Collection of criticisms of Adam Perkins’ ‘The Welfare Trait’

In late 2015, Dr Adam Perkins published his book called ‘The Welfare Trait’. The main crux of his argument was that each generation who is supported by the welfare state becomes more work-shy. He also argued that the welfare state increased the number of children born to households where neither parent works. His solution is to change the welfare state to limit the number of children that each non-working household has.

His book caused quite a storm when it was first released. Some people argued that it was crudely-disguised eugenics, others argued that those who were dismissing it were refusing to face the facts. Over time, more and more criticisms of and problems with Perkins’ work have come to light (e.g. basic statistical errors and incorrect conclusions from papers). Below is a collection of some (but not all) of the criticisms levelled at Perkins’ book. read more

Stereotype threat

Don’t you just love being wrong? Of course you don’t, no one does. But there is a grim satisfaction in no longer believing something that there isn’t good enough evidence for. This is what I experienced after examining the phenomenon known as ‘stereotype threat’. In short, it’s the idea that groups with negative stereotypes about them feel anxiety when these stereotypes are made salient (and are therefore more likely to confirm those stereotypes) e.g. women being inferior than men at maths. read more

How biased are you? The role of intelligence in protecting you from thinking biases.

People generally like to believe they are rational (Greenberg, 2015). Unfortunately, this isn’t usually the case (Tversky & Kahneman, 1974). People very easily fall prey to thinking biases which stops them from making a purely rational judgement (whether always making a rational judgement is a good thing is a discussion for another time). These are flaws in thinking e.g. the availability bias, where you judge the likelihood of an event or the frequency of a class by how easily you can recall an example of that event (Tversky & Kahneman, 1974). So after seeing a shark attack in the news, people think the probability of a shark attack is much higher than it is (because they can easily recall an example of one). read more

The benefits of single-sex schooling

Many people claim that single-sex (SS) education is better for students than co-educational (CE) e.g. Jackson (2016). There have been criticisms of this idea e.g. Halpern et a. (2011) but generally it is believed to be beneficial. But what does the evidence suggest? A large-scale meta-analysis by Pahlke et al. (2014), involving 184 studies and 1,663,662 students, compared them on a variety of variables (mathematics performance; mathematics attitudes; science performance; science attitudes; attitudes about school; gender stereotyping; self-concept; interpersonal relations; aggression; victimisation; and body-image) to see if attending a SS school benefited males, females, or both. read more

How views about willpower affect you and your grades

There has been a lot of research into how self-control (defined as “restraint exercised over one’s own impulses, emotions and desires” Merriam-Webster, 2015) is affected by performing tasks that require self-control. One hypothesis with a large amount of experimental evidence to support it is the strength model of self-control (Baumeister, Bratslavsky, Muraven, & Tice, 1998; Baumeister, Vohs, & Tice, 2007). This holds that people’s self-control is a limited resource and that once used up, people will be less able to exert self-control later and will therefore be less likely to restrain themselves (Hagger, Wood, Stiff, & Chatzisarantis, 2010). This loss of your self-control resource is called “ego depletion”. Believing this then supposedly allows you to allocate you resources more efficiently and thus improve self-regulation (Vohs, Baumeister, & Schmeichel, 2012).

However there have been several studies that suggest ego depletion itself is not the cause of reduced self-control at a later time; it’s the person’s beliefs about whether their self-control resources is depleted or not that results in lapses of self-control (Job, Dweck, & Walton, 2010). So it’s not that your self-control resources is actually depleted; it’s that you believe they have and you will therefore be less likely to put in the effort required to maintain self-control. This is contrasted with those who believe in a nonlimited theory of willpower who do not experience a decrease in self-control across demanding tasks (Miller, Walton, Dweck, Job, Trzesniewski, & McClure, 2012).

A study by Job, Walton, Bernecker, & Dweck (2015) looked at the effect different beliefs about willpower had on everyday self-regulation (e.g.procrastination, consumption of unhealthy foods, poor time management, excess spending, and failure to control emotions). The participants had to say when they had experienced “self-regulation failures” in the past week. The data was therefore based on self-report, which comes with a host of problems (social desirability bias, lying), some time after the event occurred (so the participants may have forgotten). They were also  required to predict how many demands they would face in the coming week (academic tasks e.g. “tests to take”, and social stressors e.g. “experience of social exclusion”). Their natural self-control ability was also calculated (through a questionnaire).

