A test sheet generating algorithm based on intelligent genetic algorithm and hierarchical planning

2012 ◽  
Author(s):  
Peipei Gu ◽  
Zhendong Niu ◽  
Xuting Chen ◽  
Wei Chen
Keyword(s):  
Genetic Algorithm ◽  
Hierarchical Planning ◽  
Test Sheet ◽  
Intelligent Genetic Algorithm

scholarly journals An Adaptive Test Sheet Generation Mechanism Using Genetic Algorithm

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Huan-Yu Lin ◽  
Jun-Ming Su ◽  
Shian-Shyong Tseng
Keyword(s):  
Genetic Algorithm ◽  
Computation Time ◽  
Mixed Integer ◽  
Selection Strategy ◽  
Integer Programming Problem ◽  
Test Sheet ◽  
Test Items ◽  
Adaptive Test ◽  
Time Series Approach ◽  
Assessment Requirements

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.

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