. Psychol. 74 , 517–533 (1983).

Friedmann, N. & Lukov, L. Developmental surface dyslexias. Cortex 44 , 1146–1160 (2008).

Broom, Y. M. & Doctor, E. A. Developmental phonological dyslexia: a case study of the efficacy of a remediation programme. Cogn. Neuropsychol 12 , 725–766 (1995).

de Jong, P. F. & van der Leij, A. Developmental changes in the manifestation of a phonological deficit in dyslexic children learning to read a regular orthography. Educ. Psychol 95 , 22–40 (2003).

Landerl, K., Wimmer, H. & Frith, U. The impact of orthographic consistency on dyslexia: a German-English comparison. Cognition 63 , 315–334 (1997).

Torgesen, J. K. Recent discoveries on remedial interventions for children with dyslexia. in The Science of Reading: A Handbook , (eds Snowling, M. J. & Hulme, C.), pp.521–537 (Blackwell, 2005).

Nation, K. & Snowling, M. Semantic processing and the development of word-recognition skills: evidence from children with reading comprehension difficulties. J. Mem. Lang. 39 , 85–101 (1998).

Stuart, M., & Stainthorp, R. Reading Development and Teaching (Sage, 2016).

Hulme, C., & Snowling, M. Developmental Disorders of Language, Learning and Cognition (Wiley-Blackwell, 2009).

Jackson, N. E., & Coltheart, M. Routes to Reading Success and Failure: Toward an Integrated Cognitive Psychology of Atypical Reading (Psychology Press, 2001).

Castles, A., Kohnen, S., Nickels, L. & Brock, J. Developmental disorders: what can be learned from cognitive neuropsychology? Phil. Trans. R. Soc. B 369 , 20130407 (2014).

Coltheart, M., Rastle, K., Perry, C., Langdon, R. & Ziegler, J. DRC: a dual route cascaded model of visual word recognition and reading aloud. Psychol. Rev. 108 , 204 (2001).

Hoover, W. A. & Gough, P. B. The simple view of reading. Read. Writ. 2 , 127–160 (1990).

Perry, C., Ziegler, J. C. & Zorzi, M. Nested incremental modeling in the development of computational theories: the CDP+ model of reading aloud. Psychol. Rev. 114 , 273–315 (2007).

Plaut, D. C., McClelland, J. L., Seidenberg, M. S. & Patterson, K. Understanding normal and impaired word reading: computational principles in quasi-regular domains. Psychol. Rev. 103 , 56–115 (1996).

Rack, J. P., Snowling, M. J. & Olson, R. K. The nonword reading deficit in developmental dyslexia: a review. Read. Res. Q. 1 , 29–53 (1992).

Snowling, M. Dyslexia as a phonological deficit: evidence and implications. Child Psychol. Psychiatry.Rev. 3 , 4–11 (1998).

Warmington, M. & Hulme, C. Phoneme awareness, visual-verbal paired-associate learning, and rapid automatized naming as predictors of individual differences in reading ability. Sci. Studying Read. 16 , 45–62 (2012).

Bosse, M.-L., Tainturier, M. & Valdois, S. Developmental dyslexia: the visual attention span deficit hypothesis. Cognitio 104 , 198–230 (2007).

Bishop, D. V. M. & Snowling, M. J. Developmental dyslexia and specific language impairment: same or different? Psychol. Bull. 130 , 858–886 (2004).

Eisenmajer, N., Ross, N. & Pratt, C. Specificity and characteristics of learning disabilities. J. Child Psychol. Psychiatry. 46 , 1108–1115 (2005).

Fraser, J., Goswami, U. & Conti-Ramsden, G. Dyslexia and specific language impairment: the role of phonology and auditory processing. Sci. Studies Read. 14 , 8–29 (2010).

McArthur, G. & Castles, A. Phonological processing deficits in specific reading disability and specific language impairment: same or different? J. Res. Read. 36 , 280–302 (2013).

McArthur, G. M., Hogben, J. H., Edwards, V. T., Heath, S. M. & Mengler, E. D. On the “specifics” of specific reading disability and specific language impairment. J Child Psychol. Psychiatry Allied Disciplines 41 , 869–874 (2000).

Article   CAS   Google Scholar  

Rispens, J. & Been, P. Subject–verb agreement and phonological processing in developmental dyslexia and specific language impairment (SLI): a closer look. Int.J. Lang. Commun.Dis. 42 , 293–305 (2007).

Catts, H. W., Adolf, S. M., Hogan, T. P. & Weismer, S. E. Are specific language impairment and dyslexia distinct disorders? J. Speech. Lang. Hear. Res. 48 , 1378–1396 (2005).

Gilger, J. W., Pennington, B. F. & DeFries, J. C. A twin study of the etiology of comorbidity: attention-deficit hyperactivity disorder and dyslexia. J. Am. Acad. Child Adolesc. Psychiatry 31 , 343–348 (1992).

Shaywitz, B. A., Fletcher, J. M. & Shaywitz, S. E. Defining and classifying learning disabilities and attention-deficit/hyperactivity disorder. J. Child. Neurol. 10 , S50–S57 (1995).

Willcutt, E. G. & Pennington, B. F. Comorbidity of reading disability and attention-deficit/hyperactivity disorder differences by gender and subtype. J. Learn. Disabil. 33 , 179–191 (2000).

Maughan, B. & Carroll, J. Literacy and mental disorders. Curr. Opin. Psychiatry 19 , 350–354 (2006).

Mugnaini, D., Lassi, S., La Malfa, G. & Albertini, G. Internalizing correlates of dyslexia. World J. Clin. Pediatr. 5 , 255–264 (2009).

Snowling, M. J., Muter, V. & Carroll, J. Children at family risk of dyslexia: a follow-up in early adolescence. J. Child Psychol. Psychiatry 48 , 609–618 (2007).

Taylor, L. M., Hume, I. R. & Welsh, N. Labelling and self‐esteem: the impact of using specific vs. generic labels. Educ. Psychol. 30 , 191–202 (2010).

Galuschka, K., Ise, E., Krick, K. & Schulte-Körne, G. Effectiveness of treatment approaches for children and adolescents with reading disabilities: a meta-analysis of randomized controlled trials. PLoS ONE 9 , e89900 (2014).

Snowling, M. J. et al. YARC York Assessment of Reading for Comprehension Passage Reading (GL Assessment, 2009).

Castles, A. et al. Assessing the basic components of reading: a revision of the Castles and Coltheart test with new norms. Aust. J. Learn. Diffic. 14 , 67–88 (2009).

Dunn, L. M., & Dunn, D. M. Peabody Picture Vocabulary Test: PPVT 4 (Pearson, 2015).

Larsen, L., Kohnen, S., Nickels, L. & McArthur, G. The letter-sound test (LeST): a reliable and valid comprehensive measure of grapheme-phoneme knowledge. Aust. J. Learn. Diffic. 20 , 129–142 (2015).

McArthur, G. et al. Sight word and phonics training in children with dyslexia. J. Learn. Disabil. 48 (4), 391–407 (2015a).

McArthur, G. et al. Replicability of sight word training and phonics training in poor readers: a randomised controlled trial. Peer. J. 3 , e922 (2015b).

Article   CAS   PubMed   PubMed Central   Google Scholar  

McArthur, G. et al. Phonics training for English‐speaking poor readers. The Cochrane Library . 12 , 1–102 (2012).

Download references

Author information

Authors and affiliations.

Department of Cognitive Science, ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, Sydney, NSW, 2109, Australia

Genevieve McArthur & Anne Castles

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Genevieve McArthur .

Ethics declarations

Competing interests.

The authors declare that they have no competing interests.

Rights and permissions

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Reprints and permissions

About this article

Cite this article.

McArthur, G., Castles, A. Helping children with reading difficulties: some things we have learned so far. npj Science Learn 2 , 7 (2017). https://doi.org/10.1038/s41539-017-0008-3

Download citation

Received : 22 April 2016

Revised : 16 February 2017

Accepted : 01 March 2017

Published : 31 March 2017

DOI : https://doi.org/10.1038/s41539-017-0008-3

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Perceptions of intelligence & sentience shape children’s interactions with robot reading companions.

• Nathan Caruana
• Ryssa Moffat
• Emily S. Cross

Scientific Reports (2023)

Deaf readers benefit from lexical feedback during orthographic processing

• Eva Gutierrez-Sigut
• Marta Vergara-Martínez
• Manuel Perea

Scientific Reports (2019)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Preventing Reading Difficulties in Young Children (1998)

Chapter: 1. introduction, 1 introduction.

Reading is essential to success in our society. The ability to read is highly valued and important for social and economic advancement. Of course, most children learn to read fairly well. In fact, a small number learn it on their own, with no formal instruction, before school entry (Anbar, 1986; Backman, 1983; Bissex, 1980; Jackson, 1991; Jackson et al., 1988). A larger percentage learn it easily, quickly, and efficiently once exposed to formal instruction.

SOCIETAL CHALLENGES

Parents, educators, community leaders, and researchers identify clear and specific worries concerning how well children are learning to read in this country. The issues they raise are the focus of this report:

1. Large numbers of school-age children, including children from all social classes, have significant difficulties in learning to read.

2. Failure to learn to read adequately for continued school success is much more likely among poor children, among nonwhite

children, and among nonnative speakers of English. Achieving educational equality requires an understanding of why these disparities exist and efforts to redress them.

3. An increasing proportion of children in American schools, particularly in certain school systems, are learning disabled, with most of the children identified as such because of difficulties in learning to read.

4. Even as federal and state governments and local communities invest at higher levels in early childhood education for children with special needs and for those from families living in poverty, these investments are often made without specific planning to address early literacy needs and sustain the investment.

5. A significant federal investment in providing bilingual education programs for nonnative speakers of English has not been matched by attention to the best methods for teaching reading in English to nonnative speakers or to native speakers of nonstandard dialects.

6. The passage of the Americans with Disabilities Act (ADA) provides accommodations to children and to workers who have reading disabilities. In order to provide full access for the individuals involved, these accommodations should reflect scientific knowledge about the acquisition of reading and the effects of having a reading difficulty.

7. The debate about reading development and reading instruction has been persistent and heated, often obscuring the very real gains in knowledge of the reading process that have occurred.

In this report, we are most concerned with the children in this country whose educational careers are imperiled because they do not read well enough to ensure understanding and to meet the demands of an increasingly competitive economy. Current difficulties in reading largely originate from rising demands for literacy, not from declining absolute levels of literacy (Stedman and Kaestle, 1987). In a technological society, the demands for higher literacy are constantly increasing, creating ever more grievous consequences for those who fall short and contributing to the widening economic disparities in our society (Bronfenbrenner et al., 1996). These economic dispari-

ties often translate into disparities in educational resources, which then have the self-reinforcing effect of further exacerbating economic disparities. Although the gap in reading performance between educational haves and have-nots has shrunk over the last 50 years, it is still unacceptably large, and in recent years it has not shrunk further (National Academy of Education, 1996). These rich-get-richer and poor-get-poorer economic effects compound the difficulties facing educational policy makers, and they must be addressed if we are to confront the full scope of inadequate literacy attainment (see Bronfenbrenner et al., 1996).

Despite the many ways in which American schools have progressed and improved over the last half century (see, for example, Berliner and Biddle, 1995), there is little reason for complacency. Clear and worrisome problems have to do specifically with children's success in learning to read and our ability to teach reading to them. There are many reasons for these educational problems—none of which is simple. These issues and problems led to the initiation of this study and are the focus of this report.

The many children who succeed in reading are in classrooms that display a wide range of possible approaches to instruction. In making recommendations about instruction, one of the challenges facing the committee is the difficult-to-deal-with fact that many children will learn to read in almost any classroom, with almost any instructional emphasis. Nonetheless, some children, in particular children from poor, minority, or non-English-speaking families and children who have innate predispositions for reading difficulties, need the support of high-quality preschool and school environments and of excellent primary instruction to be sure of reading success. We attempt to identify the characteristics of the preschool and school environments that will be effective for such children.

The Challenge of a Technological Society

Although children have been taught to read for many centuries, only in this century—and until recently only in some countries—has there been widespread expectation that literacy skills should be universal. Under current conditions, in many ''literate" societies, 40 to

60 percent of the population have achieved literacy; today in the United States, we expect 100 percent of the population to be literate. Furthermore, the definition of full-fledged literacy has shifted over the last century with increased distribution of technology, with the development of communication across distances, and with the proliferation of large-scale economic enterprises (Kaestle, 1991; Miller, 1988; Weber, 1993). To be employable in the modern economy, high school graduates need to be more than merely literate. They must be able to read challenging material, to perform sophisticated calculations, and to solve problems independently (Murnane and Levy, 1993). The demands are far greater than those placed on the vast majority of schooled literate individuals a quarter-century ago.

Data from the National Education Longitudinal Study and High School and Beyond, the two most comprehensive longitudinal assessments of U.S. students' attitudes and achievements, indicate that, from 1972 through 1994 (the earliest and most recently available data), high school students most often identified two life values as "very important" (see National Center for Educational Statistics, 1995:403). "Finding steady work" was consistently highly valued by over 80 percent of male and female seniors over the 20 years of measurement and was seen as "very important'' by nearly 90 percent of the 1992 seniors—the highest scores on this measure in its 20-year history. "Being successful in work" was also consistently valued as very important by over 80 percent of seniors over the 20-year period and approached 90 percent in 1992.

The pragmatic goals stated by students amount to "get and hold a good job." Who is able to do that? In 1993, the percentage of U.S. citizens age 25 and older who were college graduates and unemployed was 2.6 percent (U.S. Department of Labor, Office of Employment and Unemployment Statistics, quoted in National Center for Education Statistics, 1995:401). By contrast, the unemployment rate for high school graduates with no college was twice as high, 5.4 percent, and for persons with less than a high school education the unemployment rate was 9.8 percent, over three times higher. An October 1994 survey of 1993-1994 high school graduates and dropouts found that fewer than 50 percent of the dropouts were holding

jobs (U.S. Department of Labor, 1995 ; quoted in National Center for Education Statistics, 1995:401).

One researcher found that, controlling for inflation, the mean income of U.S. male high school dropouts ages 25 to 34 has decreased by over 50 percent between 1973 and 1995 (Stringfield, 1995 , 1997). By contrast, the mean incomes of young male high school graduates dropped by about one-third, and those of college graduates by 20 percent in the 1970s and then stabilized. Among the six major demographic groups (males and females who are black, white, or Hispanic), the lowest average income among college graduates was higher than the highest group of high school graduates.

