Title

Using Neurophysiological Data To Inform Feedback Timing: A Pilot Study

Keywords

adaptive intelligent systems; EEG; Feedback; physiological measures; simulation based training

Abstract

In an effort to achieve a level of knowledge comparable to that which typically results from individual tutoring, innovative models of adaptive computer-based training are continually being tested and refined. Despite these efforts, adaptive computerized training programs still fall significantly short of the gold standard of one-on-one instruction. In response, this study used a previously developed model defining when to apply instructional feedback during learning in order to improve efficiency. Specifically, we compared the combination of performance and neuro-physiological indices to performance alone as indicators for when to adapt training. Contrary to our hypotheses, this study failed to demonstrate positive impact on knowledge acquisition, knowledge application, perceived cognitive load, or training efficiency. However, based on observational data, it is suspected that participants in neither group possessed enough available working memory capacity to attend to the supporting material. Consequently, this may account for the lack of differential findings. © 2011 Springer-Verlag.

Publication Date

7-19-2011

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

6780 LNAI

Number of Pages

265-274

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-642-21852-1_33

Socpus ID

79960301573 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/79960301573

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