research paper on teaching

• Tutorial Review
• Open access
• Published: 24 January 2018

Teaching the science of learning

• Yana Weinstein   ORCID: orcid.org/0000-0002-5144-968X 1 ,
• Christopher R. Madan 2 , 3 &
• Megan A. Sumeracki 4  

Cognitive Research: Principles and Implications volume  3 , Article number:  2 ( 2018 ) Cite this article

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The science of learning has made a considerable contribution to our understanding of effective teaching and learning strategies. However, few instructors outside of the field are privy to this research. In this tutorial review, we focus on six specific cognitive strategies that have received robust support from decades of research: spaced practice, interleaving, retrieval practice, elaboration, concrete examples, and dual coding. We describe the basic research behind each strategy and relevant applied research, present examples of existing and suggested implementation, and make recommendations for further research that would broaden the reach of these strategies.

Significance

Education does not currently adhere to the medical model of evidence-based practice (Roediger, 2013 ). However, over the past few decades, our field has made significant advances in applying cognitive processes to education. From this work, specific recommendations can be made for students to maximize their learning efficiency (Dunlosky, Rawson, Marsh, Nathan, & Willingham, 2013 ; Roediger, Finn, & Weinstein, 2012 ). In particular, a review published 10 years ago identified a limited number of study techniques that have received solid evidence from multiple replications testing their effectiveness in and out of the classroom (Pashler et al., 2007 ). A recent textbook analysis (Pomerance, Greenberg, & Walsh, 2016 ) took the six key learning strategies from this report by Pashler and colleagues, and found that very few teacher-training textbooks cover any of these six principles – and none cover them all, suggesting that these strategies are not systematically making their way into the classroom. This is the case in spite of multiple recent academic (e.g., Dunlosky et al., 2013 ) and general audience (e.g., Dunlosky, 2013 ) publications about these strategies. In this tutorial review, we present the basic science behind each of these six key principles, along with more recent research on their effectiveness in live classrooms, and suggest ideas for pedagogical implementation. The target audience of this review is (a) educators who might be interested in integrating the strategies into their teaching practice, (b) science of learning researchers who are looking for open questions to help determine future research priorities, and (c) researchers in other subfields who are interested in the ways that principles from cognitive psychology have been applied to education.

While the typical teacher may not be exposed to this research during teacher training, a small cohort of teachers intensely interested in cognitive psychology has recently emerged. These teachers are mainly based in the UK, and, anecdotally (e.g., Dennis (2016), personal communication), appear to have taken an interest in the science of learning after reading Make it Stick (Brown, Roediger, & McDaniel, 2014 ; see Clark ( 2016 ) for an enthusiastic review of this book on a teacher’s blog, and “Learning Scientists” ( 2016c ) for a collection). In addition, a grassroots teacher movement has led to the creation of “researchED” – a series of conferences on evidence-based education (researchED, 2013 ). The teachers who form part of this network frequently discuss cognitive psychology techniques and their applications to education on social media (mainly Twitter; e.g., Fordham, 2016 ; Penfound, 2016 ) and on their blogs, such as Evidence Into Practice ( https://evidenceintopractice.wordpress.com/ ), My Learning Journey ( http://reflectionsofmyteaching.blogspot.com/ ), and The Effortful Educator ( https://theeffortfuleducator.com/ ). In general, the teachers who write about these issues pay careful attention to the relevant literature, often citing some of the work described in this review.

These informal writings, while allowing teachers to explore their approach to teaching practice (Luehmann, 2008 ), give us a unique window into the application of the science of learning to the classroom. By examining these blogs, we can not only observe how basic cognitive research is being applied in the classroom by teachers who are reading it, but also how it is being misapplied, and what questions teachers may be posing that have gone unaddressed in the scientific literature. Throughout this review, we illustrate each strategy with examples of how it can be implemented (see Table  1 and Figs.  1 , 2 , 3 , 4 , 5 , 6 and 7 ), as well as with relevant teacher blog posts that reflect on its application, and draw upon this work to pin-point fruitful avenues for further basic and applied research.

Spaced practice schedule for one week. This schedule is designed to represent a typical timetable of a high-school student. The schedule includes four one-hour study sessions, one longer study session on the weekend, and one rest day. Notice that each subject is studied one day after it is covered in school, to create spacing between classes and study sessions. Copyright note: this image was produced by the authors

a Blocked practice and interleaved practice with fraction problems. In the blocked version, students answer four multiplication problems consecutively. In the interleaved version, students answer a multiplication problem followed by a division problem and then an addition problem, before returning to multiplication. For an experiment with a similar setup, see Patel et al. ( 2016 ). Copyright note: this image was produced by the authors. b Illustration of interleaving and spacing. Each color represents a different homework topic. Interleaving involves alternating between topics, rather than blocking. Spacing involves distributing practice over time, rather than massing. Interleaving inherently involves spacing as other tasks naturally “fill” the spaces between interleaved sessions. Copyright note: this image was produced by the authors, adapted from Rohrer ( 2012 )

Concept map illustrating the process and resulting benefits of retrieval practice. Retrieval practice involves the process of withdrawing learned information from long-term memory into working memory, which requires effort. This produces direct benefits via the consolidation of learned information, making it easier to remember later and causing improvements in memory, transfer, and inferences. Retrieval practice also produces indirect benefits of feedback to students and teachers, which in turn can lead to more effective study and teaching practices, with a focus on information that was not accurately retrieved. Copyright note: this figure originally appeared in a blog post by the first and third authors ( http://www.learningscientists.org/blog/2016/4/1-1 )

Illustration of “how” and “why” questions (i.e., elaborative interrogation questions) students might ask while studying the physics of flight. To help figure out how physics explains flight, students might ask themselves the following questions: “How does a plane take off?”; “Why does a plane need an engine?”; “How does the upward force (lift) work?”; “Why do the wings have a curved upper surface and a flat lower surface?”; and “Why is there a downwash behind the wings?”. Copyright note: the image of the plane was downloaded from Pixabay.com and is free to use, modify, and share

Three examples of physics problems that would be categorized differently by novices and experts. The problems in ( a ) and ( c ) look similar on the surface, so novices would group them together into one category. Experts, however, will recognize that the problems in ( b ) and ( c ) both relate to the principle of energy conservation, and so will group those two problems into one category instead. Copyright note: the figure was produced by the authors, based on figures in Chi et al. ( 1981 )

Example of how to enhance learning through use of a visual example. Students might view this visual representation of neural communications with the words provided, or they could draw a similar visual representation themselves. Copyright note: this figure was produced by the authors

Example of word properties associated with visual, verbal, and motor coding for the word “SPOON”. A word can evoke multiple types of representation (“codes” in dual coding theory). Viewing a word will automatically evoke verbal representations related to its component letters and phonemes. Words representing objects (i.e., concrete nouns) will also evoke visual representations, including information about similar objects, component parts of the object, and information about where the object is typically found. In some cases, additional codes can also be evoked, such as motor-related properties of the represented object, where contextual information related to the object’s functional intention and manipulation action may also be processed automatically when reading the word. Copyright note: this figure was produced by the authors and is based on Aylwin ( 1990 ; Fig.  2 ) and Madan and Singhal ( 2012a , Fig.  3 )

Spaced practice

The benefits of spaced (or distributed) practice to learning are arguably one of the strongest contributions that cognitive psychology has made to education (Kang, 2016 ). The effect is simple: the same amount of repeated studying of the same information spaced out over time will lead to greater retention of that information in the long run, compared with repeated studying of the same information for the same amount of time in one study session. The benefits of distributed practice were first empirically demonstrated in the 19 th century. As part of his extensive investigation into his own memory, Ebbinghaus ( 1885/1913 ) found that when he spaced out repetitions across 3 days, he could almost halve the number of repetitions necessary to relearn a series of 12 syllables in one day (Chapter 8). He thus concluded that “a suitable distribution of [repetitions] over a space of time is decidedly more advantageous than the massing of them at a single time” (Section 34). For those who want to read more about Ebbinghaus’s contribution to memory research, Roediger ( 1985 ) provides an excellent summary.

Since then, hundreds of studies have examined spacing effects both in the laboratory and in the classroom (Kang, 2016 ). Spaced practice appears to be particularly useful at large retention intervals: in the meta-analysis by Cepeda, Pashler, Vul, Wixted, and Rohrer ( 2006 ), all studies with a retention interval longer than a month showed a clear benefit of distributed practice. The “new theory of disuse” (Bjork & Bjork, 1992 ) provides a helpful mechanistic explanation for the benefits of spacing to learning. This theory posits that memories have both retrieval strength and storage strength. Whereas retrieval strength is thought to measure the ease with which a memory can be recalled at a given moment, storage strength (which cannot be measured directly) represents the extent to which a memory is truly embedded in the mind. When studying is taking place, both retrieval strength and storage strength receive a boost. However, the extent to which storage strength is boosted depends upon retrieval strength, and the relationship is negative: the greater the current retrieval strength, the smaller the gains in storage strength. Thus, the information learned through “cramming” will be rapidly forgotten due to high retrieval strength and low storage strength (Bjork & Bjork, 2011 ), whereas spacing out learning increases storage strength by allowing retrieval strength to wane before restudy.