Academic success, as defined by high school graduation, can be predicted with reasonable accuracy by knowing someone's reading skill at the end of grade 3 (for reviews, see Slavin et al., 1994). A person who is not at least a modestly skilled reader by the end of third grade is quite unlikely to graduate from high school. Only a generation ago, this did not matter so much, because the long-term economic effects of not becoming a good reader and not graduating from high school were less severe. Perhaps not surprisingly, when teachers are asked about the most important goal for education, over half of elementary school teachers chose "building basic literacy skills" (National Center for Education Statistics Schools and Staffing Survey, 1990-1991, quoted in National Center for Education Statistics, 1995:31) .

The Special Challenge of Learning to Read English

Learning to read poses real challenges, even to children who will eventually become good readers. Furthermore, although every writing system has its own complexities, English presents a relatively large challenge, even among alphabetic languages. Learning the principles of a syllabic system, like the Japanese katakana, is quite straightforward, since the units represented—syllables—are pronounceable and psychologically real, even to young children. Such systems are, however, feasible only in languages with few possible syllable types; the hiragana syllabary represents spoken Japanese with 46 characters, supplemented with a set of diacritics (Daniels

and Bright, 1996). Spoken English has approximately 5,000 different possible syllables; instead of representing each one with a symbol in the writing system, written English relies on an alphabetic system that represents the parts that make up a spoken syllable, rather than representing the syllable as a unit.

An alphabetic system poses a challenge to the beginning reader, because the units represented graphically by letters of the alphabet are referentially meaningless and phonologically abstract. For example, there are three sounds represented by three letters in the word "but," but each sound alone does not refer to anything, and only the middle sound can really be pronounced in isolation; when we try to say the first or last consonant of the word all by itself, we have to add a vowel to make it a pronounceable entity (see Box 1-1).

Once the learner of written English gets the basic idea that letters represent the small sound units within spoken and heard words, called phonemes, the system has many advantages: a much more limited set of graphemic symbols is needed than in either syllabic (like Japanese) or morphosyllabic (like Chinese) systems; strategies

for sounding out unfamiliar strings and spelling novel words are available; and subsequences, such as prefixes and suffixes, are encountered with enough frequency for the reader to recognize them automatically.

Alphabetic systems of writing vary in the degree to which they are designed to represent the surface sounds of words. Some languages, such as Spanish, spell all words as they sound, even though this can cause two closely related words to be spelled very differently. Writing systems that compromise phonological representations in order to reflect morphological information are referred to as deep orthographies. In English, rather than preserving one-letter-to-one-sound correspondences, we preserve the spelling, even if that means a particular letter spells several different sounds. For example, the last letter pronounced "k" in the written word "electric" represents quite different sounds in the words "electricity" and ''electrician," indicating the morphological relation among the words but making the sound-symbol relationships more difficult to fathom.

The deep orthography of English is further complicated by the retention of many historical spellings, despite changes in pronunciation that render the spellings opaque. The "gh" in "night" and "neighborhood" represents a consonant that has long since disappeared from spoken English. The "ph" in "morphology" and "philosophy" is useful in signaling the Greek etymology of those words but represents a complication of the pattern of sound-symbol correspondences that has been abandoned in Spanish, German, and many other languages that also retain Greek-origin vocabulary items. English can present a challenge for a learner who expects to find each letter always linked to just one sound.

SOURCES OF READING DIFFICULTIES

Reading problems are found among every group and in every primary classroom, although some children with certain demographic characteristics are at greater risk of reading difficulties than others. Precisely how and why this happens has not been fully understood. In some cases, the sources of these reading difficulties

are relatively clear, such as biological deficits that make the processing of sound-symbol relationships difficult; in other cases, the source is experiential such as poor reading instruction.

Biological Deficits

Neuroscience research on reading has expanded understanding of the reading process (Shaywitz, 1996). For example, researchers have now been able to establish a tentative architecture for the component processes of reading (Shaywitz et al., 1998; Shaywitz, 1996). All reading difficulties, whatever their primary etiology, must express themselves through alterations of the brain systems responsible for word identification and comprehension. Even in disadvantaged or other high-risk populations, many children do learn to read, some easily and others with great difficulty. This suggests that, in all populations, reading ability occurs along a continuum, and biological factors are influenced by, and interact with, a reader's experiences. The findings of an anomalous brain system say little about the possibility for change, for remediation, or for response to treatment. It is well known that, particularly in children, neural systems are plastic and responsive to changed input.

Cognitive studies of reading have identified phonological processing as crucial to skillful reading, and so it seems logical to suspect that poor readers may have phonological processing problems. One line of research has looked at phonological processing problems that can be attributed to the underdevelopment or disruption of specific brain systems.

Genetic factors have also been implicated in some reading disabilities, in studies both of family occurrence (Pennington, 1989; Scarborough, 1989) and of twins (Olson et al., 1994). Differences in brain function and behavior associated with reading difficulty may arise from environmental and/or genetic factors. The relative contributions of these two factors to a deficit in reading (children below the local 10th percentile) have been assessed in readers with normal-range intelligence (above 90 on verbal or performance IQ) and apparent educational opportunity (their first language was English and they had regularly attended schools that were at or above national

norms in reading). This research has provided evidence for strong genetic influences on many of these children's deficits in reading (DeFries and Alarcon, 1996) and in related phonological processes (Olson et al., 1989). Recent DNA studies have found evidence for a link between some cases of reading disability and inheritance of a gene or genes on the short arm of chromosome 6 (Cardon et al., 1994; Grigorenko et al., 1997).

It is important to emphasize that evidence for genetic influence on reading difficulty in the selected population described above does not imply genetic influences on reading differences between groups for which there are confounding environmental differences. Such group differences may include socioeconomic status, English as a second language, and other cultural factors. It is also important to emphasize that evidence for genetic influence and anomalous brain development does not mean that a child is condemned to failure in reading. Brain and behavioral development are always based on the interaction between genetic and environmental influences. The genetic and neurobiological evidence does suggest why learning to read may be particularly difficult for some children and why they may require extraordinary instructional support in reading and related phonological processes.

Instructional Influences

A large number of students who should be capable of reading ably given adequate instruction are not doing so, suggesting that the instruction available to them is not appropriate. As Carroll (1963) noted more than three decades ago, if the instruction provided by a school is ineffective or insufficient, many children will have difficulty learning to read (unless additional instruction is provided in the home or elsewhere).

Reading difficulties that arise when the design of regular classroom curriculum, or its delivery, is flawed are sometimes termed "curriculum casualties" (Gickling and Thompson, 1985; Simmons and Kame'enui, in press). Consider an example from a first-grade classroom in the early part of the school year. Worksheets were being used to practice segmentation and blending of words to facili-

tate word recognition. Each worksheet had a key word, with one part of it designated the "chunk" that was alleged to have the same spelling-sound pattern in other words; these other words were listed on the sheet. One worksheet had the word "love" and the chunk "ove.'' Among the other words listed on the sheet, some did indicate the pattern ("glove," "above," "dove"), but others simply do not work as the sheet suggests they should ("Rover," "stove," and "woven"). In lesson plans and instructional activities, such mistakes occur in the accuracy and clarity of the information being taught.

When this occurs consistently, a substantial proportion of students in the classroom are likely to exhibit low achievement (although some students are likely to progress adequately in spite of the impoverished learning situation). If low-quality instruction is confined to one particular teacher, children's progress may be impeded for the year spent in that classroom, but they may overcome this setback when exposed to more adequate teaching in subsequent years. There is evidence, however, that poor instruction in first grade may have long-term effects. Children who have poor instruction in the first year are more seriously harmed by the bad early learning experience and tend to do poorly in schooling across the years (Pianta, 1990).

In some schools, however, the problem is more pervasive, such that low student achievement is schoolwide and persistent. Sometimes the instructional deficiency can be traced to lack of an appropriate curriculum. More often, a host of conditions occur together to contribute to the risk imposed by poor schooling: low expectations for success on the part of the faculty and administration of the school, which may translate into a slow-paced, undemanding curriculum; teachers who are poorly trained in effective methods for teaching beginning readers; the unavailability of books and other materials; noisy and crowded classrooms; and so forth.

It is regrettable that schools with these detrimental characteristics continue to exist anywhere in the United States; since these schools often exist in low-income areas, where resources for children's out-of-school learning are limited, the effects can be very detrimental to students' probabilities of becoming skilled readers (Kozol, 1991; Puma et al., 1997; Natriello et al., 1990). Attending a

school in which low achievement is pervasive and chronic, in and of itself, clearly places a child at risk for reading difficulty. Even within a school that serves most of its students well, an instructional basis for poor reading achievement is possible. This is almost never considered, however, when a child is referred for evaluation of a suspected reading difficulty. Evidence from case study evaluations of children referred for special education indicate that instructional histories of the children are not seriously considered (Klenk and Palincsar, 1996). Rather, when teachers refer students for special services, the "search for pathology" begins and assessment focused on the child continues until some explanatory factor is unearthed that could account for the observed difficulty in reading (Sarason and Doris, 1979).

In sum, a variety of detrimental school practices may place children at risk for poorer achievement in reading than they might otherwise attain. Interventions geared at improving beginning reading instruction, rehabilitating substandard schools, and ensuring adequate teacher preparation are discussed in subsequent chapters.

DEMOGRAPHICS OF READING DIFFICULTIES

A major source of urgency in addressing reading difficulties derives from their distribution in our society. Children from poor families, children of African American and Hispanic descent, and children attending urban schools are at much greater risk of poor reading outcomes than are middle-class, European-American, and suburban children. Studying these demographic disparities can help us identify groups that should be targeted for special prevention efforts. Furthermore, examining the literacy development of children in these higher-risk groups can help us understand something about the course of literacy development and the array of conditions that must be in place to ensure that it proceeds well.

One characteristic of minority populations that has been offered as an explanation for their higher risk of reading difficulties is the use of nonstandard varieties of English or limited proficiency in English. Speaking a nonstandard variety of English can impede the easy acquisition of English literacy by introducing greater deviations

in the representation of sounds, making it hard to develop sound-symbol links. Learning English spelling is challenging enough for speakers of standard mainstream English; these challenges are heightened for some children by a number of phonological and grammatical features of social dialects that make the relation of sound to spelling even more indirect (see Chapter 6).

The number of children who speak other languages and have limited proficiency in English in U.S. schools has risen dramatically over the past two decades and continues to grow. Although the size of the general school population has increased only slightly, the number of students acquiring English as a second language grew by 85 percent nationwide between 1985 and 1992, from fewer than 1.5 million to almost 2.7 million (Goldenberg, 1996). These students now make up approximately 5.5 percent of the population of public school students in the United States; over half (53 percent) of these students are concentrated in grades K-4. Eight percent of kindergarten children speak a native language other than English and are English-language learners (August and Hakuta, 1997).

Non-English-speaking students, like nonstandard dialect speakers, tend to come from low socioeconomic backgrounds and to attend schools with disproportionately high numbers of children in poverty, both of which are known risk factors (see Chapter 4). Hispanic students in the United States, who constitute the largest group of limited-English-proficient students by far, are particularly at risk for reading difficulties. Despite the group's progress in achievement over the past 15 to 20 years, they are about twice as likely as non-Hispanic whites to be reading below average for their age. Achievement gaps in all academic areas between whites and Hispanics, whether they are U.S. or foreign born, appear early and persist throughout their school careers (Kao and Tienda, 1995).

One obvious reason for these achievement differences is the language difference itself. Being taught and tested in English would, of course, put students with limited English proficiency at a disadvantage. These children might not have any reading difficulty at all if they were taught and tested in the language in which they are proficient. Indeed, there is evidence from research in bilingual education that learning to read in one's native language—thus offsetting the

obstacle presented by limited proficiency in English—can lead to superior achievement (Legarreta, 1979; Ramirez et al., 1991). This field is highly contentious and politicized, however, and there is a lack of clear consensus about the advantages and disadvantages of academic instruction in the primary language in contrast to early and intensive exposure to English (August and Hakuta, 1997; Rossell and Baker, 1996).

In any event, limited proficiency in English does not, in and of itself, appear to be entirely responsible for the low reading achievement of these students. Even when taught and tested in Spanish, as the theory and practice of bilingual education dictates, many Spanish-speaking Hispanic students in the United States still demonstrate low levels of reading attainment (Escamilla, 1994; Gersten and Woodward, 1995; Goldenberg and Gallimore, 1991; Slavin and Madden, 1995). This suggests that factors other than lack of English proficiency may also contribute to these children's reading difficulties.

One such factor is cultural differences, that is, the mismatch between the schools and the families in definitions of literacy, in teaching practices, and in defined roles for parents versus teachers (e.g., Jacob and Jordan, 1987; Tharp, 1989); these differences can create obstacles to children's learning to read in school. Others contend that primary cultural differences matter far less than do "secondary cultural discontinuities," such as low motivation and low educational aspirations that are the result of discrimination and limited social and economic opportunities for certain minority groups (Ogbu, 1974, 1982). Still others claim that high motivation and educational aspirations can and do coexist with low achievement (e.g., Labov et al., 1968, working in the African American community; Goldenberg and Gallimore, 1995, in the Hispanic community) and that other factors must therefore explain the differential achievement of culturally diverse groups.

Literacy is positively valued by adults in minority communities, and the positive views are often brought to school by young children (Nettles, 1997). Nonetheless, the ways that reading is used by adults and children varies across families from different cultural groups in ways that may influence children's participation in literacy activities

in school, as Heath (1983) found. And adults in some communities may see very few functional roles for literacy, so that they will be unlikely to provide conditions in the home that are conducive to children's acquisition of reading and writing skills (Purcell-Gates, 1991, 1996). The implications of these various views for prevention and intervention efforts are discussed in Part III of this volume.

It is difficult to distinguish the risk associated with minority status and not speaking English from the risk associated with lower socioeconomic status (SES). Studying the differential experiences of children in middle- and lower-class families can illuminate the factors that affect the development of literacy and thus contribute to the design of prevention and intervention efforts.

