A Tutor Assisting Novel Electronic Framework for Qualitative Analysis of a Question Bank

The traditional approach followed by tutors to assess the students is through a set of questions. The quality of a question bank has an impact on the effectiveness of evaluation in educational institutions. Determining the coverage of these questions with respect to a set of prescribed text/reference books helps in evaluating students efficiently. In this paper, we describe a Tutor Assisting e-Framework (TAeF) that enables the tutors to analyze the quality of a question bank. Initially, it clusters all individual topics of each of the input text/reference books according to their dependencies. Later, the questions are classified into these topics. The result is a set of topics, each containing the topic title and the probability by which the question is related to it. Lower the accuracy of the predicted topics, higher is the quality of the question. In other words, if question contains the topic title unaltered, it has a higher probability of being related to the topic; this degrades the quality of question. Furthermore, the congruence relation between the questions and the set of topics is found. This gives the question coverage of each topic. Finally, with this relation, the percentage of understanding the students have developed in each of these topics is computed. The Tutor Assisting e-Framework (TAeF) helps to improve the quality of a question bank, to check the topics covered by each question and the knowledge gained.