They found no significant difference in anticipated demands between students with different theories about willpower. When students experienced/reported high demand, those with a limited resource-theory reported a greater number of self-regulation failures on procrastination. The other measures either didn’t reach significance or only just reached it (so I’m not going to focus on those). There was no significant difference between theories of willpower when demands were low. The possibility that students who endorsed the limited resource-theory were simply worse at self-regulating behaviour was controlled for and they still found a significant effect of different theories of willpower on self-regulatory failures (during high demand). This implies their beliefs about willpower affected their reported self-regulatory failures, as opposed to their natural ability to control themselves being the only causal factor.

The next step was examining whether beliefs about willpower affected an objective measure (in this case, GPA or grade point average for us non-Americans). Even when controlling for prior GPA, the students who agreed with the limited resource-theory scored lower on their GPA (though this variable only just reached significance). They also found that students who believed in the limited resource theory (and were on a course with a high work-load) scored significantly lower GPA’s than students who endorsed a nonlimited view of willpower on the same course (this last result was found even when the participant’s natural self-control was controlled for).

This is an interesting study as it suggests students who hold willpower is a limited resource are more likely to procrastinate and thus achieve a lower grade in their final tests. I feel running this as a longitudinal study and using better methods of recording self-regulatory failures would be a good next step.

References:
Baumeister, R.F.; Bratslavsky, E.; Muraven, M.; & Tice, D.M. (1998). Ego Depletion: Is the Active Self a Limited Resource? Journal of Personality and Social Psychology, 74 (5), 1252-1265.
Baumeister, R.F.; Vohs, K.D.; & Tice, D.M. (2007). The Strength Model of Self-Control. Current Directions in Psychological Science, 16 (6), 351-355.
Hagger, M.S.; Stiff, C.; & Chatzisarantis, N.L.D. (2010). Ego Depletion and the Strength Model of Self-Control: A Meta-Analysis. Psychological Bulletin, 136 (4), 495-525.
Job, V.; Dweck, C.S.; & Walton, G.M. (2010). Ego Depletion- Is It All In Your Head? Implicit Theories About Will-Power Affect Self-Regulation. Psychological Science, 21 (11), 1686-1693.
Job, V.; Walton, G.M.; Bernecker, K.; & Dweck, C.S. (2015). Implicit Theories About Willpower Predict Self-Regulation and Grades in Everyday Life. Journal of Personality and Social Psychology, 108 (4), 637-647.
Merriam-Webster. (2015). Self-control. Available at: http://www.merriam-webster.com/dictionary/self-control. Last accessed 07/04/2015.
Miller, E.M.; Walton, G.M.; Dweck, C.S.; Job, V.; Trzesniewski, K.H.; & McClure, S.M. (2012). Theories of Willpower Affect Sustained Learning. PLoS ONE, 7 (6), e38680, doi:10.1371/journal.pone.0038680.
Vohs, K.D.; Baumeister, R.F.; & Schmeichel, B.J. (2012). Motivation, personal beliefs, and limited resources all contribute to self-control. Journal of Experimental Social Psychology, 48 (4), 943-947. (function(i,s,o,g,r,a,m){i[‘GoogleAnalyticsObject’]=r;i[r]=i[r]||function(){ (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o), m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m) })(window,document,’script’,’//www.google-analytics.com/analytics.js’,’ga’); ga(‘create’, ‘UA-63654510-1’, ‘auto’); ga(‘send’, ‘pageview’); read more

So what are the best learning techniques?

We’ve looked at (some of) the evidence for different learning techniques, but which ones are the most effective? The clear winners are active retrieval and distributed practice (click on each technique for the evidence and a more in-depth analysis), so definitely try and make them a part of your learning/revision schedule. After that, it seems that summarisation has limited utility if you know how to do it properly (if you don’t it appears to be a bit of a waste of time). Self explanation may be useful, but there’s not really enough evidence to conclusively say that either way. Rereading and highlighting are very ineffective ways of learning so I would encourage you not to use them, especially if it stops you from using far more effective techniques. They may also install a false sense of understanding because you are more familiar with them, rather than actually understanding the material.