The most extensive studies of SES differences have been conducted in Britain. Stubbs (1980) found a much lower percentage of poor readers with higher (7.5 percent) than with lower SES (26.9 percent).  Some have suggested that SES differences in reading achievement are actually a result of differences in the quality of schooling; that is, lower-SES children tend to go to inferior schools, and therefore their achievement is lower because of inferior educational opportunities (Cook, 1991). However, a recent study by Alexander and Entwisle (1996) appears to demonstrate that it is during nonschool time—before they start and during the summer months—that low-SES children fall academically behind their higher-SES peers and get progressively further behind. During the school months (at least through elementary school) the rate of progress is virtually identical for high- and low-SES children.

Regardless of the specific explanation, differences in literacy achievement among children as a result of socioeconomic status are pronounced. Thirty years ago Coleman et al. (1966) and Moynihan (1965) reported that the educational deficit of children from low-income families was present at school entry and increased with each year they stayed in school. Evidence of SES differences in reading achievement has continued to accumulate (National Assessment of Educational Progress, 1981, 1995). Reading achievement of children in affluent suburban schools is significantly and consistently higher than that of children in "disadvantaged" urban schools (e.g.,

NAEP, 1994, 1995; White, 1982; Hart and Risley, 1995). An important conceptual distinction was made by White (1982) in a groundbreaking meta-analysis. White discovered that, at the individual level, SES is related to achievement only very modestly. However, at the aggregate level, that is, when measured as a school or community characteristic, the effects of SES are much more pronounced. A low-SES child in a generally moderate or higher-SES school or community is far less at risk than an entire school or community of low-SES children.

The existence of SES differences in reading outcomes offers by itself little information about the specific experiences or activities that influence literacy development at home. Indeed, a look at socioeconomic factors alone can do no more than nominate the elements that differ between middle-class and lower-class homes. Researchers have tried to identify the specific familial interactions that can account for social class differences, as well as describe those interactions around literacy that do occur in low-income homes. For example, Baker et al. (1995) compared opportunities for informal literacy learning among preschoolers in the homes of middle-income and low-income urban families. They found that children from middle-income homes had greater opportunities for informal literacy learning than children of low-income homes. Low-income parents, particularly African-American parents, reported more reading skills practice and homework (e.g., flash cards, letter practice) with their kindergarten-age children than did middle-income parents. Middle-income parents reported only slightly more joint book reading with their children than did low-income families. But these middle-income parents reported more play with print and more independent reading by children. Among the middle-class families in this study, 90 percent reported that their child visited the library at least once a month, whereas only 43 percent of the low-income families reported such visits. The findings of Baker et al. that low-income homes typically do offer opportunities for literacy practice, though perhaps of a different nature from middle-class homes, have been confirmed in ethnographic work by researchers such as Teale (1986), Taylor and Dorsey-Gaines (1988), Taylor and Strickland (1986), Gadsden (1993), Delgado-Gaitan (1990), and Goldenberg et al. (1992).

ABOUT THIS REPORT

Charge to the committee.

The Committee on the Prevention of Reading Difficulties in Young Children has conducted a study of the effectiveness of interventions for young children who are at risk of having problems in learning to read. It was carried out at the request of the U.S. Department of Education's Office of Special Education Programs and its Office of Educational Research and Improvement (Early Childhood Institute) and the National Institute on Child Health and Human Development (Human Learning and Behavior Branch). The sponsors requested that the study address young children who are at -risk for reading difficulties, within the context of reading acquisition for all children. The scope included children from birth through grade 3, in special and regular education settings. The project had three goals: (1) to comprehend a rich research base; (2) to translate the research findings into advice and guidance for parents, educators, publishers, and others involved in the care and instruction of the young; and (3) to convey this advice to the targeted audiences through a variety of publications, conferences, and other outreach activities. In making its recommendations, the committee has highlighted key research findings that should be integrated into existing and future program interventions to enhance the reading abilities of young children, particularly instruction at the preschool and early elementary levels.

The Committee's Perspective

Our recommendations extend to all children. Of course, we are most worried about children at high risk of developing reading difficulties. However, there is little evidence that children experiencing difficulties learning to read, even those with identifiable learning disabilities, need radically different sorts of supports than children at low risk, although they may need much more intensive support. Childhood environments that support early literacy development and

excellent instruction are important for all children. Excellent instruction is the best intervention for children who demonstrate problems learning to read.

Knowledge about reading derives from work conducted in several disciplines, in laboratory settings as well as in homes, classrooms, and schools, and from a range of methodological perspectives. Reading is studied by ethnographers, sociologists, historians, child developmentalists, neurobiologists, and psycholinguists. Reading has been approached as a matter of cognition, culture, socialization, instruction, and language. The committee that wrote this report embraces all these perspectives—but we acknowledge the difficulty of integrating them into a coherent picture.

The committee agrees that reading is inextricably embedded in educational, social, historical, cultural, and biological realities. These realities determine the meaning of terms like literate as well as limits on access to literacy and its acquisition. Literacy is also essentially developmental, and appropriate forms of participation, instruction, and assessment in literacy for preschoolers differ from those for first graders and also from those for sophisticated critical readers.

Reading as a cognitive and psycholinguistic activity requires the use of form (the written code) to obtain meaning (the message to be understood), within the context of the reader's purpose (for learning, for enjoyment, for insight). In children, one can see a developmental oscillation between these foci: the preschool child who can pretend to read a story she has heard many times is demonstrating an understanding that reading is about content or meaning; the same child as a first grader, having been taught some grapheme-phoneme correspondences, may read the same storybook haltingly, disfluently, by sounding out the words she had earlier memorized, demonstrating an extreme focus on form. The mature, fluent, practiced reader shows more rapid oscillations between form-focused and meaning-focused reading: she can rely on automatic processing of form and focus on meaning until she encounters an unfamiliar pharmaceutical term or a Russian surname, whereupon the processing of meaning is disrupted while the form is decoded.

Groups define the nature as well as the value of literacy in culturally specific ways as well. A full picture of literacy from a cultural

and historical perspective would require an analysis of the distribution of literacy skills, values, and uses across classes and genders as well as religious and social groups; it would require a discussion of the connections between professional, religious, and leisure practices and literacy as defined by those practices. Such a discussion would go far beyond the scope of this report, which focuses on reading and reading difficulties as defined by mainstream opinions in the United States, in particular by U.S. educational institutions at the end of the twentieth century. In that context, employability, citizenship, and participation in the culture require high levels of literacy achievement.

Nature of the Evidence

Our review and summary of the literature are framed by some very basic principles of evidence evaluation. These principles derive from our commitment to the scientific method, which we view not as a strict set of rules but instead as a broad framework defined by some general guidelines. Some of the most important are that (1) science aims for knowledge that is publicly verifiable, (2) science seeks testable theories—not unquestioned edicts, (3) science employs methods of systematic empiricism (see Box 1-2). Science renders knowledge public by such procedures as peer review and such mechanisms as systematic replication (see Box 1-3). Testable theories are those that are potentially falsifiable—that is, defined in such a way that empirical evidence inconsistent with them can in principle be accumulated. It is the willingness to give up or alter a theory in the face of evidence that is one of the most central defining features of the scientific method. All of the conclusions reached in this report

are provisional in this important sense: they have empirical consequences that, if proven incorrect, should lead to their alteration.

The methods of systematic empiricism employed in the study of reading difficulties are many and varied. They include case studies, correlational studies, experimental studies, narrative analyses, quasi-experimental studies, interviews and surveys, epidemiological studies, ethnographies, and many others. It is important to understand how the results from studies employing these methods have been used in synthesizing the conclusions of this report.

First, we have utilized the principle of converging evidence. Scientists and those who apply scientific knowledge must often make a judgment about where the preponderance of evidence points. When this is the case, the principle of converging evidence is an important tool, both for evaluating the state of the research evidence and also for deciding how future experiments should be designed. Most areas of science contain competing theories. The extent to which one particular theory can be viewed as uniquely supported by a particular study depends on the extent to which other competing explanations have been ruled out. A particular experimental result is never equally relevant to all competing theoretical explanations. A given experiment may be a very strong test of one or two alternative theories but a weak test of others. Thus, research is highly convergent when a series of experiments consistently support a given theory while collectively eliminating the most important competing explanations. Although no single experiment can rule out all alternative explanations, taken collectively, a series of partially diagnostic studies can

lead to a strong conclusion if the data converge. This aspect of the convergence principle implies that we should expect to see many different methods employed in all areas of educational research. A relative balance among the methodologies used to arrive at a given conclusion is desirable because the various classes of research techniques have different strengths and weaknesses.

Another important context for understanding the present synthesis of research is provided by the concept of synergism between descriptive and hypothesis-testing research methods. Research on a particular problem often proceeds from more exploratory methods (ones unlikely to yield a causal explanation) to methods that allow stronger causal inferences. For example, interest in a particular hypothesis may originally stem from a case study of an unusually successful teacher. Alternately, correlational studies may suggest hypotheses about the characteristics of teachers who are successful. Subsequently, researchers may attempt experiments in which variables identified in the case study or correlation are manipulated in order to isolate a causal relationship. These are common progressions in areas of research in which developing causal models of a phenomenon is the paramount goal. They reflect the basic principle of experimental design that the more a study controls extraneous variables the stronger is the causal inference. A true experiment in controlling all extraneous variables is thus the strongest inferential tool.

Qualitative methods, including case studies of individual learners or teachers, classroom ethnographies, collections of introspective interview data, and so on, are also valuable in producing complementary data when carrying out correlational or experimental studies. Teaching and learning are complex phenomena that can be enhanced or impeded by many factors. Experimental manipulation in the teaching/learning context typically is less ''complete" than in other contexts; in medical research, for example, treatments can be delivered through injections or pills, such that neither the patient nor the clinician knows who gets which treatment, and in ways that do not require that the clinician be specifically skilled in or committed to the success of a particular treatment.

Educational treatments are often delivered by teachers who may enhance or undermine the difference between treatments and controls; thus, having qualitative data on the authenticity of treatment and on the attitudes of the teachers involved is indispensable. Delivering effective instruction occurs in the context of many other factors—the student-teacher relationship, the teacher's capability at maintaining order, the expectations of the students and their parents—that can neither be ignored nor controlled. Accordingly, data about them must be made available. In addition, since even programs that are documented to be effective will be impossible to implement on a wider scale if teachers dislike them, data on teacher beliefs and attitudes will be useful after demonstration of treatment effects as well (see discussion below of external validity).

Furthermore, the notion of a comparison between a treatment group and an untreated control is often a myth when dealing with social treatments. Families who are assigned not to receive some intervention for their children (e.g., Head Start placement, one-on-one tutoring) often seek out alternatives for themselves that approximate or improve on the treatment features. Understanding the dynamic by which they do so, through collecting observational and interview data, can prevent misguided conclusions from studies designed as experiments. Thus, although experimental studies represent the most powerful design for drawing causal inferences, their limitations must be recognized.

Another important distinction in research on reading is that between retrospective and prospective studies. On one hand, retrospective studies start from observed cases of reading difficulties and attempt to generate explanations for the problem. Such studies may involve a comparison group of normal readers, but of course inference from the finding of differences between two groups, one of whom has already developed reading difficulties and one of whom has not, can never be very strong. Studies that involve matching children with reading problems to others at the same level of reading skill (rather than to age mates) address some of these problems but at the cost of introducing other sources of difficulty—comparing two groups of different ages, with different school histories, and different levels of perceived success in school.

Prospective studies, on the other hand, are quite expensive and time consuming, particularly if they include enough participants to ensure a sizable group of children with reading difficulties. They do, however, enable the researcher to trace developmental pathways for participants who are not systematically different from one another at recruitment and thus to draw stronger conclusions about the likely directionality of cause-effect relationships.

As part of the methodological context for this report, we wish to address explicitly a misconception that some readers may have derived from our emphasis on the logic of an experiment as the most powerful justification for a causal conclusion. By such an emphasis, we do not mean to imply that only studies employing true experimental logic are to be used in drawing conclusions. To the contrary, as mentioned previously in our discussion of converging evidence, the results from many different types of investigations are usually weighed to derive a general conclusion, and the basis for the conclusion rests on the convergence observed from the variety of methods used. This is particularly true in the domains of classroom and curriculum research.

For example, it is often (but not always) the case that experimental investigations are high in internal validity but limited in external validity, whereas correlational studies are often high in external validity but low in internal validity. Internal validity concerns whether we can infer a causal effect for a particular variable. The more a study approximates the logic of a true experiment (i.e., includes manipulation, control, and randomization), the more we can make a strong causal inference. The internal validity of qualitative research studies depends, of course, on their capacity to reflect reality adequately and accurately. Procedures for ensuring adequacy of qualitative data include triangulation (comparison of findings from different research perspectives), cross-case analyses, negative case analysis, and so forth. Just as for quantitative studies, our review of qualitative studies has been selective and our conclusions took into account the methodological rigor of each study within its own paradigm.

External validity concerns the generalizability of the conclusion to the population and setting of interest. Internal validity and exter-

nal validity are often traded off across different methodologies. Experimental laboratory investigations are high in internal validity but may not fully address concerns about external validity. Field classroom investigations are often quite high in external validity but, because of the logistical difficulties involved in carrying out such investigations, are often quite low in internal validity. Hence, there is a need to look for a convergence of results—not just consistency across studies conducted with one method. Convergence across different methods increases confidence that the conclusions have both internal and external validity.

A not uncommon misconception is that correlational (i.e., nonexperimental) studies cannot contribute to knowledge. This is false for a number of reasons. First, many scientific hypotheses are stated in terms of correlation or lack of correlation, so that such studies are directly relevant to these hypotheses. Second, although correlation does not imply causation, causation does imply correlation. That is, although a correlational study cannot definitively prove a causal hypothesis, it may rule one out. Third, correlational studies are more useful than they used to be because some of the recently developed complex correlational designs allow for limited causal inferences. The technique of partial correlation, widely used in studies cited in this report, provides a case in point. It makes possible a test of whether a particular third variable is accounting for a relationship.

Perhaps the most important argument for quasi-experimental studies, however, is that some variables (for instance, human malnutrition, physical disabilities) simply cannot be manipulated for ethical reasons. Other variables, such as birth order, sex, and age, are inherently correlational because they cannot be manipulated, and therefore the scientific knowledge concerning them must be based on correlational evidence. Finally, logistical difficulties in carrying out classroom and curriculum research often render impossible the logic of the true experiment. However, this circumstance is not unique to educational or psychological research. Astronomers obviously cannot manipulate the variables affecting the objects they study, yet they are able to arrive at scientifically founded conclusions.