Teachers can introduce spacing to their students in two broad ways. One involves creating opportunities to revisit information throughout the semester, or even in future semesters. This does involve some up-front planning, and can be difficult to achieve, given time constraints and the need to cover a set curriculum. However, spacing can be achieved with no great costs if teachers set aside a few minutes per class to review information from previous lessons. The second method involves putting the onus to space on the students themselves. Of course, this would work best with older students – high school and above. Because spacing requires advance planning, it is crucial that the teacher helps students plan their studying. For example, teachers could suggest that students schedule study sessions on days that alternate with the days on which a particular class meets (e.g., schedule review sessions for Tuesday and Thursday when the class meets Monday and Wednesday; see Fig.  1 for a more complete weekly spaced practice schedule). It important to note that the spacing effect refers to information that is repeated multiple times, rather than the idea of studying different material in one long session versus spaced out in small study sessions over time. However, for teachers and particularly for students planning a study schedule, the subtle difference between the two situations (spacing out restudy opportunities, versus spacing out studying of different information over time) may be lost. Future research should address the effects of spacing out studying of different information over time, whether the same considerations apply in this situation as compared to spacing out restudy opportunities, and how important it is for teachers and students to understand the difference between these two types of spaced practice.

It is important to note that students may feel less confident when they space their learning (Bjork, 1999 ) than when they cram. This is because spaced learning is harder – but it is this “desirable difficulty” that helps learning in the long term (Bjork, 1994 ). Students tend to cram for exams rather than space out their learning. One explanation for this is that cramming does “work”, if the goal is only to pass an exam. In order to change students’ minds about how they schedule their studying, it might be important to emphasize the value of retaining information beyond a final exam in one course.

Ideas for how to apply spaced practice in teaching have appeared in numerous teacher blogs (e.g., Fawcett, 2013 ; Kraft, 2015 ; Picciotto, 2009 ). In England in particular, as of 2013, high-school students need to be able to remember content from up to 3 years back on cumulative exams (General Certificate of Secondary Education (GCSE) and A-level exams; see CIFE, 2012 ). A-levels in particular determine what subject students study in university and which programs they are accepted into, and thus shape the path of their academic career. A common approach for dealing with these exams has been to include a “revision” (i.e., studying or cramming) period of a few weeks leading up to the high-stakes cumulative exams. Now, teachers who follow cognitive psychology are advocating a shift of priorities to spacing learning over time across the 3 years, rather than teaching a topic once and then intensely reviewing it weeks before the exam (Cox, 2016a ; Wood, 2017 ). For example, some teachers have suggested using homework assignments as an opportunity for spaced practice by giving students homework on previous topics (Rose, 2014 ). However, questions remain, such as whether spaced practice can ever be effective enough to completely alleviate the need or utility of a cramming period (Cox, 2016b ), and how one can possibly figure out the optimal lag for spacing (Benney, 2016 ; Firth, 2016 ).

There has been considerable research on the question of optimal lag, and much of it is quite complex; two sessions neither too close together (i.e., cramming) nor too far apart are ideal for retention. In a large-scale study, Cepeda, Vul, Rohrer, Wixted, and Pashler ( 2008 ) examined the effects of the gap between study sessions and the interval between study and test across long periods, and found that the optimal gap between study sessions was contingent on the retention interval. Thus, it is not clear how teachers can apply the complex findings on lag to their own classrooms.

A useful avenue of research would be to simplify the research paradigms that are used to study optimal lag, with the goal of creating a flexible, spaced-practice framework that teachers could apply and tailor to their own teaching needs. For example, an Excel macro spreadsheet was recently produced to help teachers plan for lagged lessons (Weinstein-Jones & Weinstein, 2017 ; see Weinstein & Weinstein-Jones ( 2017 ) for a description of the algorithm used in the spreadsheet), and has been used by teachers to plan their lessons (Penfound, 2017 ). However, one teacher who found this tool helpful also wondered whether the more sophisticated plan was any better than his own method of manually selecting poorly understood material from previous classes for later review (Lovell, 2017 ). This direction is being actively explored within personalized online learning environments (Kornell & Finn, 2016 ; Lindsey, Shroyer, Pashler, & Mozer, 2014 ), but teachers in physical classrooms might need less technologically-driven solutions to teach cohorts of students.

It seems teachers would greatly appreciate a set of guidelines for how to implement spacing in the curriculum in the most effective, but also the most efficient manner. While the cognitive field has made great advances in terms of understanding the mechanisms behind spacing, what teachers need more of are concrete evidence-based tools and guidelines for direct implementation in the classroom. These could include more sophisticated and experimentally tested versions of the software described above (Weinstein-Jones & Weinstein, 2017 ), or adaptable templates of spaced curricula. Moreover, researchers need to evaluate the effectiveness of these tools in a real classroom environment, over a semester or academic year, in order to give pedagogically relevant evidence-based recommendations to teachers.

Interleaving

Another scheduling technique that has been shown to increase learning is interleaving. Interleaving occurs when different ideas or problem types are tackled in a sequence, as opposed to the more common method of attempting multiple versions of the same problem in a given study session (known as blocking). Interleaving as a principle can be applied in many different ways. One such way involves interleaving different types of problems during learning, which is particularly applicable to subjects such as math and physics (see Fig.  2 a for an example with fractions, based on a study by Patel, Liu, & Koedinger, 2016 ). For example, in a study with college students, Rohrer and Taylor ( 2007 ) found that shuffling math problems that involved calculating the volume of different shapes resulted in better test performance 1 week later than when students answered multiple problems about the same type of shape in a row. This pattern of results has also been replicated with younger students, for example 7 th grade students learning to solve graph and slope problems (Rohrer, Dedrick, & Stershic, 2015 ). The proposed explanation for the benefit of interleaving is that switching between different problem types allows students to acquire the ability to choose the right method for solving different types of problems rather than learning only the method itself, and not when to apply it.

Do the benefits of interleaving extend beyond problem solving? The answer appears to be yes. Interleaving can be helpful in other situations that require discrimination, such as inductive learning. Kornell and Bjork ( 2008 ) examined the effects of interleaving in a task that might be pertinent to a student of the history of art: the ability to match paintings to their respective painters. Students who studied different painters’ paintings interleaved at study were more successful on a later identification test than were participants who studied the paintings blocked by painter. Birnbaum, Kornell, Bjork, and Bjork ( 2013 ) proposed the discriminative-contrast hypothesis to explain that interleaving enhances learning by allowing the comparison between exemplars of different categories. They found support for this hypothesis in a set of experiments with bird categorization: participants benefited from interleaving and also from spacing, but not when the spacing interrupted side-by-side comparisons of birds from different categories.

Another type of interleaving involves the interleaving of study and test opportunities. This type of interleaving has been applied, once again, to problem solving, whereby students alternate between attempting a problem and viewing a worked example (Trafton & Reiser, 1993 ); this pattern appears to be superior to answering a string of problems in a row, at least with respect to the amount of time it takes to achieve mastery of a procedure (Corbett, Reed, Hoffmann, MacLaren, & Wagner, 2010 ). The benefits of interleaving study and test opportunities – rather than blocking study followed by attempting to answer problems or questions – might arise due to a process known as “test-potentiated learning”. That is, a study opportunity that immediately follows a retrieval attempt may be more fruitful than when that same studying was not preceded by retrieval (Arnold & McDermott, 2013 ).

For problem-based subjects, the interleaving technique is straightforward: simply mix questions on homework and quizzes with previous materials (which takes care of spacing as well); for languages, mix vocabulary themes rather than blocking by theme (Thomson & Mehring, 2016 ). But interleaving as an educational strategy ought to be presented to teachers with some caveats. Research has focused on interleaving material that is somewhat related (e.g., solving different mathematical equations, Rohrer et al., 2015 ), whereas students sometimes ask whether they should interleave material from different subjects – a practice that has not received empirical support (Hausman & Kornell, 2014 ). When advising students how to study independently, teachers should thus proceed with caution. Since it is easy for younger students to confuse this type of unhelpful interleaving with the more helpful interleaving of related information, it may be best for teachers of younger grades to create opportunities for interleaving in homework and quiz assignments rather than putting the onus on the students themselves to make use of the technique. Technology can be very helpful here, with apps such as Quizlet, Memrise, Anki, Synap, Quiz Champ, and many others (see also “Learning Scientists”, 2017 ) that not only allow instructor-created quizzes to be taken by students, but also provide built-in interleaving algorithms so that the burden does not fall on the teacher or the student to carefully plan which items are interleaved when.

An important point to consider is that in educational practice, the distinction between spacing and interleaving can be difficult to delineate. The gap between the scientific and classroom definitions of interleaving is demonstrated by teachers’ own writings about this technique. When they write about interleaving, teachers often extend the term to connote a curriculum that involves returning to topics multiple times throughout the year (e.g., Kirby, 2014 ; see “Learning Scientists” ( 2016a ) for a collection of similar blog posts by several other teachers). The “interleaving” of topics throughout the curriculum produces an effect that is more akin to what cognitive psychologists call “spacing” (see Fig.  2 b for a visual representation of the difference between interleaving and spacing). However, cognitive psychologists have not examined the effects of structuring the curriculum in this way, and open questions remain: does repeatedly circling back to previous topics throughout the semester interrupt the learning of new information? What are some effective techniques for interleaving old and new information within one class? And how does one determine the balance between old and new information?

