標題: An Adaptive Test Sheet Generation Mechanism Using Genetic Algorithm
作者: Lin, Huan-Yu
Su, Jun-Ming
Tseng, Shian-Shyong
資訊工程學系
Department of Computer Science
公開日期: 2012
摘要: For test-sheet composition systems, it is important to adaptively compose test sheets with diverse conceptual scopes, discrimination and difficulty degrees to meet various assessment requirements during real learning situations. Computation time and item exposure rate also influence performance and item bank security. Therefore, this study proposes an Adaptive Test Sheet Generation (ATSG) mechanism, where a Candidate Item Selection Strategy adaptively determines candidate test items and conceptual granularities according to desired conceptual scopes, and an Aggregate Objective Function applies Genetic Algorithm (GA) to figure out the approximate solution of mixed integer programming problem for the test-sheet composition. Experimental results show that the ATSG mechanism can efficiently, precisely generate test sheets to meet the various assessment requirements than existing ones. Furthermore, according to experimental finding, Fractal Time Series approach can be applied to analyze the self-similarity characteristics of GA's fitness scores for improving the quality of the test-sheet composition in the near future.
URI: http://hdl.handle.net/11536/16376
http://dx.doi.org/820190
ISSN: 1024-123X
DOI: 820190
期刊: MATHEMATICAL PROBLEMS IN ENGINEERING
顯示於類別:期刊論文


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