So if you want to be as effective as possible with your learning and give yourself the best chance of doing well, do these things: test yourself on the material; spread out your revision sessions and don’t just highlight or reread your notes!

References:
PsychologyBrief. (2014). Active Retrieval. Available: http://psychbrief.blogspot.co.uk/2014/07/active-retrieval.html. Last accessed 19/02/2015.
PsychologyBrief. (2014). Highlighting. Available: http://psychbrief.blogspot.co.uk/2014/08/highlighting.html. Last accessed 19/02/2015.
PsychologyBrief. (2014). Rereading. Available: http://psychbrief.blogspot.co.uk/2014/09/rereading.html. Last accessed 19/02/2015.
PsychologyBrief. (2014). Self-explanation. Available: http://psychbrief.blogspot.co.uk/2014/12/self-explanation.html. Last accessed 19/02/2015.
PsychologyBrief. (2014). Summarising. Available: http://psychbrief.blogspot.co.uk/2015/01/summarising.html. Last accessed 19/02/2015.
PsychologyBrief. (2015). Distributed Practice. Available: http://psychbrief.blogspot.co.uk/2015/02/distributed-practice.html. Last accessed 19/02/2015. (function(i,s,o,g,r,a,m){i[‘GoogleAnalyticsObject’]=r;i[r]=i[r]||function(){ (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o), m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m) })(window,document,’script’,’//www.google-analytics.com/analytics.js’,’ga’); ga(‘create’, ‘UA-63654510-1’, ‘auto’); ga(‘send’, ‘pageview’); read more

Active Retrieval

Active retrieval is the method of looking at some information and then testing yourself (either through free-recall or guided recall) to see how much you can remember. But the key aspect of this method is that it isn’t used just to see how much someone has learnt or if there are any gaps in their knowledge. Rather it is to actually help them learn and remember the information (by consolidating it in their mind).

The utility of active retrieval is well documented. They have found that students who used practice testing showed greater retention of information compared to: creating mind maps (Karpicke & Blunt, 2011); increased exposure to the materials or restudying (Roediger & Karpicke, 2006; Pyc & Rawson, 2010).

This effect is also seen across age groups, from kindergartners (Fritz, Morris, Nolan & Singleton, 2007) to university medical students (Kromann, Jensen & Ringsted, 2009).

There is evidence to suggest that testing can help transfer information; when tested in a different format to the the one they had learnt the original information in, participants remembered more and performed better if they had employed active retrieval learning techniques (Carpenter, 2012 for a review).

After a thorough review, Dunlosky et al. (2013) rated practice retrieval’s utility as a learning technique as “high” and it is easy to see why, given how effective it is and how easy it is to implement.

References:
Carpenter, S.K. (2012). Testing Enhances the Transfer of Learning. Current Directions in Psychological Science, 21 (5), 279-283.
Dunlosky, J.; Rawson, K.; Marsh, E.; Nathan, M. & Willingham, D. (2013). Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology. Psychological Science in the Public Interest. 14 (1), 4-58.
Fritz, C.O.; Morris, P.E.; Nolan, D. & Singleton, J. (2007). Expanding Retrieval Practice: an effective aid to preschool children’s learning. The Quarterly Journal of Educational Psychology, 60 (7), 991-1004.
Karpicke, J.D. & Blunt, J.R. (2011). Retrieval Practice produces more learning than Elaborative Studying with Concept Mapping. Sciece, 331 (6018), 772-775.
Kromann, C.B.; Jensen, M.L. & Ringstead, C. (2009). The effect of testing on skills learning. Medical Education, 43, 21-27.
Pyc, M.A. & Rawson, K.A. (2010). Why Testing Improves Memory: Mediator Effectiveness Hypothesis. Science, 330 (6002), 335.
Roediger, H.L. & Karpicke, J.D. (2006). Test Enhanced Learning: Taking Memory Tests Improves Long-term Retention. Association for Psychological Science, 17 (3), 249-255. (function(i,s,o,g,r,a,m){i[‘GoogleAnalyticsObject’]=r;i[r]=i[r]||function(){ (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o), m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m) })(window,document,’script’,’//www.google-analytics.com/analytics.js’,’ga’); ga(‘create’, ‘UA-63654510-1’, ‘auto’); ga(‘send’, ‘pageview’); read more

Summarising

Summarising is taking a large block of text or a large number of ideas and cutting it down to the most important points. It’s the skill of understanding what you’ve just read and picking out the relevant points. It can be used to help initial learning of the material or as a revision technique.