Retrieval practice

While tests are most often used in educational settings for assessment, a lesser-known benefit of tests is that they actually improve memory of the tested information. If we think of our memories as libraries of information, then it may seem surprising that retrieval (which happens when we take a test) improves memory; however, we know from a century of research that retrieving knowledge actually strengthens it (see Karpicke, Lehman, & Aue, 2014 ). Testing was shown to strengthen memory as early as 100 years ago (Gates, 1917 ), and there has been a surge of research in the last decade on the mnemonic benefits of testing, or retrieval practice . Most of the research on the effectiveness of retrieval practice has been done with college students (see Roediger & Karpicke, 2006 ; Roediger, Putnam, & Smith, 2011 ), but retrieval-based learning has been shown to be effective at producing learning for a wide range of ages, including preschoolers (Fritz, Morris, Nolan, & Singleton, 2007 ), elementary-aged children (e.g., Karpicke, Blunt, & Smith, 2016 ; Karpicke, Blunt, Smith, & Karpicke, 2014 ; Lipko-Speed, Dunlosky, & Rawson, 2014 ; Marsh, Fazio, & Goswick, 2012 ; Ritchie, Della Sala, & McIntosh, 2013 ), middle-school students (e.g., McDaniel, Thomas, Agarwal, McDermott, & Roediger, 2013 ; McDermott, Agarwal, D’Antonio, Roediger, & McDaniel, 2014 ), and high-school students (e.g., McDermott et al., 2014 ). In addition, the effectiveness of retrieval-based learning has been extended beyond simple testing to other activities in which retrieval practice can be integrated, such as concept mapping (Blunt & Karpicke, 2014 ; Karpicke, Blunt, et al., 2014 ; Ritchie et al., 2013 ).

A debate is currently ongoing as to the effectiveness of retrieval practice for more complex materials (Karpicke & Aue, 2015 ; Roelle & Berthold, 2017 ; Van Gog & Sweller, 2015 ). Practicing retrieval has been shown to improve the application of knowledge to new situations (e.g., Butler, 2010 ; Dirkx, Kester, & Kirschner, 2014 ); McDaniel et al., 2013 ; Smith, Blunt, Whiffen, & Karpicke, 2016 ); but see Tran, Rohrer, and Pashler ( 2015 ) and Wooldridge, Bugg, McDaniel, and Liu ( 2014 ), for retrieval practice studies that showed limited or no increased transfer compared to restudy. Retrieval practice effects on higher-order learning may be more sensitive than fact learning to encoding factors, such as the way material is presented during study (Eglington & Kang, 2016 ). In addition, retrieval practice may be more beneficial for higher-order learning if it includes more scaffolding (Fiechter & Benjamin, 2017 ; but see Smith, Blunt, et al., 2016 ) and targeted practice with application questions (Son & Rivas, 2016 ).

How does retrieval practice help memory? Figure  3 illustrates both the direct and indirect benefits of retrieval practice identified by the literature. The act of retrieval itself is thought to strengthen memory (Karpicke, Blunt, et al., 2014 ; Roediger & Karpicke, 2006 ; Smith, Roediger, & Karpicke, 2013 ). For example, Smith et al. ( 2013 ) showed that if students brought information to mind without actually producing it (covert retrieval), they remembered the information just as well as if they overtly produced the retrieved information (overt retrieval). Importantly, both overt and covert retrieval practice improved memory over control groups without retrieval practice, even when feedback was not provided. The fact that bringing information to mind in the absence of feedback or restudy opportunities improves memory leads researchers to conclude that it is the act of retrieval – thinking back to bring information to mind – that improves memory of that information.

The benefit of retrieval practice depends to a certain extent on successful retrieval (see Karpicke, Lehman, et al., 2014 ). For example, in Experiment 4 of Smith et al. ( 2013 ), students successfully retrieved 72% of the information during retrieval practice. Of course, retrieving 72% of the information was compared to a restudy control group, during which students were re-exposed to 100% of the information, creating a bias in favor of the restudy condition. Yet retrieval led to superior memory later compared to the restudy control. However, if retrieval success is extremely low, then it is unlikely to improve memory (e.g., Karpicke, Blunt, et al., 2014 ), particularly in the absence of feedback. On the other hand, if retrieval-based learning situations are constructed in such a way that ensures high levels of success, the act of bringing the information to mind may be undermined, thus making it less beneficial. For example, if a student reads a sentence and then immediately covers the sentence and recites it out loud, they are likely not retrieving the information but rather just keeping the information in their working memory long enough to recite it again (see Smith, Blunt, et al., 2016 for a discussion of this point). Thus, it is important to balance success of retrieval with overall difficulty in retrieving the information (Smith & Karpicke, 2014 ; Weinstein, Nunes, & Karpicke, 2016 ). If initial retrieval success is low, then feedback can help improve the overall benefit of practicing retrieval (Kang, McDermott, & Roediger, 2007 ; Smith & Karpicke, 2014 ). Kornell, Klein, and Rawson ( 2015 ), however, found that it was the retrieval attempt and not the correct production of information that produced the retrieval practice benefit – as long as the correct answer was provided after an unsuccessful attempt, the benefit was the same as for a successful retrieval attempt in this set of studies. From a practical perspective, it would be helpful for teachers to know when retrieval attempts in the absence of success are helpful, and when they are not. There may also be additional reasons beyond retrieval benefits that would push teachers towards retrieval practice activities that produce some success amongst students; for example, teachers may hesitate to give students retrieval practice exercises that are too difficult, as this may negatively affect self-efficacy and confidence.

In addition to the fact that bringing information to mind directly improves memory for that information, engaging in retrieval practice can produce indirect benefits as well (see Roediger et al., 2011 ). For example, research by Weinstein, Gilmore, Szpunar, and McDermott ( 2014 ) demonstrated that when students expected to be tested, the increased test expectancy led to better-quality encoding of new information. Frequent testing can also serve to decrease mind-wandering – that is, thoughts that are unrelated to the material that students are supposed to be studying (Szpunar, Khan, & Schacter, 2013 ).

Practicing retrieval is a powerful way to improve meaningful learning of information, and it is relatively easy to implement in the classroom. For example, requiring students to practice retrieval can be as simple as asking students to put their class materials away and try to write out everything they know about a topic. Retrieval-based learning strategies are also flexible. Instructors can give students practice tests (e.g., short-answer or multiple-choice, see Smith & Karpicke, 2014 ), provide open-ended prompts for the students to recall information (e.g., Smith, Blunt, et al., 2016 ) or ask their students to create concept maps from memory (e.g., Blunt & Karpicke, 2014 ). In one study, Weinstein et al. ( 2016 ) looked at the effectiveness of inserting simple short-answer questions into online learning modules to see whether they improved student performance. Weinstein and colleagues also manipulated the placement of the questions. For some students, the questions were interspersed throughout the module, and for other students the questions were all presented at the end of the module. Initial success on the short-answer questions was higher when the questions were interspersed throughout the module. However, on a later test of learning from that module, the original placement of the questions in the module did not matter for performance. As with spaced practice, where the optimal gap between study sessions is contingent on the retention interval, the optimum difficulty and level of success during retrieval practice may also depend on the retention interval. Both groups of students who answered questions performed better on the delayed test compared to a control group without question opportunities during the module. Thus, the important thing is for instructors to provide opportunities for retrieval practice during learning. Based on previous research, any activity that promotes the successful retrieval of information should improve learning.

Retrieval practice has received a lot of attention in teacher blogs (see “Learning Scientists” ( 2016b ) for a collection). A common theme seems to be an emphasis on low-stakes (Young, 2016 ) and even no-stakes (Cox, 2015 ) testing, the goal of which is to increase learning rather than assess performance. In fact, one well-known charter school in the UK has an official homework policy grounded in retrieval practice: students are to test themselves on subject knowledge for 30 minutes every day in lieu of standard homework (Michaela Community School, 2014 ). The utility of homework, particularly for younger children, is often a hotly debated topic outside of academia (e.g., Shumaker, 2016 ; but see Jones ( 2016 ) for an opposing viewpoint and Cooper ( 1989 ) for the original research the blog posts were based on). Whereas some research shows clear links between homework and academic achievement (Valle et al., 2016 ), other researchers have questioned the effectiveness of homework (Dettmers, Trautwein, & Lüdtke, 2009 ). Perhaps amending homework to involve retrieval practice might make it more effective; this remains an open empirical question.

One final consideration is that of test anxiety. While retrieval practice can be very powerful at improving memory, some research shows that pressure during retrieval can undermine some of the learning benefit. For example, Hinze and Rapp ( 2014 ) manipulated pressure during quizzing to create high-pressure and low-pressure conditions. On the quizzes themselves, students performed equally well. However, those in the high-pressure condition did not perform as well on a criterion test later compared to the low-pressure group. Thus, test anxiety may reduce the learning benefit of retrieval practice. Eliminating all high-pressure tests is probably not possible, but instructors can provide a number of low-stakes retrieval opportunities for students to help increase learning. The use of low-stakes testing can serve to decrease test anxiety (Khanna, 2015 ), and has recently been shown to negate the detrimental impact of stress on learning (Smith, Floerke, & Thomas, 2016 ). This is a particularly important line of inquiry to pursue for future research, because many teachers who are not familiar with the effectiveness of retrieval practice may be put off by the implied pressure of “testing”, which evokes the much maligned high-stakes standardized tests (e.g., McHugh, 2013 ).

Elaboration

Elaboration involves connecting new information to pre-existing knowledge. Anderson ( 1983 , p.285) made the following claim about elaboration: “One of the most potent manipulations that can be performed in terms of increasing a subject’s memory for material is to have the subject elaborate on the to-be-remembered material.” Postman ( 1976 , p. 28) defined elaboration most parsimoniously as “additions to nominal input”, and Hirshman ( 2001 , p. 4369) provided an elaboration on this definition (pun intended!), defining elaboration as “A conscious, intentional process that associates to-be-remembered information with other information in memory.” However, in practice, elaboration could mean many different things. The common thread in all the definitions is that elaboration involves adding features to an existing memory.

One possible instantiation of elaboration is thinking about information on a deeper level. The levels (or “depth”) of processing framework, proposed by Craik and Lockhart ( 1972 ), predicts that information will be remembered better if it is processed more deeply in terms of meaning, rather than shallowly in terms of form. The leves of processing framework has, however, received a number of criticisms (Craik, 2002 ). One major problem with this framework is that it is difficult to measure “depth”. And if we are not able to actually measure depth, then the argument can become circular: is it that something was remembered better because it was studied more deeply, or do we conclude that it must have been studied more deeply because it is remembered better? (See Lockhart & Craik, 1990 , for further discussion of this issue).

