CPI 494 - 1001:  Intelligent interactive instructional systems (class number 23006)

Graduate students please enroll in CPI 598 - 1002 (class number 26792)

Tues & Thurs 1:30-2:45; BYAC 260

 

Instructor information:

Spring 2009  Kurt VanLehn, kurt.vanlehn@asu.edu, http://www.public.asu.edu/~kvanlehn/

 

Catalog description

Intelligent interactive instructional systems serve as tutors, as learning companions or both.  This course introduces their design, the technology that powers them, the learning theories that motivate them and results from experimental evaluations. 

 

Course Objectives and Outcomes

Participants who have taken this course should have advanced understanding of Intelligent Tutoring and Learning Companion systems that includes:

 

  1. Understanding, from firsthand experience, the differences between intelligent instructional systems and conventional, less intelligent instructional systems.
  2. Understanding how to design and implement an intelligent instructional system, including both tutors and companions.
  3. Understanding current, practical theories of human learning and their relationship to intelligent instructional systems.
  4. Understanding how such systems have used advanced technology, such as speech input/output, 3D gaming environments and artificial intelligence.
  5. Understanding how to evaluate such systems, and the kinds of results that have been obtained so far.
  6. Understanding enculturation, scale-up and commercialization issues.

 

Grading

Grades will be based on class participation (30%), exams (30%), and a project (40%). 

 

Course organization

As the class progresses, we will evolve a general framework for comparing and contrasting intelligent interactive instructional systems.  An initial version of the framework appears below, and will be explained in the first lecture. The framework is intended to help us understand these systems more deeply despite the appalling inconsistency and vagueness in the literature that describes them.  Often, the only way to truly understand one of these systems, especially the more innovative ones, is to actually use it.  Thus, each of the modules in the course is centered around a prototypical system which, if at all possible, we will download and use. 

 

Initial Framework

·         Step loop

·         User interface

·         Interpreting student actions

·         Suggesting good actions

·         Feedback and hints

·         Task selection

·         Assessment

·         Authoring and the software development

·         Evaluations

·         Dissemination

 

Course modules (in chronological order)

  1. Cognitive tutors and other model-tracing tutors
  2. The Andes tutor and other canvas-based tutors
  3. SQL and other constraint-based tutors
  4. Wayang Outpost and affective learning companions
  5. The SQL Tutor and other constraint-based tutors
  6. Betty’s Brain and other teachable agents
  7. AutoTutor, Atlas, Criterion and other natural language systems
  8. Simulations and games e.g., AETS, SASO-ST, Crystal Island, River City
  9. Project presentations

 

To see the course schedule, with links to readings, exercises and downloads, click here.