Title

Using Learners' Internal States To Drive Feedback Decisions

Abstract

The overarching goal of learner assessments is to identify areas of skill and deficit and to use this information to guide future instruction or error correction through feedback. To date, a variety of methods have been used to better understand individual learners. However, the tools used to assess learners' internal states have only allowed researchers to infer these states and, as a result, the information provided lacks the prescriptive specificity needed to most appropriately address learners' needs. The technological advances of current neuro-physiological measures may provide such specificity in real-time learning environments. These data show preliminary support for the use of electroencephalography measurements of workload and engagement to predict learning and knowledge acquisition. Additionally, the data suggest that the relation-ship between these two internal states may differ based on the level of information being assessed. Copyright 2013 by Human Factors and Ergonomics Society, Inc.

Publication Date

12-13-2013

Publication Title

Proceedings of the Human Factors and Ergonomics Society

Number of Pages

2086-2090

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1177/1541931213571465

Socpus ID

84889836670 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84889836670

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