Intelligent tutoring systems and SUMMIT: design and implementation

Open Access
Casale, Francis Burke
Area of Honors:
Information Sciences and Technology
Bachelor of Science
Document Type:
Thesis Supervisors:
  • Steven Raymond Haynes, Thesis Supervisor
  • Rosalie Ocker, Honors Advisor
  • learning
  • tutoring
  • application design
Tutoring is regarded by some as the most effective form of learning, and over the years, researchers have worked to create “intelligent tutoring systems” to quickly and reliably train students in a particular area. This thesis proposes a design for an intelligent tutoring system within an existing application: SUMMIT. The rationale of this design is based on research in learning, and the past, present and future of intelligent tutoring systems. The design is expressed through diagrams based in the Unified Modeling Language (UML), and screenshots and mockups are created in order to visualize the design. This work tackles a number of the problems associated with previous intelligent tutoring systems by taking a relatively unique approach: limiting the requirement that the system must be fully “intelligent” in the traditional sense. Instead, the design prioritizes the process of task decomposition, which takes a complex skill or knowledge area and breaks it down into smaller components. Learners receive their knowledge in more manageable “chunks” that, when together, form the intended framework. In the future, it is suggested that work be done to fully implement the design proposed in this thesis. If successful, a completely flexible intelligent tutoring system could have far-reaching effects on the training and education industry.