User profiling based Adaptive Test Generation and Assessment in E - Learning System

In this paper, we describe a User profiling based E-Learning System with Adaptive Test Generation and Assessment. This system uses rule-based Intelligence Technique and implicit User Profiling to judge the proficiency level of the student and generates tests for them accordingly. More specifically it´s a Test Generation, Assessment and Remedial System where the student can give a test after he has completed studying a particular concept where the difficulty level of the test will be decided by the expert system engine. After the completion of the test, the system helps the student in improving the proficiency of the concept either if it is expected by the concept or if he faces difficulty in understanding the concept. Based on the type of errors made in the test, the Test Remedial System will help the student to improve in that domain of understanding of the concept. Every phase transition is rule-based which considers the user´s profile and the concept importance to make sure that he does well where it is required. Preliminary Experimental Implementations show that with User Profiling we can reduce the amount of efforts required by the user to clear a concept. Moreover, with test remedial we assure that the user actually covers all erroneous domains under a particular concept depending on its importance.