Outline of the Report

In Chapter 2 we present a picture of typical skilled reading and the process by which it develops. We see this as crucial background information for understanding reading difficulties and their prevention.

Part II presents a fuller picture of the children we are addressing in this report. We survey the population of children with reading difficulties in Chapter 3. In Chapter 4 we discuss risk factors that may help identify children who will have problems learning to read.

Part III presents our analysis of preventions and interventions, including instruction. Chapter 5focuses on the preschool years. Chapter 6 discusses prevention and literacy instruction delivered in classrooms in kindergarten and the primary grades. Chapter 7 presents our analysis of organizational factors, at the classroom, school, or district level, that contribute to prevention and intervention for grades 1 through 3. Chapter 8 continues discussion of grades 1 through 3, presenting more targeted intervention efforts to help children who are having reading difficulties.

Part IV presents our discussion of how the information reviewed in the report should be used to change practice. Chapter 9 discusses a variety of domains in which action is needed and obstacles to change in those domains. Chapter 10 presents our recommendations for practice, policy, and research.

While most children learn to read fairly well, there remain many young Americans whose futures are imperiled because they do not read well enough to meet the demands of our competitive, technology-driven society. This book explores the problem within the context of social, historical, cultural, and biological factors.

Recommendations address the identification of groups of children at risk, effective instruction for the preschool and early grades, effective approaches to dialects and bilingualism, the importance of these findings for the professional development of teachers, and gaps that remain in our understanding of how children learn to read. Implications for parents, teachers, schools, communities, the media, and government at all levels are discussed.

The book examines the epidemiology of reading problems and introduces the concepts used by experts in the field. In a clear and readable narrative, word identification, comprehension, and other processes in normal reading development are discussed.

Against the background of normal progress, Preventing Reading Difficulties in Young Children examines factors that put children at risk of poor reading. It explores in detail how literacy can be fostered from birth through kindergarten and the primary grades, including evaluation of philosophies, systems, and materials commonly used to teach reading.

READ FREE ONLINE

Welcome to OpenBook!

You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

Do you want to take a quick tour of the OpenBook's features?

Show this book's table of contents , where you can jump to any chapter by name.

...or use these buttons to go back to the previous chapter or skip to the next one.

Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

Switch between the Original Pages , where you can read the report as it appeared in print, and Text Pages for the web version, where you can highlight and search the text.

To search the entire text of this book, type in your search term here and press Enter .

Share a link to this book page on your preferred social network or via email.

View our suggested citation for this chapter.

Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

Get Email Updates

Do you enjoy reading reports from the Academies online for free ? Sign up for email notifications and we'll let you know about new publications in your areas of interest when they're released.

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

RESEARCH TOPIC: INVESTIGATING READING DIFFICULTIES AMONG CLASS SIX PUPILS OF WA BASIC SCHOOL COMPLEX

Related Papers

Lambert Academic Publishing

Justice Agyei Ampofo

This book explores investigate the reading difficulties among class six pupils of Wa Basic School Complex in the Wa Municipality. The research gathered data from both secondary and primary sources and used the mixed method approach. The key instruments used for the data collection were questionnaire. A total of sixty (60) respondents (class six pupils of Wa Basic School Complex) who took part in this study were purposively selected. The study found out that lack in reading by pupils, laziness to read books such as novels, newspapers and magazines by pupils, lack of enjoyment of reading test outside classroom work, playing by pupils rather than reading during leisure time and lack of provision of reading materials by parents, lack of guidance by parents on pupils reading, no proper method of reading by teachers in teaching, lack of guidance by teachers on pupils reading, lack of instructional materials for teaching reading in school and lack of encouragement to develop the habit of reading at early age, parents negative attitude toward reading, and illiteracy of parents are factors causing reading difficulties among class six pupils of Wa Basic School Complex.

ayo olowookun

Luckmore Gada

This study sought to identify the causes of reading difficulties affecting reading English among the rural Grade Six Learners in Bondamakara Cluster in Mutoko District. It followed a mixed research design approach. To obtain a representative sample of the population of primary schools, purposeful sampling was used, selecting two teachers and 70 learners from Mudzonga primary schools from the six schools in the cluster. Both qualitative and quantitative data was obtained from lesson observations and from reading tests, and findings revealed that, inadequate English reading materials, improper teaching methodology and insufficient English language development were causes of reading difficulties in Bondamakara cluster. Lack of English language development was a result of insufficient teacher-learner interactions during the English lessons. The results from the tests indicated that decoding, phonemic awareness, word recognition skills and comprehension might impede reading proficiency i...

International Journal of Linguistics, Literature and Translation

Arleen Rivera

The main purpose of the study was to diagnose the reading difficulties of grade 5 pupils in English. The researchers made use of descriptive method to obtain the data on the reading difficulties, comprehension, and behavioral performance of the respondents. To gather the data, the researchers adopted the reading selections from Philippine Informal Reading Inventory as a tool in examining the reading level of the pupils. As for the respondents’ reading miscues and behavioral performance, a teacher-made questionnaire was used to determine the learning areas that require intervention. The findings of the study pointed out that grade 5 pupils had difficulties on word recognition and reading comprehension. They tend to mispronounce English words and their behavior affects their performance while reading. A proposed reading program was included in this study to provide a reading remediation to learners with reading difficulties. Alongside with this initiative, teachers may conduct drill l...

Language is considered a strong weapon to develop and strengthen the relationship between human beings. The purpose of language learning is to enable a man to communicate in that particular language. In daily life communication people need and use a variety of language skills-listening, speaking, reading, and writing. Reading is one of the four macro skills to be developed as a means of effective communication in both first and second language learning context. It is a common observation that most of our students cannot read a text with suitable speed and proper understanding. The study was conducted in order to identify the Reading difficulties of students in the subject of English and a survey type research methodology was adopted to collect the data. A Questionnaire was designed for 280 students from 07 Federal Government Schools of Punjab, Pakistan. 20 students from grade 9 and 20 students from grade 10 were randomly selected from each school by giving equal representation to all the schools. The collected data was analyzed through SPSS and a comparison was made among the results of different respondent's observations. At the end of the study, the findings indicate that a significant majority of the respondents were of the opinion that they encountered the reading difficulties in pronunciation, vocabulary, accent, silent words, abbreviations, grammatical structure and in narrative writings. Majority of the respondents suggested that their reading skill can be improved by daily newspapers reading and story books, by frequent reading drills, visiting the different libraries and by providing extra reading sessions in formal class rooms.

Habtamu Walga

The aim of this study was to find out the factors that affect students' reading speed and comprehension that are related to students, teachers, and school with particular reference to Grade Nine Manasibu Secondary of West Wallagga Zone, Oromia. A descriptive survey of quantitative and qualitative data analysis method was employed to carry out this study. 97 students and 12 teachers were selected using purposive and simple random sampling techniques. The data were gathered through questionnaires, interview and classroom observation. The questionnaires were used to explore the teachers', students' and school related constraints with respect to the learning and teaching of reading speed and comprehension skills. The interview and classroom observation supplemented the data obtained through the questionnaires. Numbers and percentages were used to analyze the collected data. The result of the study revealed that the teachers rarely played their roles to improve the students' reading speed and comprehension in the classroom reading due to lack of awareness. Besides, the main factors students' related factors that affect the students' reading speed and comprehension skills in the target grade level were such as carelessness, negative attitudes toward reading, poor background knowledge, lack of knowledge of using appropriate reading strategies to the purpose of the reading, lack of practice and low participation in classroom reading. The finding also revealed the problem related to school like less orientedness to the reading skills, lack of finance, lack of awareness, large number students in each class, unsuitability of seating arrangements to pair and group works and lack of access to teaching aids. Finally, on the basis of the findings, it was recommended that in order to improve students' reading speed and comprehension, above all, the students have to practice reading in the target language by reading in the library and at their homes and by participating activities in the classroom. To this end, teachers also ought to play prominent roles to improve the students' reading speed and comprehension. That is, they should use modern methodologies which give room for improvement of reading speed and comprehension and the students have to play their appropriate roles in doing against problems that hindered students' learning of reading skills. Besides, the concerned bodies need to deal with the problem of large class size and instructional materials related factors to alleviate the problem.

shafaque zaheer

The purpose of the study is twofold in nature, firstly to enumerate the reading difficulties among post-primary students and secondly, to explore the challenges that the teachers face in teaching reading to these students. There were three main objectives of this study. First, to find out the factors contributing to the development of difficulties in reading among post-primary learners, second to find out teachers' perceptions of students' reading difficulties and its relationship with the actual performance of learners. Third, to draw a comparison between the reading difficulties faced by the students of two different educational Institutions: government school and private school. The study was conducted in the vicinity of Dhanbad district and specifically concentrates on the post-primary learners, that is, the students of standard 6th and 7th. Two groups of students belonging to two different schools were made to participate in the study. The first group comprised of the s...

Gemechis T . Chali

In this study, the researcher has revealed how teaching reading skill is going on in some selected second cycle of primary school (5-8) of Oromiya region, Ethiopia. Forty English language teachers who teach second cycle of primary school in the two zones of Ormiya participated in the study. To assess teachers’ and students’ views about teaching reading, an in depth interview and classroom observation were conducted on the selected subject of the study. The study investigated if the teachers employed an effective reading techniques and how the students were accessible to reading materials. It was found out that the most important problems identified in teaching reading is that the less applicability of appropriate reading techniques by teachers and students’ lack of relevant reading materials as well. Qualitative research design was employed to analyse the data collected through thick word explanation. The outcome of the study revealed that reading is not given adequate attention in the schools the way it ought to, all the subject teachers rarely use an effective reading techniques and there are less access of reading materials for the students. It was also seen during the classroom observation that teachers are not in a good position to implement active learning methods ALM while teaching reading skills. Thus, the study has found that teachers were unable to provide effective techniques of teaching reading and they rarely used ALM. Furthermore, the study found that libraries were not facilitated with reading materials in order to motivate students towards reading. Key words: Reading skills; teaching reading; EFL Teachers; primary school (5-8).

Review of Education, Administration & LAW

madiha tahir

The paper aims at investigating reading difficulties that the primary school learners face in English language. Keeping in view the aim of the study, it was further divided into two research objectives: To find out the factors that were causing difficulties in reading English text and To find out the effects that such factors have on the students’ performance in reading a text in English. The data was collected using two separate tools for each of the research objectives. Data for the first objective was collected using a semi-structured interview with the English teachers of the mentioned locale of the study. For the second objective non-participatory observation was selected as a method to collect data which included a check-list as a tool to mark the effects in the performance of the students with respect to their reading texts in English Language. As far as the analysis of the data is concerned, it was thematically analyzed and the effects were mentioned following the discussion...

RELATED PAPERS

zenaida cuenca

Stéphane Trois Carres

Jose Ruben Garcia

H.Özgür YEŞİLÇİMEN

Krzysztof Smykowski

International Journal of Heat and Mass Transfer

Hushairi Zen

Applied Surface Science

Carlos Humberto Gomez Meier

British Journal of Dermatology

Muhammad Uzair

Adriana Velazquez Morlet

Global Change — The IGBP Series

Yongkang Xue

Federica Pulvirenti

The American Journal of Drug and Alcohol Abuse

Nomi Weiss-laxer

Sungkana Hadi

Archives of General Psychiatry

Tracie Gardner

Scientific Data

Masato Moteki

Journal of Food Research

Guy Takuissu

Trilhas Filosóficas

Aldo Dinucci

Animal Conservation

Olle Calles

Cogent Social Sciences

Shannon Said

njjfr hggtgrf

Call Girls in Shaheen Bagh

preeya khan

Innovation in Aging

Inthira Roopsawang

Romanian Review of Geographical Education

mioara clius

加拿大毕业证办理SFU毕业证模仿效果图87527357<微Q>学历证书购买 SFU录取通知书Offer成绩单制作、24小时出SFU成绩单办理文凭烫金防伪效果西蒙菲莎大学毕业证

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

What can writing-process data add to the assessment of spelling difficulties?

• Open access
• Published: 22 April 2024

Cite this article

You have full access to this open access article

• Åsa Wengelin   ORCID: orcid.org/0000-0002-6913-5128 1 ,
• Sanna Kraft   ORCID: orcid.org/0000-0003-3324-7328 2 ,
• Fredrik Thurfjell 3 &
• John Rack   ORCID: orcid.org/0000-0001-7525-6180 4  

83 Accesses

Explore all metrics

Spelling difficulties are commonly associated primarily with spelling errors. However, it is not uncommon for spelling challenges to transform the whole writing process into a formidable struggle. This paper delves into the exploration of whether and to what extent analyses of children’s writing processes can enhance our understanding of their difficulties, potentially contributing to the assessment of spelling challenges. We focused particularly on the degree of hesitation within words and the ability to detect and correct spelling errors among children with and without reading and spelling difficulties, as well as how these processes impact the quality and lexical diversity of their texts. Additionally, we sought to contribute to disentangling the influence of spelling and decoding abilities on these processes. A cohort of 47 children, aged 10–13, participated in the study, comprising 16 typically developing children, 16 with predominantly spelling difficulties, and 15 with both reading and spelling difficulties. Our analysis encompassed their spelling performance in both standardized tests and task-oriented writing samples, as well as an examination of their pausing and revision behaviour. As expected, we found robust correlations between the children’s spelling test scores and the proportions of spelling errors in their texts. Furthermore, our findings indicated that children encountering spelling difficulties exhibited a reduced ability to detect and correct errors compared to their peers without such challenges. Additionally, they displayed a slightly higher tendency to experience word-internal interruptions, aligning with prior research. The children who also had reading difficulties produced fewer words and processed words more slowly compared to children in both the other groups. Intriguingly, process data did not reliably predict text characteristics, suggesting that dysfluent writing may not significantly detriment the overall quality of the text, contrary to our initial expectations based on prevailing writing development models. Nevertheless, the study revealed considerable individual variation, with some participants demonstrating a high degree of struggling and dysfluency, resulting in poorer text outcomes, but also others whose struggling processes led to better outcomes. We posit that the crucial aspect lies in identifying these individuals within a classroom context and gaining insights into their processes to provide them with appropriate, formative feedback and adequate writing tools to facilitate their writing.

Similar content being viewed by others

The use of cronbach’s alpha when developing and reporting research instruments in science education.

