By Topic

An Automated Decision System for Computer Adaptive Testing Using Genetic Algorithms

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Phankokkruad, M. ; Dept. of Comput. Educ., King Mongkut''s Univ. of Technol., Bangkok ; Woraratpanya, K.

This paper proposes an approach to solve the triangle decision tree problem for computer adaptive testing (CAT) using genetic algorithms (GAs). In this approach, item response theory (IRT) parameters composed of discrimination, difficulty, and guess are firstly obtained and stored in an item bank. Then a fitness function, which is based on IRT parameters, of GAs for obtaining an optimal solution is set up. Finally, the GAs is applied to the parameters of the item bank so that an optimal decision tree is generated. Based on a six-level triangle-decision tree for examination items, the experimental results show that the optimal decision tree can be generated correctly when compared with the standard patterns.

Published in:

Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2008. SNPD '08. Ninth ACIS International Conference on

Date of Conference:

6-8 Aug. 2008