Intellectual Question Categorization for Assessing the Learner Performance in E-Learning

Abstract

E-learning plays a critical role in education. Each learner is having their own way of learning style that cannot be assessed in an exclusive way. They should not be evaluated only on number of right and wrong answers. Testing must be intelligent to pose intellectual questions based on the performance during the session. So, questions have to be classified based on the item difficulty using item responses. The study involves the categorization of questions based on ANN and ANFIS techniques. This paper reports the investigation of the effectiveness and performances of these methods to observe the question classification abilities depending on item responses, item difficulty and question levels. The effectiveness of these methods was evaluated by comparing the performance and class correctness. The comparative test performance analysis based on error rating revealed that ANFIS yield better performance. This study is focused because, each item affects a students’ overall success throughout the test in terms of difficulty.