Construction and analysis of educational tests using abductive machine learning
Computers & Education
Dynamic question generation system for web-based testing using particle swarm optimization
Expert Systems with Applications: An International Journal
An adaptive testing system for supporting versatile educational assessment
Computers & Education
A blog article recommendation generating mechanism using an SBACPSO algorithm
Expert Systems with Applications: An International Journal
A Novel Online Test-Sheet Composition Approach Using Genetic Algorithm
ISICA '09 Proceedings of the 4th International Symposium on Advances in Computation and Intelligence
A personalized genetic algorithm approach for test sheet assembling
ICWL'11 Proceedings of the 10th international conference on Advances in Web-Based Learning
A divide-and-conquer tabu search approach for online test paper generation
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Analyzing radar emitter signals with membrane algorithms
Mathematical and Computer Modelling: An International Journal
Web-based mathematics testing with automatic assessment
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Journal of Network and Computer Applications
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A computer skill certification test is one of the most important methods for evaluation of a student's computer ability. Since the tests are held frequently, one must efficiently and effectively compose test sheets from a large item bank containing over 10 000 test items. To certify student computer skills fairly, the composed test sheets must meet multiple assessment criteria such as the ratio of relevant concepts to be evaluated, the average discrimination degree, the difficulty degree, and the estimated testing time. One must allow significant time to compose an optimal test sheet from a large item bank by generating and testing each possible combination of test items. To cope with this problem, a Tabu search-based approach is proposed for more efficient composition of near-optimal test sheets from very large item banks, while meeting multiple assessment criteria. Based on the proposed approach, a computer-assisted testing system has been developed, and a series of experiments have been conducted to compare the efficiency and efficacy of this approach with other approaches. The experimental results show that the new approach is desirable for the composition of near-optimal test sheets from large item banks.