Summarising can help with organisational processing as you are structure the material in your mind before writing it down. It also facilitates extraction of meaning (a useful skill) because you are engaging and thinking about the material, taking out the relevant points.

But is there evidence supporting its efficacy? Bednall & Kehoe (2011) found that there was a significant correlation between the quality of the summarisation (number of correct definitions and the number of links to prior knowledge) and their scores on subsequent tests. However, summarisation had no significant effect on students scores compared to a control condition and participants in this condition scored significantly lower than explanation (participants were asked to write a paragraph explaining the information) and explanation+summarisation.

Bretzing & Kulhavy (1979) divided participants into groups, two of which were participants wrote 3 sentence summarises  of different pages of a book (either whilst they were reading or at the end of the page). They found these groups performed better on a test about the information than those who wrote out 3 verbatim sentences or just read it. These results were seen a week later in a delayed test. The study had low power as it only had 18 participants per cell. Despite it’s lower power, it is further evidence suggesting that writing about the text in your own words has greater benefit than just copying out the text (as you are actively considering the text and understanding it).

Summarisation appears to be most effective for those who already know how to do it, so it’s efficacy for younger students may be limited. However, there have been studies that show when younger students are taught how to summarise properly then it can have a positive impact on later tests (Armbruster, Anderson & Ostertag, 1986; Nelson, Smith & Dodd, 1992).

However, Annis (1985) found that summarisation didn’t have an effect on recall when asked basic comprehension questions about a passage they had read. Not only did summarisation not have a positive effect on comprehension of the text, it actually had a negative impact on student’s ability to answer questions involving evaluation and synthesis of the information.

Overall, it would appear that summarisation is a useful learning tool for those who already know how to use it effectively. Proper summarisation techniques can be taught to those who do not know how to do it but I think their time would be better spent using more effective learning techniques e.g. active retrieval, than learning a new technique that is only moderately effective.

References:
Annis, L.F. (1985). Student-generated Paragraph Summaries and the Information Processing-theory of Prose Learning. Journal of Experimental Education, 51, 4-10.
Armbruster, B.B.; Anderson, T.H. & Ostertag, J. (1987). Does text structure/summarisation instruction facilitate learning from expository text? Reading Research Quarterly, 22, 33-346.
Bednall, T.C. & Kelhoe, E.J. (2011). Effects of self-regulatory instructional aids on self-directed learning. Instructional Science, 39, 205-226.
Bretzing, B.H. & Kulhavy, R.W. (1979). Notetaking and depth of processing. Contemporary Educational Psychology, 4 (1),145-153.
Dunlosky, J.; Rawson, K.; Marsh, E.; Nathan, M. & Willingham, D. (2013). Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology. Psychological Science in the Public Interest. 14 (1), 4-58.
Nelson, J.R.; Smith, D.J. & Dodd, J.M. (1992). The effects of teaching a summary skills strategy to students identified as learning disabled on their comprehension of science text. Education and Treatment of Children, 15, (3), 228-243. (function(i,s,o,g,r,a,m){i[‘GoogleAnalyticsObject’]=r;i[r]=i[r]||function(){ (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o), m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m) })(window,document,’script’,’//www.google-analytics.com/analytics.js’,’ga’); ga(‘create’, ‘UA-63654510-1’, ‘auto’); ga(‘send’, ‘pageview’); read more

Distributed practice

Distributed practice is the idea of delaying retrieval of information that you want to remember, as opposed to trying to learn the same thing for an extended period of time. Is it better to break up learning sessions about that topic over several days or work at one segment of information for a long period of time? Distributed practice versus cramming?

