The research of mining association rules between personality and behavior of learner under web-based learning environment

  • Authors:
  • Jin Du;Qinghua Zheng;Haifei Li;Wenbin Yuan

  • Affiliations:
  • Department of Computer Science, Xi'an Jiaotong University, Xi'an, Shannxi, P. R. China;Department of Computer Science, Xi'an Jiaotong University, Xi'an, Shannxi, P. R. China;Department of Mathematics and Computer Science at Union University, Jackson, TN, U.S.A;Department of Computer Science, Xi'an Jiaotong University, Xi'an, Shannxi, P. R. China

  • Venue:
  • ICWL'05 Proceedings of the 4th international conference on Advances in Web-Based Learning
  • Year:
  • 2005

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Abstract

Discovering the relationship between behavior and personality of learner in the web-based learning environment is a key to guide learners in the learning process. This paper proposes a new concept called personality mining to find the “deep” personality through the observed data about the behavior. First, a learner model which includes personality model and behavior model is proposed. Second, we have designed and implemented an improved algorithm, which is based on Apriori algorithm widely used in market basket analysis, to identify the relationship. Third, we have discussed various issues like constructing the learner model, unifying the value domain of heterogeneous model attributes, and improving Apriori algorithm with decision domain. Experiment result indicated that this algorithm for mining association rules between behavior and personality is feasible and efficient. The algorithm has been used in a web-based learning environment developed at Xi'an Jiaotong University.