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
Copyright Status
Unknown
Socpus ID
84889836670 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84889836670
STARS Citation
Vogel-Walcutt, Jennifer J.; Carper, Teresa Marino; Bowers, Clint; and Nicholson, Denise, "Using Learners' Internal States To Drive Feedback Decisions" (2013). Scopus Export 2010-2014. 5930.
https://stars.library.ucf.edu/scopus2010/5930