The evidence is unequivocally in favour of distributed practice. Large-scale meta-analyses (Cepeda et al., 2006; Delaney, Verkoeijen & Spirgel, 2010) have shown the positive effects of distributed practice as opposed to massed practice (where there is no gap between successive rehearsals). This has also been found by Benjamin & Tullis (2010) and Toppino & Gerbier (2014). It has even been found for children as young as 4 years old for free recall (Toppino, 1991). This phenomenon has been called the “spacing effect”. There is evidence to suggest that the longer you want to learn something for, the longer gap you should have between each session (Cepeda et al., 2008). They found that the best time lag to have between sessions was 10-20% of the time you wanted to remember it for. So if you want to learn something for 1 week, the learning sessions should be spaced 12-24 hours apart; to remember something for 5 years, space the sessions 6-12 months apart (Dunlosky et al., 2013).

So we know that distributed practice is better than cramming. But what type of distributed practice should you use? If you are trying to learn a series of topics or concepts that are very similar e.g. different models for explaining mental illness, then it has been repeatedly shown that by mixing up which topic you learn about (interleaved study) helps with recall and understanding (Taylor & Rohrer, 2010; Rohrer & Taylor, 2007). So first you could study the disease model, then the integrated model, the social model and finally the psycho-dynamic model (Tyrer, 2013) in one session. This is opposed to dedicating one session to each of the different models (blocked learning). We should note that the improvement in learning with interleaved study is not even due to the spacing effect (as this method usually incurs there being a delay between sessions), but because of the cross-category comparisons that can be made using interleaved study (Carvalho & Goldstone, 2014c). On the flip side, if the categories to be learnt have low similarity then using blocked learning has been found to be more effective (Zulkiply & Burt, 2013; Carvalho & Goldstone, 2014a).

In conclusion, it seems clear that distributed practice is far more effective for learning than cramming is. It’s easy to implement as the thing it requires is that you plan your learning sessions in advance (but seeing as most students do not plan their learning months in advance, this might be easier said than done).

References:
Benjamin, A.S. & Tullis, J. (2010). What makes distributed practice effective? Cognitive Psychology, 61, 228-247.
Cepeda, N.J.; Pashler, H.; Vul, E.; Wixted, J.,T. & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132, 354-380.
Cepeda, N.J.; Vul, E.; Rohrer, D.; Wixted, J.T. & Pashler, H. (2008). Spacing effects in learning: A temporal ridgeline of optimal retention. Psychological Science, 19, 1095-1102.
Carvalho, P.F. & Goldstone, R.L. (2014a). Putting category learning in order: Category structure and temporal arrangement affect the benefit of interleaved over blocked study. Memory and Cognition, 42, 481-495.
Carvalho, P.F. & Goldstone, R.L. (2014c). Effects of interleaved and blocked study on delayed test of category learning generalisation. Frontiers in Prsychology, 5 (936), 1-11.
Delaney, P.F.; Verkoeijen, P.P.J.L & Spirgel, A. (2010). Spacing and the testing effects: A deeply critical, lengthy, and at times discursive review of the literature. Psychology of Learning and Motivation, 53, 63-147.
Dunlosky, J.; Rawson, K.; Marsh, E.; Nathan, M. & Willingham, D. (2013). Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology. Psychological Science in the Public Interest. 14 (1), 4-58.
Rohrer, D. & Taylor, K. (2007). The shuffling of mathematics problems improves learning. Instructional Science, 35, 481-498.
Taylor, K. & Rohrer, D. (2010). The effects of interleaved practice. Applied Cognitive Psychology, 24, 837-848.
Toppino, T.C. (1991). The spacing effect in young children’s free recall: Support for automatic-process explanations. Memory and Cognition, 19 (2), 159-167.
Toppino, T.C. & Gerbier, E. (2014). About Practice: Repetition, Spacing, and Abstraction. Psychology of Learning and Motivation, 60, 113-189.
Tyrer, P. (2013). Models for Mental Disorders: Conceptual Models in Psychiatry. 5th ed. Oxford: Wiley Blackwell. 1-123.
Zulkiply, N, & Burt, J.S. (2013). The exemplar interleaving effect in inductive learning: Moderation by the difficulty of category discriminations. Memory and Cognitions, 41, 16-27. (function(i,s,o,g,r,a,m){i[‘GoogleAnalyticsObject’]=r;i[r]=i[r]||function(){ (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o), m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m) })(window,document,’script’,’//www.google-analytics.com/analytics.js’,’ga’); ga(‘create’, ‘UA-63654510-1’, ‘auto’); ga(‘send’, ‘pageview’); read more

Self explanation

Self-explanation is the technique of explaining to another person (or yourself) what you are doing whilst you work and why e.g. precisely detailing why you are times the numerator by 7 and the denominator by 2 or what happens in a synapse when it fires to transfer a signal from one neuron to the next.

