Review of Adaptive Training System Techniques

Landsberg, Carla R.; Astwood, Randy S.; Buskirk, Wendi L. Van; Townsend, Lisa; Steinhauser, Natalie B.; Mercado, Alyssa D.

doi:10.1080/08995605.2012.672903

Cited by 41 publications

(15 citation statements)

References 37 publications

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“…In contrast to the preceding experiments, which administered feedback on a trial-by-trial basis, Experiment 4 provided observers with outcome feedback about their face matching performance (see, e.g., Kulhavy & Stock, 1989;Kluger & DeNisi, 1996;Mory, 2004;Shute, 2008;Narciss, 2008;Landsberg et al, 2012). This was delivered by providing each observer with a percentage score of the total number of their correct responses at the end of a block of trials.…”

Section: Methodsmentioning

confidence: 99%

The Effect of Feedback on Face‐Matching Accuracy

Alenezi

Bindemann

2013

Applied Cognitive Psychology

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The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record. EnquiriesFor any further enquiries regarding the licence status of this document, please contact: researchsupport@kent.ac.uk If you believe this document infringes copyright then please contact the KAR admin team with the take-down information provided at http://kar.kent.ac.uk/contact.html Alenezi, Hamood and Bindemann, Markus (2013) Citation for published version AbstractIn face matching, observers have to decide if two photographs depict the same person or different people. This is a remarkably difficult task so the current study investigated whether it can be improved when observers receive feedback for their performance. In five experiments, observersÕ initial matching performance was recorded before feedback for their accuracy was administered across three blocks. Improvements were then assessed with faces that had been seen previously with or without feedback and with completely new, previously unseen faces. In all experiments, feedback failed to improve face-matching accuracy. However, trial-by-trial feedback helped to maintain accuracy at baseline level after feedback was withdrawn again, even with new faces (Experiments 1 to 3). By contrast, when no feedback was given throughout the experiment (Experiments 1 to 3) or when outcome feedback was administered at the end of blocks (Experiments 4 and 5), a continuous decline in matching accuracy was found, whereby observers found it increasingly difficult to tell different facial identities apart. A sixth experiment showed that this decline in accuracy continues throughout when the matching task is prolonged substantially. Together, these findings indicate that observers find it increasingly difficult to differentiate faces in matching tasks over time, but trial-by-trial feedback can help to maintain accuracy. The theoretical and practical implications of these findings are discussed.3

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Section: Methodsmentioning

confidence: 99%

The Effect of Feedback on Face‐Matching Accuracy

Alenezi

Bindemann

2013

Applied Cognitive Psychology

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“…Many authors (Cook 2005;Landsberg et al 2012) have suggested that increased personalization (i.e. adaptive learning) gives online learning an efficiency advantage.…”

Section: Myth 2 Online Learning Is Cheap and Easy To Implementmentioning

confidence: 99%

The value of online learning and MRI: Finding a niche for expensive technologies

Cook

2014

Medical Teacher

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“…All three models currently lack a theory of how individual differences in aptitude, personality, and prior knowledge affect performance (Ackerman, 1987;Landsberg et al, 2012). All three models currently lack a theory of how individual differences in aptitude, personality, and prior knowledge affect performance (Ackerman, 1987;Landsberg et al, 2012).…”

Section: Account For Effects Of Training Variables On Learning and Rementioning

confidence: 99%

Evaluating the Theoretic Adequacy and Applied Potential of Computational Models of the Spacing Effect

et al. 2018

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The spacing effect is among the most widely replicated empirical phenomena in the learning sciences, and its relevance to education and training is readily apparent. Yet successful applications of spacing effect research to education and training is rare. Computational modeling can provide the crucial link between a century of accumulated experimental data on the spacing effect and the emerging interest in using that research to enable adaptive instruction. In this paper, we review relevant literature and identify 10 criteria for rigorously evaluating computational models of the spacing effect. Five relate to evaluating the theoretic adequacy of a model, and five relate to evaluating its application potential. We use these criteria to evaluate a novel computational model of the spacing effect called the Predictive Performance Equation (PPE). Predictive Performance Equation combines elements of earlier models of learning and memory including the General Performance Equation, Adaptive Control of Thought-Rational, and the New Theory of Disuse, giving rise to a novel computational account of the spacing effect that performs favorably across the complete sets of theoretic and applied criteria. We implemented two other previously published computational models of the spacing effect and compare them to PPE using the theoretic and applied criteria as guides.

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Review of Adaptive Training System Techniques

Cited by 41 publications

References 37 publications

The Effect of Feedback on Face‐Matching Accuracy

The Effect of Feedback on Face‐Matching Accuracy

The value of online learning and MRI: Finding a niche for expensive technologies

Evaluating the Theoretic Adequacy and Applied Potential of Computational Models of the Spacing Effect

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