Abstract:

There is a great boom in e-learning in the area of technology-enhanced Intelligent Tutoring Educational Systems where excellent virtual instructors/teachers which guide their learners/students. Progress has been made, addressing a variety of educational needs, ranging from supplements to existing “traditional” courses, to complete on-line courses, to complete on-line programs. Despite all this effort, hype, and even product development, most of the courseware material available for use at the educational level is still not judged to be as effective as a teacher lecturing and leading discussions with students.
It is often necessary for a teacher to prepare a test over information for which students have been previously quizzed or to administer multiple versions of same test. When this situation occurs, teachers are required to spend extra time creating equivalent questions. The major difficulty with this problem lies in efficiently creating sets of equivalent questions.
To solve this problem of efficiency, instead of creating the question set, the teacher may create pattern of each question. Once pattern of a question is created for each question in a test, multiple equivalent tests can be generated as necessary. In this paper, authors introduce a specific, topic-based knowledge modeling approach which has been implemented as a Question Agent in HKDA System and used in HKDA-IQPS. HKDA-IQPGS that aids teachers in creating number of question patterns and in generating equivalent variety of questions for an Intelligent Tutoring System as HKDA System. With HKDA-IQPGS, the students can explore more questions, work on questions more persistently, and accessed a larger diversity of questions. This increased participation resulted in the larger increase of their knowledge at the end of the course.

Keywords:

Intelligent Question Paper System, Question Model, Academic Learning, Knowledge Map.