Contributions of minimax theory to instructional decision making in intelligent tutoring systems

Share/Save/Bookmark

Vos, H.J. (1999) Contributions of minimax theory to instructional decision making in intelligent tutoring systems. Computers in Human Behavior, 15 (5). pp. 531-548. ISSN 0747-5632

[img] PDF
Restricted to UT campus only
: Request a copy
210kB
Abstract:The purpose of this paper is to formulate decision rules for adapting the appropriate amount of instruction to learning needs in intelligent tutoring systems. The framework for the approach is derived from minimax decision theory (minimum information approach), i.e. optimal rules are obtained by minimizing the maximum expected loss associated with each possible decision rule. The binomial model was assumed for the conditional probability of a correct response given the true level of functioning, whereas threshold loss was adopted for the loss function involved. A simple decision rule is given for which only the minimum true level of functioning required for being a ‘true master’ and the value of the loss ratio have to be specified in advance by the decision-maker. The procedures are demonstrated for the problem of determining the optimal number of interrogatory examples for concept-learning in the Minnesota Adaptive Instructional System (MAIS). The Bayesian decision component assumed in the MAIS and the minimax strategy are compared with each other in terms of their weak and strong points. An empirical example of determining the optimal number of interrogatory examples for concept-learning in medicine concludes the paper.
Item Type:Article
Copyright:© 1999 Elsevier Science
Faculty:
Behavioural Sciences (BS)
Research Group:
Link to this item:http://purl.utwente.nl/publications/61580
Official URL:http://dx.doi.org/10.1016/S0747-5632(99)00035-7
Export this item as:BibTeX
EndNote
HTML Citation
Reference Manager

 

Repository Staff Only: item control page

Metis ID: 135417