Many students are being left behind by an educational system that some people believe is in crisis. Improving educational outcomes will require efforts on many fronts, but a central premise of this monograph is that one part of a solution involves helping students to better regulate their learning through the use of effective learning techniques. Fortunately, cognitive and educational psychologists have been developing and evaluating easy-to-use learning techniques that could help students achieve their learning goals. In this monograph, we discuss 10 learning techniques in detail and offer recommendations about their relative utility. We selected techniques that were expected to be relatively easy to use and hence could be adopted by many students. Also, some techniques (e.g., highlighting and rereading) were selected because students report relying heavily on them, which makes it especially important to examine how well they work. The techniques include elaborative interrogation, self-explanation, summarization, highlighting (or underlining), the keyword mnemonic, imagery use for text learning, rereading, practice testing, distributed practice, and interleaved practice. To offer recommendations about the relative utility of these techniques, we evaluated whether their benefits generalize across four categories of variables: learning conditions, student characteristics, materials, and criterion tasks. Learning conditions include aspects of the learning environment in which the technique is implemented, such as whether a student studies alone or with a group. Student characteristics include variables such as age, ability, and level of prior knowledge. Materials vary from simple concepts to mathematical problems to complicated science texts. Criterion tasks include different outcome measures that are relevant to student achievement, such as those tapping memory, problem solving, and comprehension. We attempted to provide thorough reviews for each technique, so this monograph is rather lengthy. However, we also wrote the monograph in a modular fashion, so it is easy to use. In particular, each review is divided into the following sections: General description of the technique and why it should work How general are the effects of this technique? 2a. Learning conditions 2b. Student characteristics 2c. Materials 2d. Criterion tasks Effects in representative educational contexts Issues for implementation Overall assessment The review for each technique can be read independently of the others, and particular variables of interest can be easily compared across techniques. To foreshadow our final recommendations, the techniques vary widely with respect to their generalizability and promise for improving student learning. Practice testing and distributed practice received high utility assessments because they benefit learners of different ages and abilities and have been shown to boost students' performance across many criterion tasks and even in educational contexts. Elaborative interrogation, self-explanation, and interleaved practice received moderate utility assessments. The benefits of these techniques do generalize across some variables, yet despite their promise, they fell short of a high utility assessment because the evidence for their efficacy is limited. For instance, elaborative interrogation and self-explanation have not been adequately evaluated in educational contexts, and the benefits of interleaving have just begun to be systematically explored, so the ultimate effectiveness of these techniques is currently unknown. Nevertheless, the techniques that received moderate-utility ratings show enough promise for us to recommend their use in appropriate situations, which we describe in detail within the review of each technique. Five techniques received a low utility assessment: summarization, highlighting, the keyword mnemonic, imagery use for text learning, and rereading. These techniques were rated as low utility for numerous reasons. Summarization and imagery use for text learning have been shown to help some students on some criterion tasks, yet the conditions under which these techniques produce benefits are limited, and much research is still needed to fully explore their overall effectiveness. The keyword mnemonic is difficult to implement in some contexts, and it appears to benefit students for a limited number of materials and for short retention intervals. Most students report rereading and highlighting, yet these techniques do not consistently boost students' performance, so other techniques should be used in their place (e.g., practice testing instead of rereading). Our hope is that this monograph will foster improvements in student learning, not only by showcasing which learning techniques are likely to have the most generalizable effects but also by encouraging researchers to continue investigating the most promising techniques. Accordingly, in our closing remarks, we discuss some issues for how these techniques could be implemented by teachers and students, and we highlight directions for future research.

https://www.wku.edu/senate/documents/improving_student_learning_dunlosky_2013.pdf

Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology

The anterior cingulate cortex (ACC) has been shown to respond to conflict between simultaneously active, incompatible response tendencies. This area is active during high-conflict correct trials and also when participants make errors. Here, we use the temporal resolution of high-density event-related potentials (ERPs) in combination with source localization to investigate the timing of ACC activity during conflict and error detection. We predicted that the same area of the ACC is active prior to high-conflict correct responses and following erroneous responses. Dipole modeling supported this prediction: The frontocentral N2, occurring prior to the response on correct conflict trials, and the ERN, occurring immediately following error responses, could both be modeled as having a generator in the caudal ACC, suggesting the same process to underlie both peaks. Modeling further suggested that the rostral area of the ACC was also active following errors, but later in time, contributing to the error positivity (PE), and peaking at 200-250 msec following the ERN peak. Despite the inherent limitations of source localization, these data may begin to shed light on the timing of action-monitoring processes. First, the time course of caudal ACC activity follows the time course as predicted by the conflict theory of this region. Second, caudal ACC activity might be temporally dissociated from rostral ACC activity during error trials, which possibly reflects a separate, affective component of the evaluative functions of the ACC.

The Timing of Action-Monitoring Processes in the Anterior Cingulate Cortex

Knowing how to manage one's own learning has become increasingly important in recent years, as both the need and the opportunities for individuals to learn on their own outside of formal classroom settings have grown. During that same period, however, research on learning, memory, and metacognitive processes has provided evidence that people often have a faulty mental model of how they learn and remember, making them prone to both misassessing and mismanaging their own learning. After a discussion of what learners need to understand in order to become effective stewards of their own learning, we first review research on what people believe about how they learn and then review research on how people's ongoing assessments of their own learning are influenced by current performance and the subjective sense of fluency. We conclude with a discussion of societal assumptions and attitudes that can be counterproductive in terms of individuals becoming maximally effective learners.