Another mechanism by which elaboration can confer a benefit to learning is via improvement in organization (Bellezza, Cheesman, & Reddy, 1977 ; Mandler, 1979 ). By this view, elaboration involves making information more integrated and organized with existing knowledge structures. By connecting and integrating the to-be-learned information with other concepts in memory, students can increase the extent to which the ideas are organized in their minds, and this increased organization presumably facilitates the reconstruction of the past at the time of retrieval.

Elaboration is such a broad term and can include so many different techniques that it is hard to claim that elaboration will always help learning. There is, however, a specific technique under the umbrella of elaboration for which there is relatively strong evidence in terms of effectiveness (Dunlosky et al., 2013 ; Pashler et al., 2007 ). This technique is called elaborative interrogation, and involves students questioning the materials that they are studying (Pressley, McDaniel, Turnure, Wood, & Ahmad, 1987 ). More specifically, students using this technique would ask “how” and “why” questions about the concepts they are studying (see Fig.  4 for an example on the physics of flight). Then, crucially, students would try to answer these questions – either from their materials or, eventually, from memory (McDaniel & Donnelly, 1996 ). The process of figuring out the answer to the questions – with some amount of uncertainty (Overoye & Storm, 2015 ) – can help learning. When using this technique, however, it is important that students check their answers with their materials or with the teacher; when the content generated through elaborative interrogation is poor, it can actually hurt learning (Clinton, Alibali, & Nathan, 2016 ).

Students can also be encouraged to self-explain concepts to themselves while learning (Chi, De Leeuw, Chiu, & LaVancher, 1994 ). This might involve students simply saying out loud what steps they need to perform to solve an equation. Aleven and Koedinger ( 2002 ) conducted two classroom studies in which students were either prompted by a “cognitive tutor” to provide self-explanations during a problem-solving task or not, and found that the self-explanations led to improved performance. According to the authors, this approach could scale well to real classrooms. If possible and relevant, students could even perform actions alongside their self-explanations (Cohen, 1981 ; see also the enactment effect, Hainselin, Picard, Manolli, Vankerkore-Candas, & Bourdin, 2017 ). Instructors can scaffold students in these types of activities by providing self-explanation prompts throughout to-be-learned material (O’Neil et al., 2014 ). Ultimately, the greatest potential benefit of accurate self-explanation or elaboration is that the student will be able to transfer their knowledge to a new situation (Rittle-Johnson, 2006 ).

The technical term “elaborative interrogation” has not made it into the vernacular of educational bloggers (a search on https://educationechochamberuncut.wordpress.com , which consolidates over 3,000 UK-based teacher blogs, yielded zero results for that term). However, a few teachers have blogged about elaboration more generally (e.g., Hobbiss, 2016 ) and deep questioning specifically (e.g., Class Teaching, 2013 ), just without using the specific terminology. This strategy in particular may benefit from a more open dialog between researchers and teachers to facilitate the use of elaborative interrogation in the classroom and to address possible barriers to implementation. In terms of advancing the scientific understanding of elaborative interrogation in a classroom setting, it would be informative to conduct a larger-scale intervention to see whether having students elaborate during reading actually helps their understanding. It would also be useful to know whether the students really need to generate their own elaborative interrogation (“how” and “why”) questions, versus answering questions provided by others. How long should students persist to find the answers? When is the right time to have students engage in this task, given the levels of expertise required to do it well (Clinton et al., 2016 )? Without knowing the answers to these questions, it may be too early for us to instruct teachers to use this technique in their classes. Finally, elaborative interrogation takes a long time. Is this time efficiently spent? Or, would it be better to have the students try to answer a few questions, pool their information as a class, and then move to practicing retrieval of the information?

Concrete examples

Providing supporting information can improve the learning of key ideas and concepts. Specifically, using concrete examples to supplement content that is more conceptual in nature can make the ideas easier to understand and remember. Concrete examples can provide several advantages to the learning process: (a) they can concisely convey information, (b) they can provide students with more concrete information that is easier to remember, and (c) they can take advantage of the superior memorability of pictures relative to words (see “Dual Coding”).

Words that are more concrete are both recognized and recalled better than abstract words (Gorman, 1961 ; e.g., “button” and “bound,” respectively). Furthermore, it has been demonstrated that information that is more concrete and imageable enhances the learning of associations, even with abstract content (Caplan & Madan, 2016 ; Madan, Glaholt, & Caplan, 2010 ; Paivio, 1971 ). Following from this, providing concrete examples during instruction should improve retention of related abstract concepts, rather than the concrete examples alone being remembered better. Concrete examples can be useful both during instruction and during practice problems. Having students actively explain how two examples are similar and encouraging them to extract the underlying structure on their own can also help with transfer. In a laboratory study, Berry ( 1983 ) demonstrated that students performed well when given concrete practice problems, regardless of the use of verbalization (akin to elaborative interrogation), but that verbalization helped students transfer understanding from concrete to abstract problems. One particularly important area of future research is determining how students can best make the link between concrete examples and abstract ideas.

Since abstract concepts are harder to grasp than concrete information (Paivio, Walsh, & Bons, 1994 ), it follows that teachers ought to illustrate abstract ideas with concrete examples. However, care must be taken when selecting the examples. LeFevre and Dixon ( 1986 ) provided students with both concrete examples and abstract instructions and found that when these were inconsistent, students followed the concrete examples rather than the abstract instructions, potentially constraining the application of the abstract concept being taught. Lew, Fukawa-Connelly, Mejí-Ramos, and Weber ( 2016 ) used an interview approach to examine why students may have difficulty understanding a lecture. Responses indicated that some issues were related to understanding the overarching topic rather than the component parts, and to the use of informal colloquialisms that did not clearly follow from the material being taught. Both of these issues could have potentially been addressed through the inclusion of a greater number of relevant concrete examples.

One concern with using concrete examples is that students might only remember the examples – especially if they are particularly memorable, such as fun or gimmicky examples – and will not be able to transfer their understanding from one example to another, or more broadly to the abstract concept. However, there does not seem to be any evidence that fun relevant examples actually hurt learning by harming memory for important information. Instead, fun examples and jokes tend to be more memorable, but this boost in memory for the joke does not seem to come at a cost to memory for the underlying concept (Baldassari & Kelley, 2012 ). However, two important caveats need to be highlighted. First, to the extent that the more memorable content is not relevant to the concepts of interest, learning of the target information can be compromised (Harp & Mayer, 1998 ). Thus, care must be taken to ensure that all examples and gimmicks are, in fact, related to the core concepts that the students need to acquire, and do not contain irrelevant perceptual features (Kaminski & Sloutsky, 2013 ).

The second issue is that novices often notice and remember the surface details of an example rather than the underlying structure. Experts, on the other hand, can extract the underlying structure from examples that have divergent surface features (Chi, Feltovich, & Glaser, 1981 ; see Fig.  5 for an example from physics). Gick and Holyoak ( 1983 ) tried to get students to apply a rule from one problem to another problem that appeared different on the surface, but was structurally similar. They found that providing multiple examples helped with this transfer process compared to only using one example – especially when the examples provided had different surface details. More work is also needed to determine how many examples are sufficient for generalization to occur (and this, of course, will vary with contextual factors and individual differences). Further research on the continuum between concrete/specific examples and more abstract concepts would also be informative. That is, if an example is not concrete enough, it may be too difficult to understand. On the other hand, if the example is too concrete, that could be detrimental to generalization to the more abstract concept (although a diverse set of very concrete examples may be able to help with this). In fact, in a controversial article, Kaminski, Sloutsky, and Heckler ( 2008 ) claimed that abstract examples were more effective than concrete examples. Later rebuttals of this paper contested whether the abstract versus concrete distinction was clearly defined in the original study (see Reed, 2008 , for a collection of letters on the subject). This ideal point along the concrete-abstract continuum might also interact with development.

Finding teacher blog posts on concrete examples proved to be more difficult than for the other strategies in this review. One optimistic possibility is that teachers frequently use concrete examples in their teaching, and thus do not think of this as a specific contribution from cognitive psychology; the one blog post we were able to find that discussed concrete examples suggests that this might be the case (Boulton, 2016 ). The idea of “linking abstract concepts with concrete examples” is also covered in 25% of teacher-training textbooks used in the US, according to the report by Pomerance et al. ( 2016 ); this is the second most frequently covered of the six strategies, after “posing probing questions” (i.e., elaborative interrogation). A useful direction for future research would be to establish how teachers are using concrete examples in their practice, and whether we can make any suggestions for improvement based on research into the science of learning. For example, if two examples are better than one (Bauernschmidt, 2017 ), are additional examples also needed, or are there diminishing returns from providing more examples? And, how can teachers best ensure that concrete examples are consistent with prior knowledge (Reed, 2008 )?

Dual coding

Both the memory literature and folk psychology support the notion of visual examples being beneficial—the adage of “a picture is worth a thousand words” (traced back to an advertising slogan from the 1920s; Meider, 1990 ). Indeed, it is well-understood that more information can be conveyed through a simple illustration than through several paragraphs of text (e.g., Barker & Manji, 1989 ; Mayer & Gallini, 1990 ). Illustrations can be particularly helpful when the described concept involves several parts or steps and is intended for individuals with low prior knowledge (Eitel & Scheiter, 2015 ; Mayer & Gallini, 1990 ). Figure  6 provides a concrete example of this, illustrating how information can flow through neurons and synapses.

