Test-sheet composition using immune algorithm for E-learning application

Authors:
Chin-Ling Lee;Chih-Hui Huang;Cheng-Jian Lin
Affiliations:
Dept. of Applied Foreign Languages, Chaoyang University of Technology, Wufeng, Taichung County, Taiwan, R.O.C.;Dept. of Computer Science and Information Engineering, Chaoyang University of Technology, Wufeng, Taichung County, Taiwan, R.O.C.;Dept. of Computer Science and Information Engineering, Chaoyang University of Technology, Wufeng, Taichung County, Taiwan, R.O.C.
Venue:
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Year:
2007

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Abstract

In this paper, a novel approach Immune Algorithm (IA) is applied to improve the efficiency of composing near optimal test sheet from item banks to meet multiple assessment criteria. We compare the results of immune and Genetic Algorithm (GA) to compose test-sheets for multiple assessment criteria. From the experimental results, the IA approach is desirable in composing near optimal test-sheet from large item banks. And objective conceptual vector (OCV) and objective testsheet test item numbers (M) can be effectually achieved. Hence it can support the needs of precisely evaluating student's learning status. We successfully extend the applications of artificial intelligent - Immune to the educational measurement.