A Novel Approach in E-Learning Evaluation System for Test-Sheet Generation
Evaluation of student's knowledge state should include the significant knowledge in the order of difficulties in student's mentality. Most contemporary evaluations have been performed in the purpose of measuring student's academic achievement. Since such evaluation results do not contain enough information about individual knowledge state, the contemporary evaluation methods might not be useful for diagnostic and formative purpose. Since the last decade, computerassisted testing has proven to be an efficient and effective way to evaluating students' learning status such that proper tutoring strategies can be adopted to improve their learning performance. A good test will not only help the instructor evaluate the learning status of the students, but also facilitate the diagnosis of the problems embedded in the students' learning process. This needs construction of the test-sheets satisfying multiple assessment requirements. The novel method uses genetic algorithm for test-sheet generation. The algorithm has been applied to large sized data banks.