In addition to being able to convey information more succinctly, pictures are also more memorable than words (Paivio & Csapo, 1969 , 1973 ). In the memory literature, this is referred to as the picture superiority effect , and dual coding theory was developed in part to explain this effect. Dual coding follows from the notion of text being accompanied by complementary visual information to enhance learning. Paivio ( 1971 , 1986 ) proposed dual coding theory as a mechanistic account for the integration of multiple information “codes” to process information. In this theory, a code corresponds to a modal or otherwise distinct representation of a concept—e.g., “mental images for ‘book’ have visual, tactual, and other perceptual qualities similar to those evoked by the referent objects on which the images are based” (Clark & Paivio, 1991 , p. 152). Aylwin ( 1990 ) provides a clear example of how the word “dog” can evoke verbal, visual, and enactive representations (see Fig.  7 for a similar example for the word “SPOON”, based on Aylwin, 1990 (Fig.  2 ) and Madan & Singhal, 2012a (Fig.  3 )). Codes can also correspond to emotional properties (Clark & Paivio, 1991 ; Paivio, 2013 ). Clark and Paivio ( 1991 ) provide a thorough review of dual coding theory and its relation to education, while Paivio ( 2007 ) provides a comprehensive treatise on dual coding theory. Broadly, dual coding theory suggests that providing multiple representations of the same information enhances learning and memory, and that information that more readily evokes additional representations (through automatic imagery processes) receives a similar benefit.

Paivio and Csapo ( 1973 ) suggest that verbal and imaginal codes have independent and additive effects on memory recall. Using visuals to improve learning and memory has been particularly applied to vocabulary learning (Danan, 1992 ; Sadoski, 2005 ), but has also shown success in other domains such as in health care (Hartland, Biddle, & Fallacaro, 2008 ). To take advantage of dual coding, verbal information should be accompanied by a visual representation when possible. However, while the studies discussed all indicate that the use of multiple representations of information is favorable, it is important to acknowledge that each representation also increases cognitive load and can lead to over-saturation (Mayer & Moreno, 2003 ).

Given that pictures are generally remembered better than words, it is important to ensure that the pictures students are provided with are helpful and relevant to the content they are expected to learn. McNeill, Uttal, Jarvin, and Sternberg ( 2009 ) found that providing visual examples decreased conceptual errors. However, McNeill et al. also found that when students were given visually rich examples, they performed more poorly than students who were not given any visual example, suggesting that the visual details can at times become a distraction and hinder performance. Thus, it is important to consider that images used in teaching are clear and not ambiguous in their meaning (Schwartz, 2007 ).

Further broadening the scope of dual coding theory, Engelkamp and Zimmer ( 1984 ) suggest that motor movements, such as “turning the handle,” can provide an additional motor code that can improve memory, linking studies of motor actions (enactment) with dual coding theory (Clark & Paivio, 1991 ; Engelkamp & Cohen, 1991 ; Madan & Singhal, 2012c ). Indeed, enactment effects appear to primarily occur during learning, rather than during retrieval (Peterson & Mulligan, 2010 ). Along similar lines, Wammes, Meade, and Fernandes ( 2016 ) demonstrated that generating drawings can provide memory benefits beyond what could otherwise be explained by visual imagery, picture superiority, and other memory enhancing effects. Providing convergent evidence, even when overt motor actions are not critical in themselves, words representing functional objects have been shown to enhance later memory (Madan & Singhal, 2012b ; Montefinese, Ambrosini, Fairfield, & Mammarella, 2013 ). This indicates that motoric processes can improve memory similarly to visual imagery, similar to memory differences for concrete vs. abstract words. Further research suggests that automatic motor simulation for functional objects is likely responsible for this memory benefit (Madan, Chen, & Singhal, 2016 ).

When teachers combine visuals and words in their educational practice, however, they may not always be taking advantage of dual coding – at least, not in the optimal manner. For example, a recent discussion on Twitter centered around one teacher’s decision to have 7 th Grade students replace certain words in their science laboratory report with a picture of that word (e.g., the instructions read “using a syringe …” and a picture of a syringe replaced the word; Turner, 2016a ). Other teachers argued that this was not dual coding (Beaven, 2016 ; Williams, 2016 ), because there were no longer two different representations of the information. The first teacher maintained that dual coding was preserved, because this laboratory report with pictures was to be used alongside the original, fully verbal report (Turner, 2016b ). This particular implementation – having students replace individual words with pictures – has not been examined in the cognitive literature, presumably because no benefit would be expected. In any case, we need to be clearer about implementations for dual coding, and more research is needed to clarify how teachers can make use of the benefits conferred by multiple representations and picture superiority.

Critically, dual coding theory is distinct from the notion of “learning styles,” which describe the idea that individuals benefit from instruction that matches their modality preference. While this idea is pervasive and individuals often subjectively feel that they have a preference, evidence indicates that the learning styles theory is not supported by empirical findings (e.g., Kavale, Hirshoren, & Forness, 1998 ; Pashler, McDaniel, Rohrer, & Bjork, 2008 ; Rohrer & Pashler, 2012 ). That is, there is no evidence that instructing students in their preferred learning style leads to an overall improvement in learning (the “meshing” hypothesis). Moreover, learning styles have come to be described as a myth or urban legend within psychology (Coffield, Moseley, Hall, & Ecclestone, 2004 ; Hattie & Yates, 2014 ; Kirschner & van Merriënboer, 2013 ; Kirschner, 2017 ); skepticism about learning styles is a common stance amongst evidence-informed teachers (e.g., Saunders, 2016 ). Providing evidence against the notion of learning styles, Kraemer, Rosenberg, and Thompson-Schill ( 2009 ) found that individuals who scored as “verbalizers” and “visualizers” did not perform any better on experimental trials matching their preference. Instead, it has recently been shown that learning through one’s preferred learning style is associated with elevated subjective judgements of learning, but not objective performance (Knoll, Otani, Skeel, & Van Horn, 2017 ). In contrast to learning styles, dual coding is based on providing additional, complementary forms of information to enhance learning, rather than tailoring instruction to individuals’ preferences.

Genuine educational environments present many opportunities for combining the strategies outlined above. Spacing can be particularly potent for learning if it is combined with retrieval practice. The additive benefits of retrieval practice and spacing can be gained by engaging in retrieval practice multiple times (also known as distributed practice; see Cepeda et al., 2006 ). Interleaving naturally entails spacing if students interleave old and new material. Concrete examples can be both verbal and visual, making use of dual coding. In addition, the strategies of elaboration, concrete examples, and dual coding all work best when used as part of retrieval practice. For example, in the concept-mapping studies mentioned above (Blunt & Karpicke, 2014 ; Karpicke, Blunt, et al., 2014 ), creating concept maps while looking at course materials (e.g., a textbook) was not as effective for later memory as creating concept maps from memory. When practicing elaborative interrogation, students can start off answering the “how” and “why” questions they pose for themselves using class materials, and work their way up to answering them from memory. And when interleaving different problem types, students should be practicing answering them rather than just looking over worked examples.

But while these ideas for strategy combinations have empirical bases, it has not yet been established whether the benefits of the strategies to learning are additive, super-additive, or, in some cases, incompatible. Thus, future research needs to (a) better formalize the definition of each strategy (particularly critical for elaboration and dual coding), (b) identify best practices for implementation in the classroom, (c) delineate the boundary conditions of each strategy, and (d) strategically investigate interactions between the six strategies we outlined in this manuscript.

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YW took the lead on writing the “Spaced practice”, “Interleaving”, and “Elaboration” sections. CRM took the lead on writing the “Concrete examples” and “Dual coding” sections. MAS took the lead on writing the “Retrieval practice” section. All authors edited each others’ sections. All authors were involved in the conception and writing of the manuscript. All authors gave approval of the final version.

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Research and teaching writing

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Writing is an essential but complex skill that students must master if they are to take full advantage of educational, occupational, and civic responsibilities. Schools, and the teachers who work in them, are tasked with teaching students how to write. Knowledge about how to teach writing can be obtained from many different sources, including one’s experience teaching or being taught to write, observing others teach writing, and advise offered by writing experts. It is difficult to determine if much of the lore teachers acquire through these methods are effective, generalizable, or reliable unless they are scientifically tested. This special issue of Reading & Writing includes 11 writing intervention studies conducted primarily with students in the elementary grades. It provides important new information on evidence-based writing practices.

Avoid common mistakes on your manuscript.

There are many different ways that teachers can learn about how to teach writing. One way of acquiring such knowledge is by teaching this skill to others. As teachers apply different instructional procedures, they form judgments about the value and efficacy of these practices. In essence, they learn by doing (Graham, 2018 ).

A second way teachers learn about how to teach writing is by observing others and learning from them (Graham, 2018 ). Teachers likely remember some of the instructional methods used by those who taught them to write (e.g., teachers, mentors, parents, guardians, and peers). They may in turn adopt some of these practices when they teach their own students. This may be particularly true for instructional practices they considered effective.

Teachers can gain additional insight into teaching writing by observing and absorbing insights offered by others who have taught writing or studied how to teach it. This includes knowledge acquired from instructors teaching literacy and writing courses as well as experts offering advice on writing instruction at conferences, through workshops, podcasts, or other forms of information sharing. Teachers may also learn about teaching writing by discussing this topic with their peers or observing them as they teach writing.

A third source of knowledge that teachers can access are published materials about how to teach writing. This includes textbooks and articles on the subject, curriculum guides, commercial materials, and position statements from professional organizations to provide just a few examples. These resources can further involve digital sources such as videos demonstrating how to apply specific writing procedures, experts promoting specific teaching techniques, or web sites devoted to writing instruction.

