Literaturnachweis - Detailanzeige
Autor/inn/en | Feng, Shi; Stewart, Janay; Clewley, Danielle; Graesser, Arthur C. |
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Titel | Emotional, Epistemic, and Neutral Feedback in AutoTutor Trialogues to Improve Reading Comprehension [Konferenzbericht] Paper presented at the International Conference on Artificial Intelligence in Education (17th, 2015). |
Quelle | (2015), (5 Seiten)
PDF als Volltext |
Zusatzinformation | Weitere Informationen |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Monographie |
Schlagwörter | Intelligent Tutoring Systems; Educational Technology; Technology Uses in Education; Feedback (Response); Emotional Response; Nonverbal Communication; Preferences; Student Attitudes; Motivation; Undergraduate Students; Adult Literacy; Reading Comprehension; Tennessee (Memphis) |
Abstract | We manipulated three types of short feedback (emotional, epistemic, and neutral) in an intelligent tutoring system designed to help struggling adult readers improve reading comprehension strategies. We conducted our research on college students to eventually compare with the targeted adult population. We also recorded their facial emotions. Although participants self-reported a preference for emotional feedback, there were no differences in individual motivation or usefulness ratings between emotional and epistemic feedback. Analysis from coded facial emotions indicated that participants tended to be more sensitive to epistemic feedback than emotional feedback when using AutoTutor-CSAL. [This paper was published in: C. Conati, N. Heffernan, A. Mitrovic, M. F. Verdejo (Eds.), "Proceedings of the 17th International Conference on Artificial Intelligence in Education" (pp. 570-573). Cham: Springer.] (As Provided). |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2020/1/01 |