Research on E-Learning Effects Evaluation Based on Information Entropy

Although there are a large amount of platforms and tools providing distributed online learning services, it is rather difficult to identify and evaluate which solution gets the best effect. Therefore, it is definitely necessary to make assumptions about e-learning effects in distributed system which are not explicitly available. One possible choice is to assume that the better e-learning effects are, the more difficult questions web-based learners can answer. In this paper, a feature approach from the point of entropy, according to students' answers to on-line tests and exams, is proposed. Results show that it is a dependable and practical method for evaluating the e-learning effects especially for multiple choice questions.