IMPACTS OF USER SENTIMENT ON INFORMATION RECALL, INTRINSIC MOTIVATION, AND ENGAGEMENT IN THE CONTEXT OF INTELLIGENT TUTORING SYSTEMS
Open Access
Author:
Metaxas, Luke Richard
Area of Honors:
Information Sciences and Technology
Degree:
Bachelor of Science
Document Type:
Thesis
Thesis Supervisors:
Frank Edward Ritter, Thesis Supervisor Dr. Edward J Glantz, Thesis Honors Advisor
Keywords:
sentiment motivation engagement intelligent tutoring systems computer-based instruction affect flow self-determination theory
Abstract:
The study assesses the learning impact of an individual’s sentiments (emotional associations) in the context of intelligent tutoring systems. Assessed learning outcomes include information recall, intrinsic motivation, and engagement. Seventy volunteers took two computer-based tutors and provided self-report measures throughout their learning. The learning impacts of topic sentiment and learning-medium sentiment were measured separately and compared. Results showed positive linear relationships between net sentiments and intrinsic motivation and net sentiments and engagement. A negative linear relationship between negative sentiments and information recall was also identified. Findings were summarized, and four CBI design recommendations were provided. Recommendations include: to use learner emotion data in the form of sentiments to better understand learning outcomes, to align sentiment measurement strategies with the tutor’s purpose, to account for the impact of prior sentiments, and to monitor sentiment change.