Why, When, Who, What, How, and Where for Trainees Writing Literature Review Articles

Reconsidering the Evidence That Systematic Phonics Is More Effective Than Alternative Methods of Reading Instruction

Avoid common mistakes on your manuscript.

Introduction

Individuals with reading and writing difficulties often identify spelling as their most significant (e.g., Hatcher et al., 2002 ; Sumner & Connelly, 2020 ) and enduring challenge (Kemp et al., 2009 ). They frequently leave more spelling errors in their texts than writers without such difficulties (e.g., Connelly et al., 2006 ), resulting in lower quality ratings compared to their peers’ work (Bogdanowicz et al., 2014 ; Connelly et al., 2006 ; Sterling et al., 1998). To some extent, these quality differences seem to persist even after texts have been corrected for spelling (Galbraith et al., 2012 ; Gregg et al., 2007 ; Tops et al., 2013 ). It has been suggested that variables such as low fluency causing cognitive overload (e.g., Berninger et al., 2008 ) or avoidance strategies (O’Rourke, 2020 ; Wengelin, 2007 ) resulting in lower lexical diversity (Sumner et al., 2016 ; Wengelin, 2007 ) could account for some of these outcomes, indicating that spelling difficulty is a complex phenomenon that requires understanding not only of the errors that meet the eye but also of the underlying processes. This raises questions about the need to take spelling processes more into account in the assessment and instruction of writing.

One might argue that spelling is not crucial since most texts can still be comprehensible despite a few errors. However, research suggests that spelling mistakes negatively impact the reading speed of fluent adult readers, even if they are not consciously noticed (Melin, 2007 ), and that children find texts with errors less engaging, memorable, well-crafted, and comprehensible (Varnhagen, 2000 ). Moreover, some readers use spelling errors to infer authors’ intelligence (Figueredo & Varnhagen, 2005 ), credibility (Schloneger, 2016), or trustworthiness (Melin, 2007 ). Therefore, it is not surprising that adults, including educators and parents, commonly consider spelling fundamental to good writing (Rankin et al., 1993 ), or that children and adolescents perceive spelling proficiency as crucial for academic success and future career prospects (Rankin et al., 1994 ). Spelling ability is typically assumed to reflect the effort invested in writing, and authors making spelling mistakes are often stigmatized as careless and lazy thinkers (Varnhagen, 2000 ). This is likely one reason why many individuals with reading and writing difficulties continue to struggle with writing well into their later years (e.g., Wengelin, 2007 ).

Let’s consider an exemplary case of struggling writing, drawn from the experiences of 15-year-old Philip, a participant in one of our previous studies (Wengelin et al., 2014 ). Despite initially scoring at Stanine 1 on a spelling test during the screening process, he managed to compose a short argumentative text (57 words long) with just two misspellings. A segment from the keystroke log (Example 1) sheds light on his approach to the task, which he needed a total of 37 min to complete. We zoom in on the third word “engagera” (engage). Numbers within angle brackets (e.g., <2.86>) shows pause lengths in seconds, and BACKSPACE X within angle brackets (e.g., <BACKSPACE4>) demonstrates Philip’s use of the backspace key, including number of characters deleted.

L<2.86>ärarna <42.58>sk<36.79><BACKSPACE2>bör eng<4.88>a<9.27>

<BACKSPACE2>ga<22.96><BACKSPACE4>äng<2.82>agera<2.22><BACKSPACE8>eng<4.75>agera<2.60><135.59>sig.

Philip clearly hesitated about, reread, and revised the word several times before his efforts resulted in a correct spelling. The first phoneme, /ɛ/, which he identified correctly seemed to cause a major challenge, as shown by the way he exchanged the letter “e” for “ä”, both of which can represent the phoneme, and then back to “e”.

One potential explanation for his laborious and slow word processing could be that Philip has fuzzy representations of words. According to this view (Sénéchal et al., 2016 ), mental representations of words are initially constructed as a frame in which consistent graphemes are clearly specified, whereas inconsistent graphemes are more likely to be underspecified, if represented at all. “Fuzziness” may arise from variability in pronunciation, complex morphological structures, or visual similarities. Consequently, uncertainty regarding the sequence or presence of specific letters may arise, leading to slow word production, particularly among children facing reading and writing challenges who struggle with recalling the correct letter combinations.

In combination with the stigma surrounding texts that include spelling errors, difficulties in retrieving the correct spelling from memory may also—with increasing age and awareness—lead to conscious worry about spelling, including increased hesitation, rereading, and revision. Philip’s example is, of course, anecdotal and stems from a relatively dated dataset. Thus, its generalizability to other writers grappling with reading and writing difficulties in today’s digital communication landscape remains unclear. However, a more recent study by Reynolds and Wu ( 2018 ), in which dyslexic young adults self-reported their Facebook usage, suggests that many writers encountering writing difficulties contend with significant stigma regarding their spelling. These writers commented, for example, on how spelling errors were used to discredit arguments or divert debates, causing strong emotional responses toward writing and prompting them to meticulously edit and revise their content until deemed error-free.

There is also evidence from experimental and quasi-experimental research suggesting that those with spelling difficulties often exhibit hesitation and struggle. This line of research typically operationalizes hesitation and struggle in terms of word production speed/fluency, word-level pausing, and revision. While some early studies failed to find significant differences in writing speed or pausing between children with and without dyslexia (Martlewm, 1992 ), or yielded inconclusive results (Søvik et al., 1987), more recent research has demonstrated that both young children (English 9-year-olds by Sumner et al., 2013 ; 2016 , Spanish 8–12-year-olds by Suárez-Coalla et al., 2020 and Afonso et al., 2020 , and French 11-year-olds by Alamargot et al., 2020 ) with dyslexia, and adolescents (Norwegian 17-year-olds by Torrance et al., 2016 , and Swedish 15-year-olds, by Wengelin et al., 2014 ) with reading and writing difficulties, have been reported to require more time to transition from one letter to another and/or to make more word-internal pauses, i.e. hesitate more within words, than comparable control/reference groups. Similar results have been demonstrated for Swedish (Wengelin, 2002 , 2007 ) and Croatian (Tomazin et al., 2023 ) adults, the majority of whom did not possess a university education, and for university students (Afonso et al., 2015 ; O’Rourke, 2020 ; Sumner & Connelly, 2020 ). However, Galbraith et al. ( 2012 ) found no differences in temporal processing between university students with and without dyslexia.

Regarding spelling-related revision, Wengelin’s (2002; 2007) adult dyslexic participants revised their spelling more frequently compared to the reference group, and their spelling-related revisions constituted a higher proportion of their total number of revisions. Notably, only 50% of their spelling revisions were successful. In Sumner and Connelly’s ( 2020 ) research, university students with dyslexia did not revise spelling more frequently than those in the control group, but their spelling revisions did indeed comprise a higher proportion of their overall revisions. Interestingly, in contrast, the adolescents in Torrance et al.’s ( 2016 ) study made slightly fewer word-level revisions than their peers. This could perhaps be attributed to either a lack of concern about errors or difficulty in error detection, possibly due to reading challenges. However, in a masked condition where their participants could not see their texts, they neither revised more nor less. Like Wengelin ( 2002 ; 2007 ), Torrance et al. analysed all word-level revisions, including for example typos, and we have only found one study focusing specifically on spelling error detection by individuals with reading and writing difficulties. O’Rourke ( 2020 ) conducted an experimental sentence-level task for this purpose and found that university students with dyslexia detected and correctly revised fewer spelling errors compared to students without dyslexia.

Although it is well established that texts by writers with spelling difficulties typically receive lower quality assessments, the relationship between their writing processes and the resulting texts is not yet clear. Contemporary models of writing and writing development, such as that of Hayes and Berninger ( 2014 ), the Simple View of Writing (Berninger et al., 2002 ), and the Revised Writer(s) Within Communities (WWC) model by Graham ( 2018 ), suggest that dysfluent and hesitant word processing can create cognitive overload, potentially impeding higher-level processes and thus affecting the content or structure of a text. Interestingly, a recent study by Rønneberg et al. ( 2022 ) that aimed to investigate this in Norwegian 6th-graders without known difficulties found no effects of fluency measures on the quality of completed text, thus not supporting what they termed the “process-disruption hypothesis” for typically developing children writing in a shallow orthography. The authors did note though that their participants may have had sufficient fluency in spelling and typing for this not to be disruptive. They also acknowledged that their results do not negate the relevance of spelling ability to higher-level text in individuals with writing difficulties.

For texts composed by writers with dyslexia, both Sumner et al. ( 2016 ) and Wengelin ( 2007 ) identified associations between spelling-related dysfluencies and lexical diversity. Sumner and Connelly ( 2020 ) also found such associations, albeit in a different manner. Their participants with dyslexia produced texts with lexical diversity equal to that of their peers but seemingly at the expense of spelling accuracy. The authors suggested that these writers had the ability to overlook spelling errors, possibly due to familiarity with spell check. This notion was supported by O’Rourke ( 2020 ) and O’Rourke et al. ( 2020 ) who found that although interrupting writing, the use of spell check by writers with dyslexia to alleviate spelling demands increased lexical diversity. O’Rourke’s result is in line with some previous research showing that dictating by means of speech recognition—thus not having to think about spelling—can facilitate for children with various language difficulties (Higgins & Raskind, 1995 ; Kraft, 2023 ; MacArthur & Cavalier, 2004 ; Quinlan, 2004 ). The suggestion that some writers had the ability to overlook spelling errors could potentially also apply to Torrance et al.’s ( 2016 ) participants, as Norwegian students are accustomed to typing their work and exams on a computer from an early age. Finally, Galbraith et al. ( 2012 ) reported a more complex relationship. Although their research indicated no discrepancies in the proportions of time that dyslexic and non-dyslexic undergraduates dedicated to various writing processes, their results did indicate that these processes were correlated with the final text’s quality in distinct ways for the two groups.

In summary: On an individual level, there appears to be little doubt that qualitative analysis of process data can offer valuable insights to both researchers and educators regarding the types of spelling challenges described above. It illuminates moments of hesitation, worry, error detection, attempted revisions, the success of these revisions, and avoidance strategies. Additionally, process data can reveal which orthographic patterns writers are aware of and find challenging. For instance, Philip demonstrated clear awareness that the phoneme /ɛ/ could be spelled in multiple ways, causing him difficulty. On the group level, while taking into account that the studies accounted for above defined and operationalized fluency and/or dysfluency in different ways, we note that they indicate a certain consistency regarding temporal aspects of word-level writing by individuals with spelling difficulties. The results for spelling-related revision and the relation between process variables and text characteristics are less conclusive. Disparities can probably, to a large extent, be explained by differences in demographics, input methods, tasks, and languages employed throughout the research. The studies accounted for include different age groups, levels of education, input modalities, and languages—including orthographies of varying levels of transparency. Thus, different results are not surprising. It is, for example, conceivable that due to fuzzy representations (e.g., Sénéchal et al., 2016 ), dysfluency in the writing of young children does indeed hinder their higher-level processing only until they reach a certain level of automatization, in accordance with the Simple View of Writing (Berninger et al., 2002 ). However, those who develop reading and writing difficulties may, with age, become increasingly aware of their limited proficiency, and thus become more hesitant, as highlighted by Reynolds and Wu ( 2018 ). This raises questions about the extent to which school children are at risk of developing such writing behaviour, when and how it happens in that case, and how classroom teachers can identify struggling writing in time to prevent it.

Three of the studies referred to in the literature review (Afonso et al., 2020 ; Alamargot et al., 2020 ; Suárez-Coalla et al., 2020 ) investigated children with reading and writing difficulties in the ages of ‘upper elementary school’/‘middle school’—all with a focus on handwriting skills. In the Swedish context, these are the grades (4–6, ages 10–12) where children are expected to move from basic writing skills into more complex spelling and composition. We speculate that these ages may be where differences between children with and without spelling difficulties start to become apparent and thus where their processes may start to deviate from those of their peers. Therefore, our first research question of this paper focuses on fluency and dysfluency in grade 4–6 Swedish children.

Another important aspect of the previous research is how the participants with spelling difficulties are conceptualized. Some studies have recruited participants with a known dyslexia diagnosis, while others have used the broader concept of reading and writing difficulties, and one has specifically focused on poor decoders. All these groups have also been shown to be poor spellers, but differences in dyslexia definitions and diagnoses across time and location aside, this means that they all, including our own research, assume reading difficulty as the default problem. Although, Torrance et al. ( 2016 ), who focused specifically on the writing of poor decoders, concluded that word-level hesitation in their sample appeared to be linked ‘solely to production rather than reading’ (Torrance et al., 2016 , p. 385), as differences between writers with and without reading and writing difficulties persisted in temporal patterns even in a condition where participants were prevented from seeing what they had written. However, inhibiting hesitation and lookbacks for anxious writers may not be easier than inhibiting other types of behaviour that have developed over a long period, and more research is needed to disentangle the influences of spelling and reading abilities on word processing. For example, the results of the studies included in the literature demonstrate the importance of distinguishing between word-level revision caused by hesitation which, as argued by Torrance et al could be merely a question of production, and spelling revision induced by unambiguous error detection, which clearly needs reading skill. As indicated by an eye-tracking study of typically developing adolescents by Beers et al. ( 2010 , p. 768), ‘reading at the inscription point’ was associated with text quality, possibly to ‘review their most recently composed words’. Paradoxically, error detection could be just as important when introducing compensatory tools to facilitate writing, such as spell check or speech recognition. Although experienced as useful by many (but under-researched), these systems are not infallible. In view of the above, we conclude that distinguishing reading and spelling skills may add to our understanding of spelling difficulties, and thus, our second research question focuses on the detection and revision of spelling errors. To understand the contribution of spelling difficulty per se, our main inclusion criterion was based on spelling skill, after which we assigned the participants into either a group with mainly spelling difficulties or a group with both reading and spelling difficulties.

The overarching aim of our paper is to explore the processes of 10–13-year-old (grades 4–6) Swedish children with and without spelling difficulties using keystroke logging, and to discuss to what extent the knowledge gained can be of use for assessment of spelling difficulties. Based on the results by Rønneberg et al. ( 2022 ), we assume that at least older children without reading and writing difficulties in our sample will have reached a certain ‘ceiling level’ of automatization. Younger children and children with reading and writing difficulties may not have done so to the same extent. Therefore, our main approach is comparative rather than correlational, as indicated by the two research questions outlined above. However, for the sake of comparability with other studies and because we are interested in whether and how process data can add to existing assessments, our third question focuses on the relationships between process data, text characteristics, and the outcomes of standardized spelling and word decoding tests. Our specific research questions are:

To what extent do Swedish children with and without spelling difficulties in grades 4–6 demonstrate dysfluency in writing in terms of word-internal pausing and word-level revision?

