Faculty Advisor or Committee Member

Ivon Arroyo, Advisor

Faculty Advisor or Committee Member

Craig Wills

Faculty Advisor or Committee Member

Joseph Beck

Co-advisor

Neil Heffernan

Identifier

etd-012715-143042

Abstract

Two of the major goals in Educational Data Mining are determining students’ state of knowledge and determining their affective state. It is useful to be able to determine whether a student is engaged with a tutor or task in order to adapt to his/her needs and necessary to have an idea of the students' knowledge state in order to provide material that is appropriately challenging. These two problems are usually examined separately and multiple methods have been proposed to solve each of them. However, little work has been done on examining both of these states in parallel and the combined effect on a student’s performance. The work reported in this thesis explores ways to observe both behavior and performance in order to more fully understand student state.

Publisher

Worcester Polytechnic Institute

Degree Name

MS

Department

Computer Science

Project Type

Thesis

Date Accepted

2015-01-27

Accessibility

Unrestricted

Subjects

engagement, educational data mining, Bayesian networks, affect, knowledge tracing, student modeling, intelligent tutoring system

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