Effective question modelling and intelligent question bank storage engine: an adaptive graph based approach

Abhijeet Kumar, Saurabh Srivastava, Vijay Krishan and R.H. Goudar

International Journal of Knowledge and Learning, 2018, vol. 12, issue 3, 204-220

Abstract: In the changing present competitive scenario, intelligent development of question model is indispensable for intellectual growth of students. There are several computer-based question paper generators, but they typically use random selection from question banks. This paper deals with the adaptive question bank development and management system (AQBDMS) that aims to generate balanced combinations of questions intelligently as per parameters provided by the question paper designer (QPD). AQBDMS uses a concept map developed on a graph database that uses hierarchical knowledge of a particular domain for fetching questions generated in former part. The concept map ensures that the question modelling process is based on certain criteria like Bloom's taxonomy, difficulty level, marking scheme etc. The evaluation of generated question model will provide a feedback to check student's overall level of understanding. On whole, the proposed system would be of great aid to the organisation in effective question modelling and its assessment.

Keywords: question modelling; QPDE; question paper designer engine; QSE; question storage engine; question bank (database); concept map. (search for similar items in EconPapers)
Date: 2018
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