The Affective Impact of Tutor Questions: Predicting Frustration and Engagement [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (9th, Raleigh, NC, Jun 29-Jul 2, 2016).

Autor/inn/en	Vail, Alexandria K.; Wiggins, Joseph B.; Grafsgaard, Joseph F.; Boyer, Kristy Elizabeth; Wiebe, Eric N.; Lester, James C.
Titel	The Affective Impact of Tutor Questions: Predicting Frustration and Engagement [Konferenzbericht] Paper presented at the International Conference on Educational Data Mining (EDM) (9th, Raleigh, NC, Jun 29-Jul 2, 2016).
Quelle	(2016), (8 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Affective Behavior; Questioning Techniques; Emotional Response; Nonverbal Communication; College Students; Student Behavior; Tutoring; Computer Mediated Communication; Educational Technology; Technology Uses in Education; North Carolina + Suchen Sie Ihr Suchwort? Affective disturbance; Active behaviour; Affektive Störung; Befragungstechnik; Fragetechnik; Emotionales Verhalten; Non-verbal communication; Nonverbale Kommunikation; Collegestudent; Student behaviour; Schülerverhalten; Förderkonzept; Nachhilfeunterricht; Computerkonferenz; Unterrichtsmedien; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen
Abstract	Tutorial dialogue is a highly effective way to support student learning. It is widely recognized that tutor dialogue moves can significantly influence learning outcomes, but the ways in which tutor moves, student affective response, and outcomes are related remains an open question. This paper presents an analysis of student affective response, as evidenced by multimodal data streams, immediately following tutor questions. The findings suggest that students' affect immediately following tutor questions is highly predictive of end-of-session self-reported engagement and frustration. Notably, facial action units which have been associated with emotional states such as embarrassment, disgust, and happiness appear to play important roles in students' expressions of frustration and engagement during learning. This line of investigation will aid in the development of a deeper understanding of the relationships between tutorial dialogue and student affect during learning. [For the full proceedings, see ED592609.] (As Provided).
Anmerkungen	International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01