Faculty Advisor or Committee Member

Dr. Ivon Arroyo, Advisor

Faculty Advisor or Committee Member

Dr. Ryan S. Baker, Committee Member

Faculty Advisor or Committee Member

Dr. Joseph Beck, Committee Member

Faculty Advisor or Committee Member

Dr. Kaska Porayska-Pomsta, Committee Member

Identifier

etd-072718-114345

Abstract

Student affect can play a profoundly important role in students' post-school lives. Understanding students' affective states within online learning environments in particular has become an important matter of research, as digital tutoring systems have the potential to intervene at the moment that students are struggling and becoming frustrated, bored or disengaged. However, despite the importance of assessing students' affective states, there is no clear consensus about what emotions are most important to assess, nor how these emotions can be best measured.

This dissertation investigates students’ self-reports of their emotions and causal attributions of those emotions collected while they are solving math problems within a mathematics tutoring system. These self-reports are collected in two conditions: through limited choice Likert response and through open response text boxes. The conditions are combined with students’ cognitive attributions to describe epistemic (neither purely affective nor purely cognitive) emotions in order to explain the relationship between observable student behaviors in the MathSpring.org tutoring system and student affect. These factors include beliefs, expectations, motivations, and perceptions of ability and control. A special emphasis of this dissertation is on analyzing the role of causal attributions for the events and appraisals of the learning environment, as possible causes of student behaviors, performance, and affect.

Publisher

Worcester Polytechnic Institute

Degree Name

PhD

Department

Learning Sciences and Technologies

Project Type

Dissertation

Date Accepted

2018-07-24

Accessibility

Unrestricted

Subjects

affect emotion self report measures education data mining learning analytics EDM

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