Can distinctions be identified between children characterized by both reading and spelling difficulties and children facing challenges specifically in spelling, particularly regarding the detection and revision of spelling errors?

Are there any identifiable correlations between data on writing processes, text characteristics, and the outcomes of standardized spelling and word decoding tests?

We expect children with spelling difficulties to be less fluent and produce texts with more spelling errors and of lower quality than typically developing children. We also expect children with both reading and spelling difficulties to detect and revise spelling errors to a lesser extent than the others. The results will be discussed in terms of implications for assessment.

Participants and corpus

Three groups of children aged 10–13 (grades 4–6), one primarily with spelling difficulties ( n  = 16), one with both reading and spelling difficulties ( n  = 15), and one without difficulties ( n  = 16), all of whom had received their entire education in a mainstream Swedish school and used laptops or tablets with physical keyboards daily, were drawn from a project aimed at understanding writing difficulties in children with decoding and spelling challenges and exploring ways to facilitate writing for them, through writing technologies and individual interventions. The project included 40 participants with reading and writing difficulties, but only 31 had complete data sets for the present study. These include a spelling test, a decoding test in two parts, and a writing task carried out on a computer—without compensatory writing technologies. These participants were recruited through special educational experts who were invited to suggest participants with reading and spelling difficulties, focusing specifically on those who would benefit from compensatory support with spelling. Spelling difficulties, as highlighted by Dockrell ( 2009 ), can be identified in a wide range of children, and we adopted an inclusive approach to participation. Autism and/or intellectual disability were exclusion criteria, but beyond that, we welcomed all children Footnote 1 . To confirm group membership, we conducted a standardized spelling test, DLS (Johansson, 1992 ). Only children who scored at stanine 3 or below were included.

Because error detection is an important aspect of this paper, we then used the LäSt (word and non-word) decoding test (Elwér et al., 2011 ) to divide this group of children into two subgroups post hoc: one with clear both reading and spelling difficulties and one with mainly spelling difficulties. Inclusion criteria for the group with both reading and writing difficulties were stanine 3 or lower on both the word-decoding part and the non-word decoding part of the decoding test. Throughout the paper, we will refer to the two groups with spelling difficulties as follows:

Children with mainly spelling difficulties.

Children with both reading and spelling difficulties.

We also initiated the recruitment of typically developing children for a reference group. Unfortunately, this data collection was interrupted by Covid-19, and therefore the reference group in this paper comprises only 16 children who, on average are slightly younger than the children with reading and writing difficulties.

The group with both reading and spelling difficulties comprised the oldest participants and exhibited the poorest performance in both reading and spelling, not only in comparison to their similarly aged peers but also in absolute terms. A Bayesian ANCOVA confirmed that the typically developing children, as expected, demonstrated stronger spelling abilities than participants in the two groups with spelling difficulties—despite being younger. However, we found no evidence for a difference between the two groups with spelling difficulties. That is, they were at similar spelling levels. The majority of children in these two groups performed at or below the expected level of a 4th grader—all of them at least one grade-level below expectations, with most of them falling even further behind.

Regarding non-word decoding, we observed very strong evidence for a group effect (BF 10  = 9410.36). Post hoc tests indicated moderate evidence for a difference between typically developing children and those with primarily spelling difficulties (BF 10  = 3.45). In contrast, there was very strong evidence that participants with both reading and spelling difficulties were weaker readers compared to both of the other two groups (BF 10  = 4071 for the comparison with typically developing children and BF 10  = 110.15 for the comparison with children mainly experiencing spelling difficulties).

For word decoding, the results were similar but demonstrated even higher probabilities (BF 10  = 137302.41 for the model based on Group). In summary, acknowledging substantial individual variation, the two groups with spelling difficulties exhibited similar levels of spelling proficiency but differed significantly in reading skills. Descriptive statistics are shown in Table  1 .

The corpus for the present study consists of 47 text samples containing both product and process data. The finally edited texts comprise a total of 4166 words (1884 by the typically developing children, 1495 by the children with mainly spelling difficulties, and 787 by the children with both spelling and reading difficulties) out of which 356 are misspelled: 64 by the children without difficulties and 292 by the children in the two groups with spelling difficulties. As will be shown later more errors were made during the writing processes, but they were detected and revised accordingly.

Elicitation material, instruments, and procedure

Individual sessions were conducted with a certified speech pathologist, either Author 2 or 3 of this paper, for all testing and text production. The DLS spelling test (Johansson, 1992 ) served as a standardized diagnostic tool, involving a word list of 36 dictated words for the child to spell. Each correctly spelled word earned the child one point, and the raw score was converted into stanine scores based on the child’s grade level (4–6). The test boasts reported reliabilities of 0.90 for grade 4, 0.88 for grade 5, and 0.96 for grade 6. The administration was carried out using pen and paper.

The LäSt decoding test (Elwér et al., 2011 ) functioned as a standardized reading assessment tool, featuring two lists of words: one with non-words and the other with real words. Both lists required the child to read individual units one at a time. The non-word list measured alphabetic reading skills, while the real-word list also evaluated the child’s orthographic reading abilities. The reported reliabilities for the two lists are 0.74 and 0.91, respectively.

The keyboarded texts were created on a MacBook computer equipped with ScriptLog, a keystroke logging program designed for recording typing processes (Wengelin et al., 2019 ). ScriptLog records each keystroke and mouse click, providing them with a timestamp, enabling playback of the writing process, and analysis of temporal patterns, pauses, and revisions. The texts were composed in ScriptLog’s simple editor, which is similar to Windows’ NotePad or TextEdit in Mac OS, and thus does not include spell check. Participants were prompted by short film clips (Berman & Verhoeven, 2002 ) presenting moral dilemmas related to cheating or stealing. They were instructed to present the problem and discuss what their favourite superhero would do in response to the incidents in the films. Participants were asked to write for a maximum of 30 min. The time spent on the task varied widely. One child gave up after 1.82 min, and another (the only one who exceeded the given time) kept writing for 65 min.

We report both product measures, that is, characteristics of the final compositions, and process measures, that is, measures related to temporal aspects of the writing process, and measures related to error detection and revision.

Product measures

We assessed text length, text quality, vocabulary diversity, and proportion of misspelled words in the finally edited texts. Prior to quality rating and calculations of text length and vocabulary diversity, all texts were corrected for spelling. Some words included more than one error but for the analyses in this study we only used number of misspelled words. We operationalized text length as the number of words in the final product, which we calculated using LIX.se, a tool which is similar to textinspector.com but specifically designed for Swedish. To measure vocabulary diversity, we used VocD, a measure that, as distinguished from type/token ratio, is not sensitive to text length (McCarthy & Jarvis, 2010 ). It does, however, require a minimum number of words (50) why not all texts could be included in this analysis. Text quality (holistic) was assessed by means of comparative judgment (using nomoremarking.com) which has been argued to have better reliability than criterion-based marking (Steedle & Ferrara, 2016; Verhavert et al., 2019). The basic idea is that judges compare two randomly selected texts and decide which is better—again and again, until each text has been compared with a large variety of other texts. Based on the recommendations in a meta-analysis by Verhavert et al. (2019) we let each text constitute the basis for comparison 20 times. The system calculates a quality score, between 0 and 100. To ensure acceptable reliability, we used four judges who had not participated in the data collection. Before starting the assessment process, the judges agreed on time slots, and how many assessments they should do during each slot to avoid that fatigue would influence their judging. They also conducted a pilot study assessing texts that were similar to those in the main study. The reliability measure reported by the system, Scale separation reliability Footnote 2 , was 0.92.

Process measures

We examined two types of process measures: (1) those concerning temporal aspects, and (2) those related to error detection and revision. Regarding temporal processing, we report word-internal mean interkey intervals (IKIs), as well as those that could be considered interruptions, here referred to as pauses . The latter necessitates establishing a pause threshold. This is somewhat problematic because pause thresholds set on the group level are by definition arbitrary. While it is essential to choose a pause threshold relevant to the research question, a two-second threshold has frequently been used to mark the point at which an IKI is considered a pause (Strömqvist et al., 2006 ) as seen in earlier keystroke logging research. This threshold was, for example, utilized in both Wengelin ( 2007 ) and Wengelin et al. ( 2014 ). Several subsequent studies that have recorded typing or handwriting have used the same threshold — either by convention or for comparability. Although this practice remains relatively common, variations in threshold choice between studies have become more apparent today. For instance, while Sumner et al. ( 2014 ) used a two-second criterion, Rønneberg et al. ( 2022 ) employed a one-second threshold within words and a two-second threshold before words. In this article, we focused on word-internal pauses and explored two different thresholds. First, we calculated the number of IKIs within words that lasted for 2 s or longer. Notably, two-second pauses are highly unlikely to occur within words during regular typing, even among children (Wengelin & Strömqvist, 2004 ). Although employing a two-second threshold might result in a lower recall rate, it is expected to yield a higher precision level, as the included pauses significantly disrupt the overall word production flow. In other words, while this approach may not capture all instances of word-level hesitation, the included pauses undoubtedly disrupt the general word production flow. Additionally, for comparison with the dataset of Rønneberg et al., which closely resembles our study in terms of recently collected data, keystroke logging usage, a reasonably similar age group, and a transparent orthography, we also present pauses based on a one-second criterion. We will revisit the rationale behind these thresholds in the Discussion section. For revision behavior, we focused on the extent to which children with and without reading and writing difficulties detected and corrected word-level errors during written composition and how frequently this occurred. Two annotators coded all revisions as either word-level revisions (typographical errors and spelling errors) or other revisions (formulation, content, punctuation, or other) and calculated the proportions of word-level revision for each group. We counted revisions of word-level errors as detected errors, regardless of their success, along with errors left in the final text to comprise the total number of errors. To calculate the detection rate, detected errors were then divided by the total number of errors.

Ethical considerations

As already mentioned, data analysed in the current study were obtained from a larger dataset collected as part of a research project which was funded by the Marcus and Amalia Wallenberg Foundation (Ref. No. 2014 − 0122). The data collection was conducted in eight schools in southern and mid-Sweden by the second and third authors. Testing normally took place over two sessions, to avoid exhausting the participants, but if a participant still showed signs of fatigue we interrupted and divided the rest of the data collection from that person in shorter sessions. Ethical approval for the study was granted by the Swedish Ethical Review Authority in Gothenburg (Ref. No. 702 − 17).

Written assent/consent was obtained from both the participants and their caregivers. Participants were informed that they could withdraw from the study at any time without providing a reason.

Statistical analyses

We used Bayesian methods to analyse the data. These methods allow for evidence in favour of both the presence and absence of group differences and correlations because they represent uncertainty about the true value of a parameter using a probability distribution, which can assign non-zero probabilities to both the null hypothesis and alternative hypotheses. Furthermore, Bayesian analyses have been argued to achieve better type I error control than traditional frequentist analyses because Bayesian methods allow for the incorporation of prior knowledge into the analysis, which can reduce the impact of random noise in the data. For all analyses, we report the Bayes factor for the best model in comparison to the null model (BF 10 ), which provides the evidence for the alternative hypothesis over the null hypothesis. For example, if BF 10  = 10, the alternative hypothesis is regarded as ten times as likely as the null hypothesis. In most of the literature, a Bayes factor below 3 is regarded as negligible. In such cases, we only state a lack of evidence for our models. Values between 3 and 10 indicate moderate evidence, and values above 10 indicate strong evidence (Jeffreys, 1961 ).

Because age is not evenly distributed across our three groups, for group comparisons, we performed Bayesian analysis of covariance, ANCOVA (Rouder et al., 2012 ) in Jamovi, version 2.3 (The Jamovi Project, 2022), using its default priors (r scale fixed effects = 0.5, r scale random effects = 1, r scale covariates = 0.354), on the proportion of word-level errors, error detection rate, frequency of word-internal pausing, vocabulary diversity, and text quality as dependent variables, including group as a fixed factor and age as a covariate for each comparison. The Bayesian ANCOVA works by comparing four models with various predictors of the dependent variable, in our case:

A null model, P(M) = 0.250.

A model containing only group as a predictor, P(M) = 0.250.

A model containing only age as a predictor, P(M) = 0.250, and.

A model containing both group and age as predictors, P(M) = 0.250.

Note that all odds were set to be equally likely, a priori (0.250). Posthoc comparisons between the individual groups are in Jamovi based on the t-test with a Cauchy prior r  = 0.707. To account for model uncertainty, we performed Bayesian model averaging to test the effects of both predictors. For relations between different variables, we conducted Bayesian Pearson’s correlations between the different spelling-related variables: spelling test score, proportion of misspellings in the final text, frequency of word-internal pausing, frequency of word-level revision, and between each of those with text quality or vocabulary diversity. Under the null hypothesis, we would expect a correlation of 0 between any two of the variables in any of the pairs in the correlation matrix. The alternative hypothesis is two-sided, and we assigned a uniform prior probability to all correlations between − 1 and + 1.

Since we are interested in whether and how process data can contribute to the assessment of spelling difficulties, we will first compare the product data, that is, the characteristics of the texts produced by the participants, and then the process data. Finally, we will present correlational analysis as follows: (a) correlations between the test results and the product data, (b) correlations between the process data and the product data, and (c) correlations between word-processing variables: spelling test, word-decoding test, proportion of misspelled words in the texts, word-internal pausing, error detection rate, and spelling revision.

Comparing the text characteristics of the three groups

The results for the text characteristics are detailed in Table  2 . For vocabulary diversity the evidence for any effect was negligible. However, as already mentioned, only a subset of the texts was included, and the results must be interpreted with great care. The typically developing children outperformed the other two groups for all the other three variables. For text length and text quality, the Bayesian analysis of covariance indicated strong evidence for the model based on Group only. In the case of the proportion of spelling errors, we found the strongest evidence for the model based on Group + Age (BF 10  = 43.37) but we also found increased odds for the model based on Group only (BF 10  = 38.29). The averaging analysis of the two predictors indicated that the data were more likely under models containing Group as a predictor than when including Age. In all three cases, posthoc tests indicated that typically developing children were likely to produce better results than both the other groups. Only for text length, children with mainly spelling difficulties were likely to perform better than the group with both reading and spelling difficulties.

