earticle

영어

At the present time, computerized tests are one of the most critical means to evaluate learning. Choosing tailored questions for each learner is a important part of such tests. Since, wide and varied learners with different abilities are involved, even randomized test cannot serve the purpose of assessment. Some form of personalized and intelligent testing is needed in E-Learning. One of the main components in composing intelligent testing is selecting the items from a huge Item Bank as the accuracy of the test depends on the quality of the assessment which in turn depends on the items selected for assessment. Furthermore, pickingappropriate items is critical in developing as assessment sheet that satisfies multiple criteria. It includes the number of test items, the definitedissemination of course concepts to be assessed, and the expected degree of difficultness and discrimination and exposure frequency. These tests, must effectively select questions from a large item bank, and to manage this problem an optimized assessment sheet composition system using the modified form of nature inspired Intelligent Water Drops optimization algorithm is proposed by embedding a local heuristic as evolutionary operator. This system is designed to choosepersonalizedtest items for each and every learner. Furthermore, the proposed approach is able to effectively generate near optimal items from large item bank that satisfy multiple constraints. The results show that the Evolutionary Intelligent Water Drops approach is suitable for the selection of nearoptimal items from large-scale item bank.