A Meta-Analysis of Ten Learning Techniques

While the purpose of schooling may change over time and differ across jurisdictions, the mechanisms by which human learning occurs arguably are somewhat more universal. Learning techniques actions that learners themselves can take to enhance their learning–have attracted considerable research interest in recent years (Edwards et al., 2014). This is unsurprising given the direct, practical applicability of such research, and its relevance to students, educators and school leaders alike.

A major, thorough, and important review of various learning techniques has created much interest. Dunlosky et al. (2013a) reviewed 10 learning techniques and a feature of their review is their careful analyses of possible moderators to the conclusions about the effectiveness of these learning techniques, such as learning conditions (e.g., study alone or in groups), student characteristics (e.g., age, ability), materials (e.g., simple concepts or problem-based analyses), and criterion tasks (different outcome measures). This article uses this review as a basis for conducting a meta-analysis on these authors’ references to add another perspective of the magnitude of the various learning techniques and how they are affected by various moderators.

Dunlosky et al. (2013a), claim to have conducted an exhaustive search of the literature, relied on previous empirical reviews of learning techniques, and applied a robust set of selection criteria before selecting final 10 techniques. These criteria included that the technique could be implemented by students without assistance, there was sufficient empirical evidence to support at least a preliminary assessment of efficacy, and there was robust evidence to identify the generalizability of its benefits across four categories of variables materials, learning conditions, student characteristics and criterion tasks. Indeed the authors’ mastery of the literature is most evident throughout the article.

The authors then categorised the 10 techniques into three groups based on whether they considered them having high, medium or low support for their effectiveness in enhancing learning. Categorised as “high” support were Practice Testing (self-testing or taking practice tests on to-be-learned material) and Distributed Practice (implementing a schedule of practice that spreads out study activities over time in contrast to massed or ‘crammed’ practice). Categorised as “moderate” support were Elaborative Interrogation (generating an explanation of a fact or concept), Self-Explanation (where the student explains how new information is related to already-known information) and Interleaved Practice (implementing a schedule of practice mixing different kinds of problems within a single study session). Finally, categorised as “low” support were Summarization (writing summaries of to-be-learned texts), Highlighting/Underlining (marking potentially important portions of to-be-learned materials whilst reading), Keyword Mnemonic (generating keywords and mental imagery to associate verbal materials), Imagery use (attempting to form mental images of text materials while reading or listening) and Re-Reading (restudying text material again after an initial reading). In an accompanying article, Dunlosky et al. (2013b) claimed that some of these low support techniques (that students use a lot) have “failed to help students of all sorts” (p. 20), the benefits can be short lived, they may not be widely applicable, the benefits are relatively limited, and they do not provide “bang for the buck” (p. 21).

Practice Testing is one of the two techniques with the highest utility. This must be distinguished from high stakes testing: Practice Testing instead involves any activity where the student practices retrieval of to-be-learned information, reproduces that information in some form, and evaluates the correctness of that reproduction against an accepted ‘correct’ answer. Any discrepancy between the produced and “correct” information then forms a type of feedback that the learner uses to modify their understanding. Practice tests can include a range of activities that students can conduct on their own, such as completing questions from textbooks or previous exams, or even self-generated flashcards. According to Dunlosky et al. (2013a), such testing helps increase the likelihood that target information can be retrieved from long-term memory and it helps students mentally organize information that supports better retention and test performance. This effect is strong regardless of test form (multiple choice or essay), even when the format of the practice test does not match the format of the criterion test, and it is effective for all ages of student. Practice Testing works well even when it is massed, but is even more effective when it is spaced over time. It does not place high demand on time, is easy to learn to do (but some basic instruction on how to most effectively use practice tests helps), is so much better than unguided restudy, and so much more effective when there is feedback about the practice test outputs (which also enhances confidence in performance).

Many studies have shown that practice spread out over time (spaced) is much more effective than practice over a short time period (massed)–this is what is meant by Distributed Practice. Most students need three to four opportunities to learn something (Nuthall, 2007) but these learning opportunities are more effective if they are distributed over time, rather than delivered in one massed session: that is, spaced practice, not skill and drill, spread out not crammed, and longer inter-study intervals are more effective than shorter. There have been four meta-analyses of Spaced vs. Massed practices involving about 300 studies, with an average effect of 0.60 (Donovan and Radosevich, 1999; Cepeda et al., 2006; Janiszewski et al., 2003; Lee and Genovese 1988). Cepeda et al. (2008) showed that for almost all retention intervals, memory performance increases sharply with the length of the spacing interval. But at a certain spacing interval, optimal test performance is reached, and from that interval onwards, performance declines but only to a limited degree. But they also note that this does not take into account the absolute level of performance, which decreases as the retention interval increases. Further, Spaced Practice is more effective for deeper than surface processing, and for all ages. Rowland (2014) completed a meta-analysis on 61 studies investigating the effect of testing vs. restudy on retention. He found a high effect size (d = 0.50) supporting the testing over restudy, and the effects were greater for recall than for recognition tasks. The educational message is to review previously covered material in subsequent units of work, time tests regularly and not all at the end (which encourages cramming and massed practice), and given that students tend to rate learning higher after massed, educate them as to the benefits of spaced practice and show them those benefits.

