Study on Learner Model in Adaptive Learning System Based on Ant Colony Algorithm
The adaptive learning system is a hotspot in the field of e-Learning and intelligent education researches. Learner model is the core of adaptive learning system. However, in the light of rapidly growing “big data”, adaptive learning system is facing the challenge of dealing with the realistic data. So in order to respond to this situation, we take a summary of oversea and domestic learner model norm of e-Learning, and then explore the ant colony algorithm and propose a construction method of learner model with consideration on the learners’ knowledge, interests and individual traits in the adaptive learning system. Especially, we regard the learners’ cognitive ability as a vital aspect of the learner model, and creatively employ the forgetting curve to the quantitative learner model built on ant colony algorithm.
KeywordsAdaptive learning Learner model E-learning Ant colony algorithm Big data
This paper is supported by Chinese National Natural Science Foundation Project “Research on key technologies in knowledge fusion of web information” (No. 61272205), Chinese Education Ministry’s New Century Excellent Talents Supporting Plan(No.NCET-13-0818), Central China Normal University Study Program “Learners’ participation degree in online learning”(No.2014B01), Wuhan Science and Technology Project “Research on anti-piracy and non-proliferation digital copyright management and identification mechanism” (No.2014060101010030) and Hubei Collaborative Innovation Center of Basic Education Information Technology Services Project “Research on key technologies in smart interaction classroom”.
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