Analyses of the process variables

Results for the process variables are presented in Table  3 . For the variables related to temporal processes, the Bayesian analysis of covariance indicated the strongest evidence for the model based on Group + Age, but the evidence for pauses longer than one second was negligible.

For the mean duration of word-internal Inter-Keystroke Intervals (IKIs), there was strong evidence for the model based on Group only, but the averaging analysis of the two predictors indicated that data were more likely under models containing Age as a predictor than when including Group. However, posthoc tests for Group indicated moderate (BF 10  = 8.863) evidence for a difference between the typically developing children and the children with both reading and writing difficulties, but not between any of these two groups and the group with only spelling difficulties. For word-internal pauses longer than 2 s, the evidence for models other than the one based on Group + Age was negligible, and once again, the averaging analysis of the two predictors indicated that data were more likely under models containing Age as a predictor than when including Group. Moreover, posthoc tests for Group indicated only negligible effects.

Regarding error detection and revision, the Bayesian analysis of covariance indicated strong evidence for both the model based on Group only and the model based on Group + Age for error detection, but the averaging analysis of the two predictors indicated that data were more likely under models containing Group as a predictor than when including Age. Posthoc tests indicated that the odds for detecting errors were much better for the typically developing children than for those in the two groups with spelling difficulties. With that in mind it was somewhat surprising to find that the probabilities for any effects of Group or Age on revision frequency or the proportion of word-level revision were, more or less, negligible. Instead, we found moderate evidence for the null hypothesis.

In sum, the probabilities for differences between the groups are small in most cases. Although the typically developing children appear to process words faster than the children with both reading and writing difficulties, age appears to be a more important predictor of both these variables and of word-internal pausing. However, visual inspection of the scatterplots (Fig.  1 ) related to these may add some food for thought. The leftmost scatterplot illustrates the mean durations of the word-internal IKIs and indicates that while word-processing speed appear to increase with age for all three groups, the distance between them is relatively stable. The scatterplot for word-internal pausing (> 2 s) on the other hand (the one in the middle) indicates that the less dysfluent the children appear to become with age, the closer the three groups get to each other. But although differences between them decreases accordingly, the participants with both reading and spelling difficulties—who are also the poorest spellers in relation to their ages—stand out as the most dysfluent. For most age levels this group demonstrate the highest number of word-internal pauses > 2 s. We will return to that in the discussion section. The probability that children detect and correctly revise their errors is, on the other hand, much higher for the typically developing children. Interestingly, the children with only spelling difficulties seem unlikely to outperform their peers with both reading and spelling difficulties in speed (mean duration of word-internal IKIs), (word-internal) pausing and revision. However, for error detection rate, the patterns look completely different. While typically developing children and the children with mainly spelling difficulties appear to improve their ability to detect and revise errors, the children with both reading and spelling difficulties demonstrate no such tendencies.

Scatterplots, mean duration of word-internal IKI:s, word-internal pausing, and error detection rate for typically developing children (0), children with mainly spelling difficulties (1), and children with both reading and spelling difficulties (2)

Bayesian Pearson correlations

Our sample is too small for reliable reports of correlations for each group, and therefore, we will focus mainly on correlations for the whole sample. We did, however, also run groupwise correlations, to explore whether some correlations for the whole group may have been driven by group differences rather than by a linear relation, and we will touch upon a couple of these.

We first report correlations between the spelling test and the word decoding test on the one hand and the text characteristic variables on the other. Bayesian correlation pairs are shown in Table  4 . We found no evidence for any correlation with vocabulary diversity and have excluded that variable from the table. Not surprisingly the odds for a strong correlation ( r = −0.735) between the tests and proportion of misspelled words are very high (BF 10  = 3.43e + 6). Furthermore, we found very strong evidence, with Bayes factors around 1000 for moderate to strong correlations ( r  ≈ 0.5) between both decoding and spelling skills on the one hand and text quality on the other. Finally, we also found strong evidence for correlations between decoding skills and text length.

However, individual variation within the groups is large and when we looked at text length and text quality for the three groups separately only one of these correlations held for a single group. The evidence was relatively strong (BF 10  = 13.62) for a correlation ( r  = 0.68) between spelling test results and text quality for the group with mainly spelling difficulties.

We then analysed correlations between spelling process related variables and the two higher-level text characteristics for the whole sample and found only negligible results.

Finally we carried out correlational analyses between the different word-level variables (test results, proportion of misspelled words in the texts, error detection rate, word-internal pausing, error detection rate, and duration of word-internal IKI:s. Since no effects were found in the comparative analysis for revision frequency or proportion word-level revision, these variables were excluded from the correlational analyses.

For word-internal pausing, we chose to include the variable with the strongest results from the comparisons, which was word-internal pausing > 2 s. Numerous correlation models with very large Bayes factors were found for correlations involving test results and word processing variables from the writing data. Table  5 shows the Bayesian Correlation Matrix, and Fig.  2 . shows the correlation plots. Not surprisingly, the spelling test results appear to correlate with both the word decoding test ( r  = 0.69) and the proportion of misspelled words in the text ( r = −0.74), indicating that poor spelling and poor word decoding go hand in hand. Furthermore, those who receive low results in a spelling test also produce many spelling errors during composition. Error detection rate appears to correlate with all three of these variables ( r  = 0.64 for the spelling test, 0.41 for the word decoding test, and −0.80 for the proportion misspelled words in the finally edited texts). This suggests that one of the reasons why poor spellers leave many errors in their texts is that they do not detect them or alternatively do not know how to revise them. However, although relatively strong, the evidence for the correlation between error detection rate and word decoding is considerably lower than for the other models (BF 10  = 10.018).

Correlation plots for word-processing related variables

Regarding the temporal process variables, there is strong evidence for correlations between the mean duration of word-internal IKIs and all the other variables, while for word-internal pausing there is evidence only for a correlation with the proportion of misspelled words ( r  = 0.444). In other words, those who hesitate more within words also tend to make many spelling errors. Just like for the correlation between word decoding skill and error detection rate, the evidence for this model is lower than that of the others, but still with a Bayes factor of 20.7, meaning that it is 20 times more probable than the null model. However, as shown in the correlation plot for word-internal pausing, the participants are scattered around one end of the regression line. Moreover, when conducting the Bayesian correlation analyses with this variable for each group separately, we found no evidence for such a correlation, so the result should be interpreted with care.

In our study, we embarked on a journey to deepen our understanding of how spelling data derived from children’s composition processes could enhance our comprehension of spelling difficulty beyond traditional spelling test results and observations from free writing samples by children with reading and writing difficulties. We were interested in whether such analyses could contribute to the assessment of spelling. Our primary focus was on (a) spelling difficulties in general and (b) the role of reading difficulties in combination with spelling difficulties.

Our first question aimed to determine whether 10–13-year-old Swedish children with spelling difficulties exhibit comparable hesitation and avoidance behaviours to those observed in adults and adolescents in previous studies. The succinct response to this query appears to be negative, or at least not to a significant extent. While typically developing children outperformed others for all product variables except vocabulary diversity, we found no indications that the groups with spelling difficulties displayed distinct patterns of revision or pauses exceeding one second. For both mean word-internal IKIs and word-internal pauses > 2 s, the best model was the one based on Group + Age, and the averaging analysis of the two predictors indicated that data were most likely under models containing Age as a predictor. These results contrast with those of Sumner et al. ( 2013 ), who showed that children with dyslexia made more word-internal pauses during handwriting. Since our group of children was based on spelling difficulty in a broad sense, these results are not too surprising. A very tentative and premature interpretation of these results could be that it is not any spelling difficulty that drives dysfluency in writing, but rather an underlying disorder, such as dyslexia. However, more research and larger samples would be needed to support that notion.

The effect of age was also clearly visible in the scatterplots in Fig.  1 . Within each group, the speed of word-level processing, as shown by the word internal IKIs, increased, and the number of long word-internal interruptions, in terms of pauses exceeding 2 s., decreased. This could to a certain extent be taken to support the claim by Rønneberg et al. ( 2022 ) that word-internal pausing did not distinguish weaker spellers from stronger in typically developing children of the same age. It does, however, also raise the question of what constitutes a dysfluency, since they only measured pauses > 1 s. within words. Like these authors, we found no evidence for either age or group effects on 1-s pauses. The suggested explanation for the results of Rønneberg et al. was that perhaps the participants in their study had already automatized typing and spelling. This interpretation seems reasonable in the light of the behaviour of the typically developing children in our data. However, for the children with spelling difficulties automatization appear to happen considerably later. While the gap between the groups narrowed considerably with age for pauses > 2 s., the gaps between the groups for mean word internal IKI:s appeared to remain more or less consistent. These findings have the potential to support the idea that fuzzy representations of words (Perfetti, 2007; Sénéchal et al., 2016 ) diminish with age in typically developing children but persist, or at least decrease at a slower rate, for children with spelling difficulties.

Our second inquiry aimed to investigate the extent to which reading difficulty influenced the observed patterns. Interestingly, we found evidence only for one clear distinction between the two groups with spelling difficulties and that related to text length. Children with mainly spelling difficulties produced considerably more text than those with both spelling and reading difficulties. In fact, the subcorpus based on texts by children with mainly spelling difficulties was about twice the size of that by children with both reading and spelling difficulties. The explanation for this is unclear. Since the children with both reading and spelling difficulties were older than those with mainly spelling difficulties, we certainly did not anticipate this difference. A potential explanation could have been a high degree of dysfluency, but as already discussed, our analyses provided very moderate evidence for this, primarily in terms of longer word internal IKIs, and very little effect for pausing or revision. Another possibility is that the children who demonstrate both reading and spelling difficulties, and thus were more “dyslexic-like”, than those with mainly spelling difficulties, had other underlying language difficulties, and/or as suggested by Torrance et al. ( 2016 ), less prior knowledge due to limited print exposure.

Of particular interest for the distinction between children with mainly spelling difficulties and those with both reading and spelling difficulties was of course the question of error detection. Surprisingly, while the evidence was strong for the typically developing children outperforming the children with spelling difficulties, we found no statistical evidence that reading difficulty played a role on the group level. However, it may be worth directing some attention to the rightmost scatterplot in Fig. 1 . Although visual observations of scatterplots should never substantiate any scientific claim, this plot does seem to tell a story that merits further research. While error detection seems to improve with age for both typically developing children and the group with mainly spelling difficulties, this improvement does not appear to be evident for the group with both reading and spelling difficulties. To our knowledge, this has not been investigated before.

Our third question related to the correlations between variables. As already mentioned, and in accordance with previous research, we found strong evidence for a correlation between spelling test results and text quality. Furthermore, despite not finding any group differences for error detection between the groups with spelling difficulties, we did observe some evidence for a correlation between the word decoding test and error detection. Therefore, we are not yet prepared to rule out the influence of reading difficulty on error detection, but should rather re-evaluate our inclusion and exclusion criteria. Is there also a relation between process and text characteristics? Whereas we did find strong evidence for a relation between test data and text characteristics, we found no correlations between the process data and product data for these young writers, except for the correlation between percentage of spelling errors, and duration of word internal IKIs, indicating on the one hand that spelling does indeed influence the processes, but that at least for the children in this study, without consequences for the text characteristics. Hence, once again our results support the claims by Rønneberg et al. (2020) that word-level dysfluency does not necessarily impede higher processes of writing in young writers—with or without reading and writing difficulties. We found this result slightly surprising, yet hopeful. It could mean that on a general level these children have not (yet?) developed the types of writing behaviour demonstrated by Philip and that described by the participants of Reynolds and Wu ( 2018 ) and thus that that type of stigma can be prevented.

Finally, we return to our final question and the title of this paper. What can writing-process data add to the assessment of spelling difficulties? At first sight: perhaps very little—at least for these young children. We have not been able to show that children with spelling difficulties consistently demonstrate process patterns that predicts their difficulties better than a traditional spelling test. Is then the problem with cognitive overload, caused by difficulties with spelling and other lower order processes, overstated, as indicated by Torrance et al. ( 2016 )? Perhaps, and that is encouraging. It could be the case that writing instruction has improved, or that better writing tools have become more accessible, or something else that have changed the conditions for writing development. However, as already mentioned, the longer mean durations of the word-internal IKI:s do indeed suggest that children with reading and spelling difficulties process words more slowly than the typically developing children, even if they don’t make long word-internal pauses, and this could support the theory of fuzzy representations (cf. Perfetti, 2007 Sénéchal et al., 2016 ), rather than conscious hesitations and coping strategies. On the other hand, the fact that not all the gaps between the groups appear to narrow, and that the group with both reading and spelling difficulties show different profiles for some variables while simultaneously being older than the others indicate that there could still be a definable group out there to identify in order to prevent stigmas related to writing, even if we didn’t manage to capture that in our current analyses. More research is needed, on larger groups, other age spans, more orthographies, and the effects of writing technologies to support struggling writers. One of several limitations with our study is the limited number of participants in each group.

In the Swedish context, the transition between grade 6 and 7 (age 12–13, accidentally the age of many of the poorest writers in our sample) should most likely be in focus for our next study. In this transition children leave upper elementary and move to secondary school, which not only constitutes a different school form, but is also frequently located at a different geographical location, with new teachers—who typically expects that the elementary school teachers have “fixed” their pupils’ reading and writing skills.

Moreover, during our explorations and analyses of the data we have noticed that there are individuals with weak spelling test results who manage to produce text with very few errors and vice versa (see Fig.  2 ). In fact, a couple of students with spelling and decoding difficulties, as assessed by the tests, produced texts that were completely free from spelling errors. During the analyses of our data, we also noticed how some children were very successful in their spelling revisions while revision for others rather made the text worse, and how some children succeeded in revising certain types of spelling errors but not others. While process data may not be the best screening tool for these ages yet, slow word writing may be a first warning, and a signal to educators to look out for and attempt to prevent more dysfluent writing processes. As shown by Afonso et al. ( 2020 ), Spanish children with dyslexia in the same age span as our participants, displayed similar patterns of slow word processing during handwriting. For a review of the relation between processes in handwriting and typing, see Feng et al. ( 2019 ). These types of measures can relatively easily be detected by means of keystroke logging or handwriting recordings. We suggest that researchers and educators alike, embrace qualitative analyses of individual cases, and use these types of information to gain valuable insights into the formative assessment (cf. Skar et al., 2022 ) of the writing processes of struggling students, to acquire knowledge of where and when bottle necks can occur and to foster more effective and targeted interventions. While these suggestions are language independent, we also encourage continued research on spelling processes and their relation to higher-level processes in different orthographies.