This can be put in to practice by asking yourself or another person to explain exactly what it is they mean when they are writing an essay or what they are doing when solving a maths problem. The prompt questions you can use can be either “content-free” or “content-specific”; they can include no information about the question at hand (e.g. “Explain what the sentence means to you. That is, what new information does the sentence provide for you? And how does it relate to what you already know?”) or they can contain relevant information to the question (e.g. “Why do you calculate the total acceptable outcomes by multiplying?”).

There have been many different studies examining the efficacy of self explanation and the circumstances in which it works best. Bielaczyc et al. (1995) conducted an experiment on 24 students (a very low number of participants) embarking on a programming course and divided them into two groups; those who received explicit instructions on how to effectively use self explanation and those who just received written instructions. They found (unsurprisingly) that those who were given explicit instructions used self explanation more and this increased use of self explanation was associated with greater performance gains. However this positive result should be taken with a pinch of salt as both conditions were actually told to use self explanation (with the experimental group actually being shown how to do it and the control group just receiving written instructions) and the fact it has a very small number of participants.

Aleven & Koedinger (2002) found that 15 and 16 year old children taking a geometry class scored higher in a subsequent test after using self explanation than the children who (during practice) just provided the correct answer. During practice, the students used a Cognitive Tutor (an interactive computer program that helped students) across all conditions e.g. participants in the self explanation condition explained each step they took and got feedback from the program as to whether it was correct. Whilst they found a positive effect for self explanation, this study also suffered from a low number of participants (41 participants, only 24 of whom actually completed the experiment).

Rittle-Johnson (2006) looked whether self explanation helped students with maths problems they had not encountered yet. There were two variables; instruction vs no instruction and self explanation vs no self explanation. She found that students who were given instructions on how to get the correct answer and those who (after getting the answer) had to explain why one answer was correct and another was incorrect, had greater procedural knowledge (the steps they had to do in order to get the correct answer). There was no interaction between instruction and self explanation. This study had enough participants per condition to have sufficient power (so you can be more confident that the finding isn’t a false-positive; Simons, Nelson & Simonsohn, 2011). This study also tested the students after a two week delay and found that participants who used self explanation scored the highest. However the participants were tested immediately after the intervention so practice testing may have had some effect on understading (Dunlowsky et al., 2013)

However, it should be noted that the utility of self explanation is massively diminished when students are provided with explanations of the answer; presumably because students put in little effort before looking at the answers (Schworm & Renkl, 2006, as cited in Dunlowsky et al., 2013).

Overall it would seem  that self explanation can be effective for learning, but more research needs to be done to determine how much of an effect it has and how long its effects last.

References:
Aleven, V. & Koedinger, K. (2002). An effective metacognitive strategy: learning by doing and explaining with a computer-based Cognitive Tutor. Cognitive Science. 26 (1), 147–179.
Bielaczyc, K.; Pirolli, P. & Brown, A.. (1995). Training in Self-Explanation and Self-Regulation Strategies: Investigating the Effects of Knowledge Acquisition Activities on Problem Solving. Cognition and Instruction. 13 (2), 221-252.
Dunlosky, J.; Rawson, K.; Marsh, E.; Nathan, M. & Willingham, D. (2013). Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology. Psychological Science in the Public Interest. 14 (1), 4-58.
Rittle-Johnson, B.. (2006). Promoting Transfer: Effects of Self-Explanation and Direct Instruction. Child Development. 77 (1), 1-15.
Simons, J.; Nelson, L. & Simonsohn, U. (2011). False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant. Psychological Science. 22 (11), 1359–1366. 
Schworm, S. & Renkl, A. (2006). Computer-supported example based learning: When instructional explanations reduce selfexplanations. Computers & Education, 46 (1), 426–445. read more