1. The Preference Matrix As A Course Design Tool John Paxton Montana State University Universität Leipzig Koli Calling Saturday, November 11, 2006

2. Outline I.Introduction II.Application III.Evaluation IV.Discussion

3. I. Introduction

4. Preference Matrix Developed by Stephen and Rachel Kaplan at The University of Michigan Based on evolutionary psychology Each individual must build a cognitive map in order to survive A cognitive map allows recognition, prediction and evaluation

5. Familiarity Matrix Low Preference High Preference Low FamiliarityStrangeFascinating High FamiliarityBoringComfortable

6. Preference Matrix Makes SenseInvolvement PresentCoherenceComplexity FutureLegibilityMystery

7. II. Application

8. Preference Matrix Pedagogy Connect new knowledge to existing knowledge  “makes sense” Don’t overwhelm short-term memory  “makes sense” Material should engage learner  “involvement” Background of learner must be roughly understood  “involvement”

9. CS 436 A senior level course that introduces artificial intelligence Making sense: clear objectives, clear syllabus, all graded work is related to the objectives, clear presentation Involvement: engaging assignments, classroom participation

10. III. Evaluation

11. Evaluation Fall 2004 – Spring 2006 Senior level computer science courses at Montana State University 2 offerings of CS 436 (33 students) 17 other offerings (225 students)

12. Evaluation 1.How does this course compare with similar technical courses? 2.What is your level of interest in taking an advanced course? 3.Did you find this course challenging? 4.Were the objectives of the course clearly stated?

13. Evaluation 5.Were the objectives of the course met? 6.How important were the lectures? 7.How important were the assignments/programs? 8.How important were the tests/quizzes?

14. Evaluation Question¬AI meanAI meanσImprove 12.191.580.9651% 22.531.671.2956% 31.921.520.8443% 41.831.240.9571%

15. Evaluation Question¬AI meanAI meanσImprove 51.931.330.9165% 61.791.520.9934% 71.821.330.9160% 82.041.940.9810%

16. IV. Discussion What are appropriate research methodologies for measuring the impact of the preference matrix in a convincing manner?