/pdf/self-regulated-learning-beliefs-techniques-and-illusions-3rocqc7w28.pdf

Self-regulated learning: beliefs, techniques, and illusions.

Handbook of motivation at school

This review builds on self-control theory (Carver & Scheier, 1998) to develop a theoretical framework for investigating associations of implicit theories with self-regulation. This framework conceptualizes self-regulation in terms of 3 crucial processes: goal setting, goal operating, and goal monitoring. In this meta-analysis, we included articles that reported a quantifiable assessment of implicit theories and at least 1 self-regulatory process or outcome. With a random effects approach used, meta-analytic results (total unique N = 28,217; k = 113) across diverse achievement domains (68% academic) and populations (age range = 5-42; 10 different nationalities; 58% from United States; 44% female) demonstrated that implicit theories predict distinct self-regulatory processes, which, in turn, predict goal achievement. Incremental theories, which, in contrast to entity theories, are characterized by the belief that human attributes are malleable rather than fixed, significantly predicted goal setting (performance goals, r = -.151; learning goals, r = .187), goal operating (helpless-oriented strategies, r = -.238; mastery-oriented strategies, r = .227), and goal monitoring (negative emotions, r = -.233; expectations, r = .157). The effects for goal setting and goal operating were stronger in the presence (vs. absence) of ego threats such as failure feedback. Discussion emphasizes how the present theoretical analysis merges an implicit theory perspective with self-control theory to advance scholarship and unlock major new directions for basic and applied research.

/pdf/mind-sets-matter-a-meta-analytic-review-of-implicit-theories-1tlp9rgtvr.pdf

Mind-Sets Matter: A Meta-Analytic Review of Implicit Theories and Self-Regulation.

Students’ beliefs and goals can powerfully influence their learning success. Those who believe intelligence is a fixed entity (entity theorists) tend to emphasize ’performance goals,’ leaving them vulnerable to negative feedback and likely to disengage from challenging learning opportunities. In contrast, students who believe intelligence is malleable (incremental theorists) tend to emphasize ’learning goals’ and rebound better from occasional failures. Guided by cognitive neuroscience models of top–down, goal-directed behavior, we use event-related potentials (ERPs) to understand how these beliefs influence attention to information associated with successful error correction. Focusing on waveforms associated with conflict detection and error correction in a test of general knowledge, we found evidence indicating that entity theorists oriented differently toward negative performance feedback, as indicated by an enhanced anterior frontal P3 that was also positively correlated with concerns about proving ability relative to others. Yet, following negative feedback, entity theorists demonstrated less sustained memory-related activity (left temporal negativity) to corrective information, suggesting reduced effortful conceptual encoding of this material–a strategic approach that may have contributed to their reduced error correction on a subsequent surprise retest. These results suggest that beliefs can influence learning success through top–down biasing of attention and conceptual processing toward goal-congruent information.

/pdf/why-do-beliefs-about-intelligence-influence-learning-success-1fagfa2lg9.pdf

Why do beliefs about intelligence influence learning success? A social cognitive neuroscience model

The relation between people's confidence in the accuracy of an erroneous response and their later performance was investigated. Most models of human memory suggest that the higher a person's confidence, the stronger the item (in the context of the eliciting cue) that is retrieved from memory. In recall, stronger associates to a cue interfere with competing associates more than do weaker associates. This state of affairs implies that errors endorsed with high, rather than low, confidence should be more difficult to correct by learning the correct response feedback. In contrast to the authors' expectations, highly confident errors were the most likely to be corrected in a subsequent retest. Participants nearly always endorsed the correct response in cases in which both the correct response and the original erroneous response were generated at retest, suggesting that people possess a refined metacognitive ability to know what is correct and incorrect.

Errors committed with high confidence are hypercorrected.

Most theories predict that when people indicate that they are highly confident they are producing their strongest responses. Hence, if such a high confidence response is in error it should be overwritten only with great difficulty. In contrast to this prediction, we have found that people easily correct erroneous responses to general information questions endorsed as correct with high-confidence, so long as the correct answer is given as feedback. Three potential explanations for this unexpected hypercorrection effect are summarized. The explanation that is tested here, in two experiments, is that after a person commits a high-confidence error the correct answer feedback, being surprising or unexpected, is given more attention than is accorded to the feedback to low-confidence errors. This enhanced attentional capture leads to better memory. In both experiments, a tone detection task was presented concurrently with the corrective feedback to assess the attentional capture of feedback stimuli. In both, tone detection was selectively impaired during the feedback to high confidence errors. It was also negatively related to final performance, indicating that the attention not devoted to the tone detection was effectively engaged by the corrective feedback. These data support the attentional explanation of the high-confidence hypercorrection effect.

/pdf/the-correction-of-errors-committed-with-high-confidence-4gaxu49pns.pdf

The correction of errors committed with high confidence

Neural correlates of error detection and correction in a semantic retrieval task.

http://www.columbia.edu/cu/psychology/metcalfe/PDFs/Cosentino.pdf

Brady Butterfield

Papers

Why do beliefs about intelligence influence learning success? A social cognitive neuroscience model

Errors committed with high confidence are hypercorrected.

The correction of errors committed with high confidence

Neural correlates of error detection and correction in a semantic retrieval task.

Objective metamemory testing captures awareness of deficit in Alzheimer's disease.