Neurocognitive mechanisms of the “testing effect”: A review

Broek, Gesa van den; Takashima, Atsuko; Wiklund-Hörnqvist, Carola; Wirebring, Linnea Karlsson; Segers, Eliane; Verhoeven, Ludo; Nyberg, Lars

doi:10.1016/j.tine.2016.05.001

Cited by 79 publications

(68 citation statements)

References 98 publications

(223 reference statements)

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“…It should be noted, however, that the tasks employed here are calibrated to the type of sample used: The complex span tasks were developed and are routinely used in university student populations (Redick et al, 2012; see section Normative Sample). The test of GCA was originally developed as a selection tool to determine whether a candidate has the necessary intellectual ability to perform well in cognitively demanding jobs and is normed for university graduates (Van Bebber et al, 2010). Thus, while the performance ranges on these measures might be restricted relative to the general population, we believe that the tasks used here are well-calibrated to detect differences within the narrower range of our homogeneous sample.…”

Section: Discussionmentioning

confidence: 99%

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Exploration of the Rate of Forgetting as a Domain-Specific Individual Differences Measure

2018

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Learners differ in their learning aptitude. Modern computerized fact-learning systems take these individual differences into account by adapting repetition schedules to the learner's characteristics. Adaptation is based on monitoring responses during learning and using these responses to inform the model's decisions about when to introduce and repeat material by updating the model's internal parameters. Typically, adaptive systems start a learning session with a set of default parameters, with these parameters being updated and adapted to the learner's characteristics when responses are collected. Here we explore whether domain-general individual differences such as working-memory capacity or measures of general intelligence, which can be assessed prior to learning sessions, can inform the choice of initial model parameters. Such an approach is viable if the domain-general individual differences are related to the model parameters estimated during learning. In the current study, we asked participants to learn factual information, and assessed whether their learning performance, operationalized as (1) a model-parameter that captures the rate of forgetting, and (2) the results on an immediate and delayed post-test, was related to two common measures of individual differences: working memory capacity (WMC) and general cognitive ability (GCA). We failed to find evidence in favor for such relations, suggesting that, at least in this relatively small and homogeneous sample, executive functioning and attentional control did not play important roles in predicting delayed recall. The model parameters estimated during learning, on the other hand, are highly correlated with delayed recall of the studied material.

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Section: Discussionmentioning

confidence: 99%

“…Subsequently, we assessed the participants' general cognitive abilities (GCA) by administering the Q1000 Cognitive Capacity test (Van Bebber et al, 2010), which took participants between 32 and 87 min to complete. Mean completion time was 56 min.…”

Section: Sessionmentioning

confidence: 99%

Exploration of the Rate of Forgetting as a Domain-Specific Individual Differences Measure

2018

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“…We therefore suggest that the retroactive strengthening of episodic memory that we observed resulted from reconsolidation. Alternatively, the effect of a reminder on episodic memory may have resulted from a “testing effect”, reflecting re-encoding or strengthening of retrieval processes 51 , 52 . First, it is important to note that the reminder did not explicitly test episodic memory.…”

Section: Discussionmentioning

confidence: 99%

A reminder before extinction strengthens episodic memory via reconsolidation but fails to disrupt generalized threat responses

Kroes

Dunsmoor

Lin

et al. 2017

Sci Rep

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A reminder can temporarily renew flexibility of consolidated memories, referred to as reconsolidation. Pavlovian threat-conditioning studies suggest that a reminder can renew flexibility of threat responses but that episodic memories remain stable. In contrast, outside the threat-conditioning domain, studies testing memory for word lists or stories find that a reminder can renew flexibility of episodic memory. This discrepancy in findings leaves it unclear if episodic memories reconsolidate, or only Pavlovian responses. Here we unite the different approaches in the field and show that a reminder can retroactively strengthen episodic memory for Pavlovian threat-conditioned events, but that, in contrast to threat-conditioning studies with simple sensory stimuli, extinction after a reminder fails to prevent recovery of generalized threat responses. Our results indicate the episodic memories also reconsolidate, allowing strengthening of relevant memories. These findings also suggest that generalized threat responses and episodic memories are less susceptible to be modified by reminder-interventions procedures.

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“…A comprehensive discussion of all theories and research perspectives from the testenhanced learning and broader transfer literatures is beyond the scope of this review (for discussions of the former, see Delaney, Verkoeijen, & Spirgel, 2010;Karpicke, Lehman, & Aue, 2014;Roediger & Butler, 2011;Roediger & Karpicke, 2006;van den Broek et al, 2016; for coverage of the latter, see Cormier & Hagman, 1987;Ellis, 1965;Haskell, 2001;McGeoch, 1942;Mestre, 2005;Singley & Anderson, 1989). However, several theoretical perspectives provide relevant background and are briefly summarized here.…”

Section: Theorizing Relevant To Transfer Of Test-enhanced Learningmentioning

confidence: 99%

Pan and Rickard (2018) Transfer of test-enhanced learning meta-analysis (preprint)

Pan¹

2018

Preprint

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Attempting recall of information from memory, as occurs when taking a practice test, is one of the most potent training techniques known to learning science. However, does testing yield learning that transfers to different contexts? In the present article, we report the findings of the first comprehensive meta-analytic review into that question. Our review encompassed 192 transfer effect sizes extracted from 122 experiments and 67 published and unpublished articles (N = 10,382) comprising over 40 years of research. A random-effects model revealed that testing can yield transferrable learning as measured relative to a non-testing reexposure control condition (d = 0.40, 95% CI [0.31, 0.50]). That transfer of learning is greatest across test formats, to application and inference questions, to problems involving medical diagnoses, and to mediator and related word cues; it is weakest to rearranged stimulus-response items, to untested materials seen during initial study, and to problems involving worked examples. Moderator analyses further indicated that response congruency and elaborated retrieval practice, as well as initial test performance, strongly influence the likelihood of positive transfer. In two assessments for publication bias (using PET-PEESE and various selection methods), the moderator effect sizes were minimally affected. However, the intercept predictions were substantially reduced, often indicating no positive transfer when none of the aforementioned moderators are present. Overall, our results motivate a three-factor framework for transfer of test-enhanced learning and have practical implications for the effective use of practice testing in educational and other training contexts.

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Neurocognitive mechanisms of the “testing effect”: A review

Cited by 79 publications

References 98 publications

Exploration of the Rate of Forgetting as a Domain-Specific Individual Differences Measure

Exploration of the Rate of Forgetting as a Domain-Specific Individual Differences Measure

A reminder before extinction strengthens episodic memory via reconsolidation but fails to disrupt generalized threat responses

Pan and Rickard (2018) Transfer of test-enhanced learning meta-analysis (preprint)

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