Elaborative Interrogation, Self-Explanation, and Interleaved Practice received moderate support. Elaborative Interrogation involves asking “Why” questions (“Why does it make sense that” “Why is this true”) and a major purpose is to integrate new information with existing prior knowledge. The effects are higher when elaborations are precise rather than imprecise, when prior knowledge is higher than lower, and when elaborations are self-generated rather than provided. A constraint of the method is that is more applicable to surface than to deep understanding. Self-explanation involves students explaining some aspect of their processing during learning. It works across task domains, across ages, but may require training, and can take some time to implement. Interleaved Practice involves alternating study practice of different kinds of items, problems, and even subject domains rather than blocking study. The claim is that Interleaving leads to better discrimination of different kinds of problems, more attention to the actual question or problem posed, and as above there is better learning from Spaced than Mass Practice. The research evidence base is currently small, and it is not clear how to break tasks in an optimal manner so as to interleave them.

There is mixed and often low support, claimed Dunlosky et al. (2013a), for Summarization, Highlighting, Keyword Mnemonic, Imagery Use for text learning, and Re-Reading. Summarization involves students writing summaries of to-be-learned texts with the aim of capturing the main points and excluding unimportant or repetitive material. The generality and accuracy of the summary are important moderators, and it is not clear whether it is better to summarize smaller pieces of a text (more frequent Summarization) or to capture more of the text in a larger summary (less frequent Summarization). Younger and less able students are not as good at Summarization, it is better when the assessments are performance or generative and not closed or multiple choice tests, and it can require extensive training to use optimally. Highlighting and Underlining are simple to use, do not require training, and demand hardly any additional time beyond the reading of the text. It is more effective when professionals do the highlighting, then for the student doing the highlighting, and least for reading other student’s highlights. It may be detrimental to later ability to make inferences; overall it does little to boost performance. The Keyword Mnemonic involves associating some imagery with the word or concept to be learned. The method requires generating images that can be difficult for younger and less able students, and there is evidence is may not produce durable retention. Similarly Imagery Use is of low utility. This method involves students mentally imaging or drawing pictures of the content using simple and clear mental images. It too is more constrained to imagery-friendly materials, and memory capacity. Re-Reading is very common. It is more effective when the Re-Reading is spaced and not massed, the effects seem to decrease beyond the second reading, is better for factual recall than for developing comprehension, and it is not clear it is effective with students below college age.

A follow-up and more teacher accessible article by Dunlosky et al. (2013b) asks why students do not learn about the best techniques for learning. Perhaps, the authors suggest, it is because curricula are developed to highlight content rather than how to effectively acquire it; and it may be because many recent textbooks used in teacher education courses fail to adequately cover the most effective techniques or how to teach students to use them. They noted that employing the best techniques will only be effective if students are motivated to use them correctly but teaching students to guide their learning of content using effective techniques will allow them to successfully learn throughout their lifetime. Some of the authors’ tips include: give a low-stakes quiz at the beginning of each class and focus on the most important material; give a cumulative exam that encourages students to re-study the most important material in a distributed fashion; encourage students to develop a “study planner” so they can distribute their study throughout a class and rely less on cramming; encourage students to use practice retrieval when studying instead of passively re-reading their books and notes; encourage students to elaborate on what they are reading, such as by asking “why” questions; mix up problems from earlier classes so students can practice identifying problems and their solutions; and tell students that highlighting is fine but only in the beginning of their learning journey.

The Dunlosky et al. (2013a), review shows a high level of care of selection of articles, an expansiveness of the review, an attention to generalizability and moderators, and is sophisticated in its conclusions. There are two aspects of the this research that the current paper aims to address. First, Dunlosky et al. (2013a) relied on a traditional literature review method and did not include any estimates of the effect-sizes of their various techniques, nor did they indicate the magnitude of their terms high, medium, and low. One of the purposes of this article is to provide these empirical estimates. Second, the authors did not empirically evaluate the moderators of the 10 learning techniques, such as Deep vs. Surface learning, Far vs. Near Transfer, or age/grade level of learner. An aim of this paper is to analyze the effects of each of the 10 techniques with respect to these and other potential moderators.