Paper Info
Title
Predicting learner engagement during well-defined and Ill-defined computer-based intercultural interactions
Abstract
This article reviews the first of two experiments investigating the effect tailoring of training content has on a learner's perceived engagement, and to examine the influence the Big Five Personality Test and the Self-Assessment Manikin (SAM) mood dimensions have on these outcome measures. A secondary objective is to then correlate signals from physiological sensors and other variables of interest, and to develop a model of learner engagement. Self-reported measures were derived from the engagement index of the Independent Television Commission-Sense of Presence Inventory (ITC-SOPI). Physiological measures were based on the commercial Emotiv Epoc Electroencephalograph (EEG) braincomputer interface. Analysis shows personality factors to be reliable predictors of general engagement within well-defined and ill-defined tasks, and could be used to tailor instructional strategies where engagement was predicted to be nonoptimal. It was also evident that Emotiv provides reliable measures of engagement and excitement in near real-time.
Year
DOI
Venue
2011
10.1007/978-3-642-24600-5_57
ACII (1)
Keywords
Field
DocType
ill-defined computer-based intercultural interaction,reliable predictor,reliable measure,physiological sensor,general engagement,physiological measure,engagement index,commercial emotiv epoc electroencephalograph,personality test,learner engagement,independent television commission-sense,eeg
Social psychology,Mood,Big Five personality traits,Communication,Psychology,Learner engagement,Personality
Conference
Volume
ISSN
Citations 
6974
0302-9743
7
PageRank 
References 
Authors
0.71
6
4
Name
Order
Citations
PageRank
Benjamin S. Goldberg1226.34
Robert A. Sottilare25112.64
Keith W. Brawner3457.84
Heather K. Holden4223.18