Student Modelling for Procedural Problem Solving

Noboru MATSUDA  Toshio OKAMOTO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E77-D   No.1   pp.49-56
Publication Date: 1994/01/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Intelligent CAI and Hypermedia)
Category: 
Keyword: 
artificial intelligence,  educational systems,  intelligent tutoring systems,  student modelling,  

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Summary: 
This study is intended to investigate a method to diagnose the student model in the domain of procedural problem solving. In this domain, the goal of an instruction should be to understand the processes of solving given problems, and to understand the reasons why problems can be solved by using sertain knowledge; the acquisition of problem solving skills might not be the intrinsic instructional goals. The tutoring systems in this domain must understand the effect of each problem solving operators, as well as when to implement these operators in order to effectively solve given problems. We have been studying and developing a system which deals with student modelling in the domain of procedural problem solving. We believe that the two types of knowledge should be clearly defined for the diagnosing tasks; effective knowledge (EK) and principle knowledge (PK). The former is the knowledge which is explicitly applied by students throughout problem solving processes, and the latter is the one which gives the justifications of the EK. We have developed a student model diagnosing system which infers students' knowledge structure pertaining to PK, based on the precedently manipulated student model about EK. This student model diagnosing method requires knowledge which argues the relationship between the PK and the EK. This knowledge plays the very important role in our system, and it's hard to describe such knowledge properly by hand. In this paper, we provide a student model diagnosing system which has the knowledge acquiring function to learn the relationship between EK and PK. The system acquires this knowledge through its own problem solving experience. Based on the student model and the acquired relational knowledge, the system can give students proper instructions about construction of EK with explanations in terms of PK. The system has been partly implemented with CESP language on a UNIX workstation.