The concern

Given all of the possible knowledge sources teachers can access or experience, there is an abundance of information, recommendations, and teaching materials on how to teach writing that is available to teachers. This blessing experiences at least one serious limitation. Too often, there is limited, circumscribed, or no evidence that the proffered advice, know-how, or wisdom works. There are many claims about what is effective, but too little proof. Unfortunately, this observation applies to much of the lore that teachers acquire about writing instruction.

Teaching lore mainly involves writing practices teachers experienced when they learned to write, instructional practices teachers develop and apply with their students, writing practices they see other teachers apply, and teaching practices promoted by experts (Graham & Harris, 2014 ). While we have no doubt that teachers and experts possess considerable knowledge and insight about how to teach writing, basing the teaching of this complex skill on such lore alone is risky.

Why is this the case? One reason is that it is difficult to determine which aspects of teaching lore are valid. For example, there are many things a teacher does while teaching writing. When their students’ writing improves, they may attribute this change to specific procedures they applied. While this evaluation may be correct, it is also possible that this judgment is incorrect or only applies to some students or to a procedure in a given context.

Teachers are not the only ones who can succumb to such selective bias. Specific teaching lore promoted by writing experts are also susceptible to misinterpretation in terms of their effectiveness. To illustrate, writing experts can overestimate the impact of favored instructional methods, forming judgments consistent with their philosophical views on writing development or instruction. For instance, proponents of the whole language approach to learning to read and write believed that writing and reading develop naturally just like oral language (Goodman, 1992 ). Consistent with these beliefs, they championed an approach to literacy instruction based on the use of informal teaching methods (e.g., reading and writing for real purposes), while at the same time deemphasizing explicitly and systematically teaching students foundational writing and reading skills and strategies (Graham & Harris, 1997 ). Instead, these skills are only taught when the need arises, mostly through short mini-lessons. Advocates for whole language frequently promoted the effectiveness of this two-pronged approach (Begeron, 1990 ), without providing much in the way of empirical evidence that it was effective, or perhaps even more importantly, that it was as effective as other alternatives such as reading and writing programs that emphasized reading and writing for real purposes, coupled with systematic and explicit skills and strategy instruction (Graham & Harris, 1994 ). Even for fundamental writing skills such as spelling, there is considerable evidence that both informal teaching and explicit instruction are effective (Graham, 2000 ; Graham & Santangelo, 2014 ), while whole language approaches are fundamentally misguided about what is written language (Liberman, 1999 ).

Whole language is not the only approach to teaching writing that has suffered from questionable claims about its effectiveness. Even the venerable Donald Graves was guilty of this to some degree with the process approach to writing that he supported and advocated (see Smagorinski, 1987 ). The evidence he offered in support of his favored approach to teaching writing relied in large part on testimonials and exemplar writing of selected students, presenting a potentially overly optimistic assessment of this approach. This is not to say that the process approach is ineffective, as there is now considerable empirical evidence supporting the opposite conclusion (Sandmel & Graham, 2011 ). Instead, this example illustrates that adopting whole cloth even highly popular and widely used teaching lore without careful consideration of its effectiveness and the evidence available to support it can be risky. The lack of evidence or the type of evidence provided can make it extremely difficult for teachers or other interested parties to determine if the testimonials or evidence used to support specific teaching lore in writing are representative or atypical.

A third issue that makes some teaching lore risky is that it may be based on the experience of a single or a very small number of teachers. As an example, this can occur for knowledge a teacher acquires as a result of his or her experience teaching writing. The teaching practice(s) may in fact be effective for the students in this teacher’s classroom, but they may not be effective when applied by another teacher or with different students. Until this proposition is tested, there is no way to determine if this teaching lore will produce reliable results when applied more broadly.

As these concerns demonstrate, the validity, generalizability, and replicability of instructional practices based on teaching lore are uncertain. This is not to devalue what teachers or experts know, but to demonstrate the limits of this knowledge.

Evidence-based writing practices

The concerns about the value of teaching lore raised above raises the question: How should the structure and details of writing instruction be determined? The solution that we recommend is to take an evidence-based practice approach to both enhance teachers’ knowledge and develop writing instruction. Starting with medicine in the 1990s, and spreading quickly to psychology, informational science, business, education, and a host of other disciplines, this movement promoted the idea that practitioners in a field should apply the best scientific evidence available to make informed and judicious decisions for their clients (Sackett et al., 1996 ). The basic assumption underlying this approach is that the findings from research can positively impact practice. The evidence-based practice movement was a reaction to practitioners basing what they did almost strictly on tradition and lore, without scientific evidence to validate it.

One reason why this represents a positive step forward in education and the teaching of writing is that instructional practices based on high quality intervention research addresses the three issues of concern we raised about teaching lore. First, high quality intervention studies address the issue of validity. They are designed specifically to isolate the effects of a specific instructional practice or set of instructional practices. They provide systematically gathered evidence on whether the instructional practices tested produced the desired impact. They further apply methodological procedures to rule out alternative explanations for observed effects. Second, high quality intervention studies address issues of generalizability by describing the participants and the context in which the practice was applied, and by using statistical procedures to determine the confidence that can be placed in specific findings. Three, they address the issue of replicability, as the replication of effects across multiple situations is the hall mark of scientific testing (Graham & Harris, 2014 ).

Another reason why the evidence-based approach represents a positive step forward in terms of teaching writing is that the evidence gathered from high quality intervention studies can provide a general set of guidelines for designing an effective writing program. Graham et al. ( 2016 ) created such a roadmap by drawing on three sources of scientific evidence: true-and quasi- experimental writing intervention studies, single-case design studies, and qualitative studies of how exceptional literacy teachers taught writing (see also Graham & Harris, 2018 ). They indicated that the scientific evidence from these three sources supports the development of writing programs that include the following. Students write frequently. They are supported by teachers and peers as they write. Essential writing skills, strategies, and knowledge are taught. Students use word processors and other twenty-first century tools to write. Writing occurs in a positive and motivating environment. Writing is used to support learning. Based on several recent meta-analyses of high quality intervention studies (Graham, et al., 2018a , b ; Graham, et al., 2018a , b ), Graham now recommends that the evidence also supports connecting writing and reading instruction (Graham, 2019 , 2020 ).

A third reason why the evidence-based approach is a positive development is that it provides teachers with a variety of techniques for teaching writing that have been shown to be effective in other teachers’ classes and in multiple situations. While this does not guarantee that a specific evidence-based practices is effective in all situations, a highly unlikely proposition for any writing practice, it does provide teachers with instructional procedures with a proven track record. This includes, but is not limited to (Graham & Harris, 2018 ; Graham et al., 2016 ):

Setting goals for writing.

Teaching general as well as genre-specific strategies for planning, revising, editing, and regulating the writing process. Engaging students in prewriting practices for gathering, organizing, and evaluation possible writing contents and plans.

Teaching sentence construction skills with sentence-combining procedures.

Providing students with feedback about their writing and their progress learning new writing skills.

Teaching handwriting, spelling, and typing.

Increasing how much students write; analyzing and emulating model texts.

Teaching vocabulary for writing.

Creating routines for students to help each other as they write.

Putting into place procedures for enhancing motivation.

Teaching paragraph writing skills.

Employing technology such as word processing that makes it easier to write.

It is also important to realize that an evidence-based approach to writing does not mean that teachers should abandon the hard-earned knowledge they have acquired through their experiences as teachers or learners. The evidence-based movement emphasizes that teachers contextualize knowledge about teaching writing acquired through research with their own knowledge about their students, the context in which they work, and what they know about writing and teaching it (Graham et al., 2016 ). When applying instructional practices acquired through research as well as teaching lore, we recommend that teachers weigh the benefits, limitations, and possible harm that might ensue as a consequence of applying any teaching procedure. Once a decision is made to apply a specific practice, it is advisable to monitor its effectiveness and make adjustments as needed.

Finally, while the scientific testing of writing practices has provided considerable insight into how writing can be taught effectively, it is not broad, deep, or rich enough to tell us all we need to know about teaching writing. It is highly unlikely that this will ever be the case. We operate on the principle that there is no single best method for teaching writing to all students, nor is it likely that science will provide us with formulas to prescribe exactly how writing should be taught to each student individually. Writing, learning, children, and the contexts in which they operate are just too complex to make this a likely consequence of the evidence-based movement. As a result, we believe that the best writing instruction will be provided by teachers who apply evidence-based practices in conjunction with the best knowledge they have acquired as teachers and learners, using each of these forms of knowledge in an intelligent, judicious, and critical manner.

Over time, we anticipate that evidence-based practices will play an ever increasing role in the process described above. This is inevitable as our knowledge about evidence-based writing practices expands. This brings us to the purpose of this special issue of Reading & Writing: An Interdisciplinary Journal . This special issue presents 11 writing intervention studies focusing almost exclusively with students in the elementary grades. These studies were conducted in Europe and the United States, and they replicate and extend prior research conducted with young developing writers.

The special issue

Perhaps the most tested writing instructional practice of all time, and the one yielding the largest effects sizes (Graham et al., 2013 ), is the Self-regulated Strategy Development (SRSD) model developed by Karen Harris (see Harris et al., 2008 for a description of this approach). Several studies in the current special issue tested specific iterations of the use of the SRSD model as a means for teaching writing to elementary grade students. Collins and her colleagues examined the effectiveness of teaching third grade students in the United States task specific strategies for planning and drafting expository essays using information from social studies text using this model. This instruction enhanced the quality of students’ texts and resulted in improvement on a norm-referenced measure of writing where students identified their favorite game and provided reasons why this was the case.

