Analyzing Student Motivation and Self-Efficacy in Using an Intelligent Tutoring System

  • Authors:

  • Leen-Kiat Soh;Lee Dee Miller

  • Affiliations:

  • Department of Computer Science and Engineering, University of Nebraska, Lincoln, NE 68588-0115 USA, { lksoh, lmille }@cse.unl.edu;Department of Computer Science and Engineering, University of Nebraska, Lincoln, NE 68588-0115 USA, { lksoh, lmille }@cse.unl.edu

  • Venue:
  • Proceedings of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation
  • Year:
  • 2005

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Abstract

In this paper, we analyze how traits such as student motivation and self-efficacy impact students' perception of the usefulness of an intelligent tutoring system (ITS). We have built and deployed an ITS called Intelligent Learning Materials Delivery Agent (ILMDA) in a CS1 course. This ITS presents instructional content such as tutorials, examples, and problems to the students with a bare bone minimal interface. The students interact with the system through a graphical user interface. The agent reasoning module of the ITS monitors the interaction, models the students, and selects the next example or problem to present to the student. Here we analyze the results of a qualitative survey of students' perception of this system, using data mining techniques such as correlation and contrast rules. We report on how the interface, the instructional content, and student motivation and self-efficacy relate to each other.