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ERIC Number: ED592731
Record Type: Non-Journal
Publication Date: 2016
Pages: 8
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
The Affective Impact of Tutor Questions: Predicting Frustration and Engagement
Vail, Alexandria K.; Wiggins, Joseph B.; Grafsgaard, Joseph F.; Boyer, Kristy Elizabeth; Wiebe, Eric N.; Lester, James C.
International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (9th, Raleigh, NC, Jun 29-Jul 2, 2016)
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.]
International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: National Science Foundation (NSF)
Authoring Institution: N/A
Identifiers - Location: North Carolina
Grant or Contract Numbers: IIS1409639; CNS1453520