In a second SRSD study conducted with second and third grade children in Spain, Salas and her colleagues examined if teaching planning and drafting strategies for writing an opinion essay was equally effective with children from more and less disadvantaged backgrounds. SRSD was equally effective in improving the opinion writing of children from both backgrounds, but carryover effects to reading comprehension (a skill not taught in this study) only occurred for students from less disadvantaged backgrounds.

A third study by Rosario and his colleagues involved a secondary analysis of data from an investigation in Portugal where third grade students were taught to write narratives using SRSD procedures and a story writing tool they developed. Their reanalysis focused on students experiencing difficulties learning to write showing that they differed in their approach and perceptions of teacher feedback. The majority of these children were able to use the feedback provided by their teacher and viewed it as helpful.

A fourth investigation by Hebert and his colleagues taught fourth grade students in the United States to write informational text using five text structures (description, compare/contrast, sequence of events, problem–solution, and cause effect). While the authors did not indicate they used SRSD to teach these strategies, the teaching methods mirrored this approach. In any event, the instruction provided to these children enhanced how well they wrote all five of these different kinds of text. These effects, however, did not generalize to better reading performance.

Lopez and her colleagues in Spain examined three approaches to improving sixth grade students’ writing. Students in all three conditions were taught how to set communicative goals for their writing. Students in one treatment condition were taught a strategy for revising. Students in a second treatment condition observed a reader trying to comprehend a text and suggesting ways it might be improved. Control students continued with the goal setting procedures. Students in both treatment conditions improved their writing and revising skills more than control students, but there were no differences between these two treatments.

In another Spanish study conducted by Rodriguez-Malaga and colleagues, the impact of two different treatments on the writing of fourth grade students was examined. One treatment group learned how to set product goals for their writing, whereas the other writing treatment group learned how to set product goals and strategies for planning compare/contrast texts. Only the students in the product goal and planning strategy treatment evidenced improved writing when compared to control students.

Philippakos and Voggt examined the effectiveness of on-line practice-based professional development (PBPD) for teaching genre-based writing strategies. Eighty-four second grade teachers were randomly assigned to PBPD or a no-treatment control condition. Treatment teachers taught the genre-based writing strategies with high fidelity and rated PBPD positively. Even more importantly, their students writing evidenced greater improvement than the writing of students in control teachers’ classes.

Walter and her colleagues in England examined the effectiveness of two writing interventions, sentence combining and spelling instruction, with 7 to 10 year old children experiencing difficulties learning to write. As expected, sentence combining instruction improved sentence construction skills, but even more importantly, these researchers found that the degree of improvements in sentence writing was related to students’ initial sentence, spelling, and reading skills.

In another study focused on improving students’ sentence construction skills, Arfé and her colleagues in Italy examined the effectiveness of an oral language intervention to improve the sentence construction skills of fifth and tenth grade students. This oral treatment did enhance the sentence writing skills of the younger fifth grade students. This study provides needed evidence that interventions aimed at improving oral language skills transfer to writing.

Chung and his colleagues in the United States examined if sixth grade students’ writing can be improved through self-assessment, planning and goal setting, and self-reflection when they revised a timed, on-demand essay. These students as well as students in the control condition were also taught how to revise such an essay. Treatment students evidenced greater writing gains, and were more confident about their revising capabilities than control students.

Lastly, Graham and his colleagues in the United States examined if the revising behavior of fourth grade students experiencing difficulties with writing can be enhanced through the use of revising goals that focused attention on making substantive when revising stories (e.g., change the setting of the story). Applying such goals across four stories had a positive effect on the revising behavior of these students when these goals were not in effect, resulting in more text-level revisions, more revisions that changed the meaning of text, and more revisions rated as improving text.

The 11 intervention studies in this special issue of Reading & Writing are particularly noteworthy for several reasons. One, some of these studies ( n  = 4) concentrated on improving students’ skills in writing informational and expository text. This is an area that has not received enough attention in existing writing literature. Two, enhancing students’ revising was the goal of multiple studies ( n  = 4). Again, too little attention has been given to this topic with either younger or older students. Three, it was especially gratifying to see that a pair of studies examined how to enhance sentence writing skills. This has been a neglected area of writing research since the 1980s. Four, multiple studies focused on improving the writing of students who experienced difficulties learning to write ( n  = 3). This is an area where we need much more research if we are to maximize these students’ writing success. Finally, more than half of the studies in this special issue ( n  = 6) were conducted in Europe, with the other half conducted in the United States. It is important to examine if specific writing treatments are effective in different social, cultural, political, institutional, and historical context (Graham, 2018 ), as was done with the four studies that applied SRSD to teach students strategies for writing.

We hope you enjoy the studies presented here. We further hope they serve as a catalyst to improve your own research if you are a writing scholar or your teaching if you are a practitioner.

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Graham, S., Alves, R.A. Research and teaching writing. Read Writ 34 , 1613–1621 (2021). https://doi.org/10.1007/s11145-021-10188-9

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The effect of the teacher's teaching style on students' motivation.

SUBMITTED BY:  MARIA THERESA BARBEROS,  ARNOLD GOZALO,  EUBERTA PADAYOGDOG  SUBMITTED TO:  LEE TZONGJIN, Ed.D.  CHAPTER I  THE EFFECT OF TEACHERS' TEACHING STYLE ON STUDENTS' MOTIVATION

Introduction

The teachers, being the focal figure in education, must be competent and knowledgeable in order to impart the knowledge they could give to their students. Good teaching is a very personal manner. Effective teaching is concerned with the student as a person and with his general development. The teacher must recognize individual differences among his/her students and adjust instructions that best suit to the learners. It is always a fact that as educators, we play varied and vital roles in the classroom. Teachers are considered the light in the classroom. We are entrusted with so many responsibilities that range from the very simple to most complex and very challenging jobs. Everyday we encounter them as part of the work or mission that we are in. It is very necessary that we need to understand the need to be motivated in doing our work well, so as to have motivated learners in the classroom. When students are motivated, then learning will easily take place. However, motivating students to learn requires a very challenging role on the part of the teacher. It requires a variety of teaching styles or techniques just to capture students' interests. Above all, the teacher must himself come into possession of adequate knowledge of the objectives and standards of the curriculum, skills in teaching, interests, appreciation and ideals. He needs to exert effort to lead children or students into a life that is large, full, stimulating and satisfying. Some students seem naturally enthusiastic about learning, but many need or expect their instructors or teachers to inspire, challenge or stimulate them. "Effective learning in the classroom depends on the teacher's ability to maintain the interest that brought students to the course in the first place (Erickson, 1978). Not all students are motivated by the same values, needs, desires and wants. Some students are motivated by the approval of others or by overcoming challenges.

Teachers must recognize the diversity and complexity in the classroom, be it the ethnicity, gender, culture, language abilities and interests. Getting students to work and learn in class is largely influenced in all these areas. Classroom diversity exists not only among students and their peers but may be also exacerbated by language and cultural differences between teachers and students.

Since 2003, many foreign professional teachers, particularly from the Philippines, came to New York City to teach with little knowledge of American school settings. Filipino teachers have distinct styles and expressions of teaching. They expect that: education is interactive and spontaneous; teachers and students work together in the teaching-learning process; students learn through participation and interaction; homework is only part of the process; teaching is an active process; students are not passive learners; factual information is readily available; problem solving, creativity and critical thinking are more important; teachers should facilitate and model problem solving; students learn by being actively engaged in the process; and teachers need to be questioned and challenged. However, many Filipino teachers encountered many difficulties in teaching in NYC public schools. Some of these problems may be attributed to: students' behavior such as attention deficiency, hyperactivity disorder, and disrespect among others; and language barriers such as accent and poor understanding of languages other than English (e.g. Spanish).

As has been said, what happens in the classroom depends on the teacher's ability to maintain students' interests. Thus, teachers play a vital role in effecting classroom changes.

As stressed in the Educator's Diary published in 1995, "teaching takes place only when learning does." Considering one's teaching style and how it affects students' motivation greatly concerns the researchers. Although we might think of other factors, however, emphasis has been geared towards the effect of teacher's teaching style and student motivation.

Hypothesis:

If teacher's teaching style would fit in a class and is used consistently, then students are motivated to learn.

Purpose of the Study

The main thrust of the study was to find out the effect of the teacher's teaching style on students' motivation.

Action Research Questions

This paper attempted to answer specific questions such as: 1. What is the effect of teacher's teaching style using English As A Second Language Strategies on student's motivation? 2. How does teacher's teaching style affect students' motivation? 3. What could be some categories that make one's teaching style effective in motivating students?

Research Design/Methods of Collecting Data

The descriptive-survey method was used in this study, and descriptive means that surveys are made in order to discover some aspects of teacher's teaching style and the word survey denotes an investigation of a field to ascertain the typical condition is obtaining. The researchers used questionnaires, observations, interviews, students' class work and other student outputs for this study. The questionnaires were administered before and after ESL strategies were applied. Observation refers to what he/she sees taking place in the classroom based on student's daily participation. Student interviews were done informally before, during, and after classes. Several categories affecting motivation were being presented in the questionnaire.

Research Environment and Respondents

The research was conducted at IS 164 and IS 143 where three teachers conducting this research were the subjects and the students of these teachers selected randomly specifically in the eighth and sixth grade. The student respondents were the researchers' own students, where 6 to 7 students from each teacher were selected. Twenty students were used as samples.

To measure students' motivation, researchers used questionnaires which covered important categories, namely: attitudes, student's participation, homework, and grades. Open-ended questions were also given for students' opinion, ideas and feelings towards the teacher and the subject. The teacher's teaching style covers the various scaffolding strategies. The data that were collected from this research helped the teachers to evaluate their strengths and weaknesses so as to improve instruction. The results of this study could benefit both teachers and students.

Research Procedure

Data gathering.

