An Artificial Intelligence Approach to Analyzing Student Errors in Statistics

Book: 
Collegiate Microcomputer
Authors: 
Sebrechts, M. M., & Schooler, L. J.
Type: 
Journal Article
Category: 
Other
Volume: 
5(1)
Pages: 
82-86
Year: 
1987
Abstract: 

Describes the development of an artificial intelligence system called GIDE that analyzes student errors in statistics problems by inferring the students' intentions. Learning strategies involved in problem solving are discussed and the inclusion of goal structures is explained. (LRW)

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education