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Combination of Bidirectional Conceptual Map and Genetic Algorithm for E-Learning Evaluation System


Chin-Ling Lee, Cheng-Jian Lin


Vol. 6  No. 9  pp. 1-7


This paper mainly proposed an E-learning evaluation system to produce effective test sheets with adaptive difficulty degree and bidirectional concept. Our proposed method utilized the characteristics of optimal genetic algorithm based on a test-sheet generation model. The learner proceeded online measurement by the adoption of a measure model. Results of the measurement will be generated throughout the process of the automation analysis, feedback and recommendation. Then, the results will be feedbacked to the system, tutors and the students. For the students, the system will diagnose and lead the students to appropriate learning concept and progress. For the system, feedback model will adjust the adaptive difficulty degree of learning. For the tutors, the system will guide the tutors in the adjustment of appropriate teaching concept and difficulty degree. The simulation results showed that the proposed method was able produce the optimal test sheet that fit the learning target which helps the learners to penetrate the learning disabilities and increase the learning effectiveness


E-learning, bidirectional concept, genetic algorithm