The researchers personally distributed the questionnaires. Each item in each category ranges from a scale of 5-1 where 5 rated as Strongly Agree while 1 as Strongly Disagree. The questionnaires were collected and data obtained were tabulated in tables and interpreted using the simple percentage. While the open ended questions, answers that were given by the students with the most frequency were noted.

Review of Related Literature

Helping students understand better in the classroom is one of the primary concerns of every teacher. Teachers need to motivate students how to learn. According to Phil Schlecty (1994), students who understand the lesson tend to be more engaged and show different characteristics such as they are attracted to do work, persist in the work despite challenges and obstacles, and take visible delight in accomplishing their work. In developing students' understanding to learn important concepts, teacher may use a variety of teaching strategies that would work best for her/his students. According to Raymond Wlodkowski and Margery Ginsberg (1995), research has shown no teaching strategy that will consistently engage all learners. The key is helping students relate lesson content to their own backgrounds which would include students' prior knowledge in understanding new concepts. Due recognition should be given to the fact that interest, according to Saucier (1989:167) directly or indirectly contributes to all learning. Yet, it appears that many teachers apparently still need to accept this fundamental principle. Teachers should mind the chief component of interest in the classroom. It is a means of forming lasting effort in attaining the skills needed for life. Furthermore teachers need to vary teaching styles and techniques so as not to cause boredom to the students in the classroom. Seeking greater insight into how children learn from the way teachers discuss and handle the lesson in the classroom and teach students the life skills they need, could be one of the greatest achievements in the teaching process.

Furthermore, researchers have begun to identify some aspects of the teaching situation that help enhance students' motivation. Research made by Lucas (1990), Weinert and Kluwe (1987) show that several styles could be employed by the teachers to encourage students to become self motivated independent learners. As identified, teachers must give frequent positive feedback that supports students' beliefs that they can do well; ensure opportunities for students' success by assigning tasks that are either too easy nor too difficult; help students find personal meaning and value in the material; and help students feel that they are valued members of a learning community. According to Brock (1976), Cashin (1979) and Lucas (1990), it is necessary for teachers to work from students' strengths and interests by finding out why students are in your class and what are their expectations. Therefore it is important to take into consideration students' needs and interests so as to focus instruction that is applicable to different groups of students with different levels.

CHAPTER II  PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA

This chapter presents and analyzes data that answer the subsidiary problems of the study. Table I showed that out of the 20 student respondents, 50% were males and 50% females. Of the male students respondents, only 2 males belong to the high group while 8 males from the low group. For the females, each of the group had 5 respondents. It also showed that there were 7 respondents from the high group and 13 came from the low group.

Table 1:Respondents by Gender

Table 2 showed that out of the 20 students respondents, 80% of students were of Hispanic origin; 10% of respondents were White (not of Hispanic origin); and 10% were Black (not of Hispanic origin); while 0% were of American Indian, Asian or Pacific Islander ethnicity. The results also showed that among the Hispanic, 40% came from the low and 40% came from the high group. There were only 10% White respondents from both groups. There were 10% respondents who were Black from both groups.

Table 2: Respondents by Ethnicity

Table 3 showed that 15% of the respondents had grades between 96-100 in Science, 0% between 91-95, while 15% scored between 86-90, the same as the range between 81-85. However, on the low group 25% of the respondents had grades between 71-75, 5% each had a range between 66-70 and 61-65; while 15% of the respondents did not have Science last year.

Table 3: Grades in Science

Table 4 revealed that for students' motivation-attitude, more than half of the respondents agreed that they are always excited to attend classes this school year. 75% of the students believed that Science is fun and interesting. Similarly, 80% of the respondents agreed that Science is important for them and 60% said that they love Science.

For student motivation-participation, it showed that more than half of the respondents affirm that they are always prepared in their Science classes. 75% of the students participated in Science activities; 50% did their Science assignments consistently.

For student motivation-homework, it could be noted that 60% of the students completed their homework on time and 50% found homework useful and important. 85% of the students said that they got enough support to do homework at home and 90% said that the teachers checked their homework.

For student motivation-grades, 65% got good grades in Science. 65% of the respondents said that they study their lessons before a test or a quiz. More than half of the respondents disagreed that the terms or words used in the test were difficult to understand. Less than half of the respondents agreed tests measure their understanding of Science concepts and knowledge, while 80% thought that grading is fair. On the other hand, the data under teaching style as noted on table 4 showed that 65% of the students strongly agreed that they have a good relationship with their Science teacher and no one disagreed. 75% noted that their Science teachers used materials that were easy to understand. 60% said that their teachers presented the lessons in many ways. More than half of the students said that they understood the way their Science teachers explained the lesson while 25% were not sure of their answer. 75% said that they got feedback from their Science teacher.

Table 4: Data on the Five Categories

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What is Teacher Research?

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Teacher research is intentional, systematic inquiry by teachers with the goals of gaining insights into teaching and learning, becom­ing more reflective practitioners, effecting changes in the classroom or school, and improving the lives of children.... Teacher research stems from teachers' own questions and seeks practical solutions to issues in their professional lives.... The major components of teacher research are: conceptualization, in which teachers identify a significant problem or interest and determine relevant re­search questions; implementation, in which teachers collect and analyze data; and interpretation, in which teachers examine findings for meaning and take appropriate actions.... Teacher research is systematic in that teachers follow specific procedures and carefully document each step of the process. — " The Nature of Teacher Research " by Barbara Henderson, Daniel R. Meier, and Gail Perry

Teacher Research Resources

The resources below provide early childhood education professionals with tools to learn more about the teacher research process, explore accounts of teachers conducting research in their own classrooms, and connect with others in the field interested in teacher research.

Resources from  Voices of Practitioners

The Nature of Teacher Research Barbara Henderson, Daniel R. Meier, and Gail Perry

The Value of Teacher Research: Nurturing Professional and Personal Growth through Inquiry Andrew J. Stremmel

How To Do Action Research In Your Classroom: Lessons from the Teachers Network Leadership Institute Frances Rust and Christopher Clark

Resources From Other Publications

The resources listed here provide early childhood education professionals with tools to learn more about the teacher research process, explore accounts of teachers conducting research in their own classrooms, and connect with others in the field interested in teacher research.

American Educational Research Association (AERA) AERA encourages scholarly inquiry and promotes the dissemination and application of research results. It includes special interest groups (SIGs) devoted to early childhood and teacher research. Potential members can join AERA and then choose the Action Research or Teachers as Researchers SIGs (See “AR SIG, AERA” and “TR SIG, AERA” below.) AERA holds an annual conference with presentations of early childhood teacher research among many other sessions. www.aera.net

Action Research Special Interest Group, American Educational Research Association (AR SIG, AERA) This group builds community among those engaged in action research and those teaching others to do action research. It offers a blog, links to action research communities, and lists of action research books, journals, and conferences. http://sites.google.com/site/aeraarsig/

Teacher as Researcher Special Interest Group, American Educational Research Association (TAR SIG, AERA) This group consists of AERA members who are teacher educators and preK–12th grade educators; it aims to present teacher research at the AERA conference and elsewhere nationally. Early childhood teacher research is an important part of the group. http://www.aera.net/SIG126/TeacherasResearcherSIG126/tabid/11980/Default.aspx

The Center for Practitioner Research (CFPR) of the National College of Education at National-Louis University CFPR aims to affect education through collaborative scholarship contributing to knowledge, practice, advocacy, and policy in education. The website includes selected action research resources, including links to websites, book lists, conference information, and its online journal  Inquiry in Education . http://nlu.nl.edu/cfpr

Educational Action Research Educational Action Research  is an international journal concerned with exploring the dialogue between research and practice in educational settings. www.tandf.co.uk/journals/reac

Let’s Collaborate, Teacher Research from Access Excellence @ the National Health Museum This site includes useful supports for engaging in teacher research, including examples of K–12 research focused on science education. It offers information on starting a project, examples of teacher research projects, and links to online resources. www.accessexcellence.org/LC/TL/AR/

National Association of Early Childhood Teacher Educators (NAECTE) NAECTE promotes the professional growth of early childhood teacher educators and advocates for improvements to the field. NAECTE’s  Journal of Early Childhood Teacher Education  occasionally publishes teacher research articles, including a special issue focused on teacher research (Volume 31, Issue 3). NAECTE also provides ResearchNets, a forum to foster educational research with teacher research presentations. www.naecte.org

Networks: An On-line Journal for Teacher Research at the University of Wisconsin A venue for sharing reports of action research and discussion on inquiry for teachers at all levels, this journal provides space for discussion of inquiry as a tool to learn about practice and improve its effectiveness. http://journals.library.wisc.edu/index.php/networks

Self-Study Teacher Research: Improving your Practice through Collaborative Inquiry, Student Study Guide from Sage Publications This web-based student study site accompanies a book of the same name; it provides a wealth of information on its own for teachers or teacher educators who conduct studies of their own teaching practice. http://www.sagepub.com/samaras/default.htm

Teacher Action Research from George Mason University This site offers information about the teacher research process, including resources for carrying out teacher research studies. It also contains discussion of current teacher research issues and a comparison of teacher research to other forms of educational research and professional development. http://gse.gmu.edu/research/tr

Teacher Inquiry Communities Network from the National Writing Project (NWP) This network offers information on a mini-grant program supporting an inquiry stance toward teaching and learning. It includes information about the grant program, program reports, and examples of projects (including early elementary projects). http://www.nwp.org/cs/public/print/programs/tic

Teaching and Teacher Education This journal aims to enhance theory, research, and practice in teaching and teacher education through the publication of primary research and review papers. http://www.journals.elsevier.com/teaching-and-teacher-education

Voices of Practitioners