We did not test children’s intelligence but trusted the selection made by the schools.

which has been shown to correspond well with both split-half reliability and Cronhach’s alpha.

Afonso, O., Suárez-Coalla, P., & Cuetos, F. (2015). Spelling impairments in Spanish dyslexic adults. Frontiers in Psychology , 6 , 466. https://doi.org/10.3389/fpsyg.2015.00466

Article   Google Scholar  

Afonso, O., Suárez-Coalla, P., & Cuetos, F. (2020). Writing impairments in Spanish Children with Developmental Dyslexia. Journal of Learning Disabilities , 53 (2), 109–119. https://doi.org/10.1177/0022219419876255

Alamargot, D., Morin, M. F., & Simard-Dupuis, E. (2020). Handwriting Delay in Dyslexia: Children at the end of Primary School still make numerous short Pauses when producing letters. Journal of Learning Disabilities , 53 (3), 163–175. https://doi.org/10.1177/0022219420903705

Beers, S. F., Quinlan, T., & Harbaugh, A. G. (2010). Adolescent students’ reading during writing behaviors and relationships with text quality: An eyetracking study. Reading and Writing , 23 (7), 743–775. https://doi.org/10.1007/s11145-009-9193-7

Berman, R. A., & Verhoeven, L. (2002). Cross-linguistic perspectives on the development of text-production abilities: Speech and writing (Vol. 5, pp. 1–43). Written Language & Literacy. https://doi.org/10.1075/wll.5.1.02ber

Berninger, V. W., Vaughan, K., Abbott, R. D., Begay, K., Coleman, K. B., Curtin, G., Hawkins, J. M., & Graham, S. (2002). Teaching spelling and composition alone and together: Implications for the simple view of writing. Journal of Educational Psychology , 94 (2), 291–304. https://doi.org/10.1037//0022-0663.94.2.291

Berninger, V. W., Nielsen, K. H., Abbott, R. D., Wijsman, E., & Raskind, W. (2008). Writing problems in developmental dyslexia: Under-recognized and under-treated. Journal of School Psychology , 46 (1), 1–21. https://doi.org/10.1016/j.jsp.2006.11.008

Bogdanowicz, K. M., Łockiewicz, M., Bogdanowicz, M., & Pąchalska, M. (2014). Characteristics of cognitive deficits and writing skills of Polish adults with developmental dyslexia. International Journal of Psychophysiology , 93 (1), 78–83. https://doi.org/10.1016/j.ijpsycho.2013.03.005

Connelly, V., Campbell, S., MacLean, M., & Barnes, J. (2006). Contribution of lower order skills to the written composition of college students with and without Dyslexia. Developmental Neuropsychology , 29 (1), 175–196. https://doi.org/10.1207/s15326942dn2901_9

Dockrell, J. (2009). Causes of delays and difficulties in the production of written text. In R. Beard, D. Myhill, J. Riley, & M. Nystrand (Eds.), The SAGE handbook of writing development (pp. 487–505). SAGE. https://doi.org/10.4135/9780857021069.n34

Elwér, Å., Inger Fridolfsson, Stefan Samuelsson & Christina Wiklund 2011. LäSt: Test i läsning och stavning.

Feng, L., Lindner, A., Ji, X. R., & Joshi, R. M. (2019). The roles of handwriting and keyboarding in writing: A meta-analytic review. Reading and Writing , 32 (1), 33–63. https://doi.org/10.1007/s11145-017-9749-x

Figueredo, L., & Varnhagen, C. K. (2005). Didn’t you run the spell checker? Effects of type of spelling error and use of a spell checker on perceptions of the author. Reading Psychology , 26 (4–5), 441–458. https://doi.org/10.1080/02702710500400495

Galbraith, D., Baaijen, V., Smith-Spark, J., & Torrance, M. (2012). 06: The effects of Dyslexia on the writing processes of students in higher Education. In M. Torrance (Ed.), Learning to write effectively: Current trends in European research (pp. 195–198). Brill.

Graham, S. (2018). A revised writer(s)-within-community model of writing. Educational Psychologist , 53 (4), 1–22. https://doi.org/10.1080/00461520.2018.1481406

Gregg, N., Coleman, C., Davis, M., & Chalk, J. C. (2007). Timed essay writing. Journal of Learning Disabilities , 40 (4), 306–318. https://doi.org/10.1177/00222194070400040201

Hatcher, J., Snowling, M. J., & Griffiths, Y. M. (2002). Cognitive assessment of dyslexic students in higher education. British Journal of Educational Psychology , 72 (1), 119–133. https://doi.org/10.1348/000709902158801

Hayes, J. R., & Berninger, V. W. (2014). Cognitive processes in writing: A framework. In B. Arfé, J. Dockrell, & V. Berninger (Eds.), Writing development in children with hearing loss, Dyslexia, or oral Language problems: Implications for assessment and instruction (pp. 3–15). Oxford University Press.

Higgins, E. L., & Raskind, M. H. (1995). Compensatory effectiveness of speech recognition on the written composition performance of postsecondary students with learning disabilities. Learning Disability Quarterly , 18 (2), s. 159–174.

https://doi.org/10.1075/wll.5.1.02ber

Jeffreys, H. (1961). Theory of probability (3rd ed.). Oxford University Press.

Johansson, M. G. (1992). LS Klassdiagnoser i läsning och skrivning för högstadiet och gymnasiet . Psykologiförlaget.

Kemp, N., Parrila, R. K., & Kirby, J. R. (2009). Phonological and orthographic spelling in high-functioning adult dyslexics. Dyslexia , 15 (2), 105–128. https://doi.org/10.1002/dys.364

Kraft, S. (2023). Revisions in written composition: Introducing speech-to-text to children with reading and writing difficulties. Frontiers in Education , 8 , 1133930. https://doi.org/10.3389/feduc.2023.1133930

MacArthur, C. A., & Cavalier, A. (2004). Dictation and speech re-cognition technology as test accommodations. Exceptional Children , 71 (1), s. 43–58.

Martlewm, M. (1992). Handwriting and spelling: Dyslexic children’s abilities compared with children of the same chronological age and younger children of the same spelling level. British Journal of Educational Psychology , 62 (3), 375–390. https://doi.org/10.1111/j.2044-8279.1992.tb01030.x

McCarthy, P. M., & Jarvis, S. (2010). MTLD, vocd-D, and HD-D: A validation study of sophisticated approaches to lexical diversity assessment. Behavior Research Methods , 42 (2), 381–392. https://doi.org/10.3758/BRM.42.2.381

Melin, L. (2007). Var är det för fel på ett fel? Forskning och Framsteg , nr 1 , s52–55.

Google Scholar  

O’Rourke, L. (2020). Investigating the impact of spellcheck on writing for students with and without dyslexia (PhD thesis). Brookes University.

O’Rourke, L., Connelly, V., Barnett, A. L., & Afonso, O. (2020). Spellcheck has a positive impact on spelling accuracy and might improve lexical diversity in essays written by students with dyslexia. Journal of Writing Research , 12 (1), 35–61. https://doi.org/10.17239/jowr-2020.12.01.03

Quinlan, T. (2004). Speech recognition technology and students with writing difficulties: Improving fluency. Journal of Educational Psychology , 96 (2), 337–346. https://doi.org/10.1037/0022-0663.96.2.337

Rankin, J. L., Bruning, R. H., Timme, V. L., & Katkanant, C. (1993). Is writing affected by spelling performance and beliefs about spelling? Applied Cognitive Psychology , 7 (2), 155–169. https://doi.org/10.1002/acp.2350070207

Rankin, J. L., Bruning, R. H., & Timme, V. L. (1994). The development of beliefs about spelling and their relationship to spelling performance. Applied Cognitive Psychology , 8 , 213–232. https://doi.org/10.1002/acp.2350080303

Reynolds, L., & Wu, S. (2018, June). I’m never happy with what I write: Challenges and strategies of people with dyslexia on social media . In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 12, No. 1). https://doi.org/10.1609/icwsm.v12i1.15004

Rønneberg, V., Uppstad, T., H., Johansson, & Christer (2022). The process-disruption hypothesis: How spelling and typing skill affects written composition process and product. Psychological Research , 1 , 3–3. https://doi.org/10.1007/s00426-021-01625-z

Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology , 56 , 356–374.

Sénéchal, M., Gingras, M., & L’Heureux, L. (2016). Modeling spelling acquisition: The effect of orthographic regularities on silent-letter representations. Scientific Studies of Reading , 20 (2), 155–162. https://doi.org/10.1080/10888438.2015.1098650

Skar, G. B., Graham, S., & Rijlaarsdam, G. (2022). Formative writing assessment for change—Introduction to the special issue. Assessment in Education: Principles Policy & Practice , 29 (2), 121–126. https://doi.org/10.1080/0969594x.2022.2089488

Strömqvist, S., Holmqvist, K., Johansson, V., Karlsson, H., & Wengelin, A. (2006). What keystroke logging can reveal about writing. In K. Sullivan & E. Lindgren (Eds.), Computer keystroke logging and writing: Methods and applications (pp. 45–71). Elsevier.

Suárez-Coalla, P., Afonso, O., Martínez-García, C., & Cuetos, F. (2020). Dynamics of sentence handwriting in Dyslexia: The impact of frequency and consistency. Frontiers in Psychology , 11 , 319. https://doi.org/10.3389/fpsyg.2020.00319

Sumner, E., & Connelly, V. (2020). Writing and revision strategies of students with and without Dyslexia . Oxford Brookes University.

Sumner, E., Connelly, V., & Barnett, A. L. (2013). Children with dyslexia are slow writers because they pause more often and not because they are slow at handwriting execution. Reading and Writing , 26 (6), 991–1008. https://doi.org/10.1007/s11145-012-9403-6

Sumner, E., Connelly, V., & Barnett, A. L. (2014). The influence of spelling ability on handwriting production: Children with and without Dyslexia. Journal of Experimental Psychology: Learning Memory and Cognition , 40 (5), 1441–1447. https://doi.org/10.1037/a0035785

Sumner, E., Connelly, V., & Barnett, A. L. (2016). The influence of spelling ability on vocabulary choices when writing for children with Dyslexia. Journal of Learning Disabilities , 49 (3), 293–304. https://doi.org/10.1177/0022219414552018

Tomazin, M. O., Kraljević, J. K., & Alves, R. A. (2023). Reactivity of the triple task on writing processes and product in adults with dyslexia. Frontiers in Psychology , 14 , 1112274. https://doi.org/10.3389/fpsyg.2023.1112274

Tops, W., Callens, C., Cauwenberghe, E. V., Adriaens, J., & Brysbaert, M. (2013). Beyond spelling: The writing skills of students with dyslexia in higher education. Reading and Writing , 26 (5), 705–720. https://doi.org/10.1007/s11145-012-9387-2

Torrance, M., Rønneberg, V., Johansson, C., & Uppstad, P. H. (2016). Adolescent weak decoders writing in a shallow orthography: Process and product. Scientific Studies of Reading , 20 (5), 1–14. https://doi.org/10.1080/10888438.2016.1205071

Varnhagen, C. K. (2000). Shoot the messenger and disregard the message? Children’s attitudes toward spelling. Reading Psychology , 21 (2), 115–128. https://doi.org/10.1080/02702710050084446

Wengelin, Å. (2002). Text production in adults with reading and writing difficulties . Gothenburg Monographs of Linguistics 20. Department of Linguistics, University of Gothenburg.

Wengelin Å, & Strömqvist S. (2004). Text-writing development viewed through on-line pausing in Swedish. In Berman R. (Ed.), Language development across childhood and adolescence: Trends in language acquisition research (pp. 177–190). John Benjamins Publishing Company.

Wengelin, Å. (2007). The word-level focus in text production by adults with reading and writing difficulties. In L. M Torrance, Van Waes, & D. Galbraith (Eds.), Writing and cognition: Research and applications (pp. 67–82). Elsevier. https://doi.org/10.1163/9781849508223_006

Wengelin, Å., Johansson, R., & Johansson, V. (2014). Expressive writing in Swedish 15-year-olds with reading and writing difficulties. In B. Arfé, J. Dockrell, & V. Berninger (Eds.), Writing development and instruction in children with hearing, speech and oral language difficulties (pp. 244–256). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199827282.003.0018

Wengelin, Å., Frid, J., Johansson, R., & Johansson, V. (2019). Combining keystroke logging with other methods. Towards an experimental environment for writing process research. In E. Lindgren & K. Sullivan (Eds.), Observing writing: Insights from keystroke logging and handwriting (pp 30–99). Brill. https://doi.org/10.1163/9789004392526_003

Download references

Acknowledgements

This research was funded by the Swedish Research Council (VR-2009-02004), the Marcus and Amalia Wallenberg Foundation (Ref. No. 2014–0122), and Riksbankens Jubileumsfond (SAB20-0018_RJ). Thanks to Petter Åberg, Celia Wik Mergulhão and Ingrid Henriksson for contributing with text quality assessments.

Open access funding provided by University of Gothenburg.

Author information

Authors and affiliations.

Department of Swedish, Multilingualism, Language Technology, University of Gothenburg, Box 200, Göteborg, 405 30, Sweden

Åsa Wengelin

Department of Swedish, Linnaeus University, Växjö, 35195, Sweden

Sanna Kraft

Fredrik Thurfjell, Region Stockholm, Stockholm, Sweden

Fredrik Thurfjell

Department of Pedagogy and Learning, Linnaeus University, Växjö, 35195, Sweden

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Åsa Wengelin .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Wengelin, Å., Kraft, S., Thurfjell, F. et al. What can writing-process data add to the assessment of spelling difficulties?. Read Writ (2024). https://doi.org/10.1007/s11145-024-10524-9

Download citation

Accepted : 19 February 2024

Published : 22 April 2024

DOI : https://doi.org/10.1007/s11145-024-10524-9

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Spelling difficulty
• Writing difficulties
• Reading and writing difficultlies
• Writing processes
• Keystroke logging
• Struggling writers
• Spelling errors
• Find a journal
• Publish with us
• Track your research