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.
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© 2005 Springer-Verlag Berlin Heidelberg
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Du, J., Zheng, Q., Li, H., Yuan, W. (2005). The Research of Mining Association Rules Between Personality and Behavior of Learner Under Web-Based Learning Environment. In: Lau, R.W.H., Li, Q., Cheung, R., Liu, W. (eds) Advances in Web-Based Learning – ICWL 2005. ICWL 2005. Lecture Notes in Computer Science, vol 3583. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11528043_42
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DOI: https://doi.org/10.1007/11528043_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27895-5
Online ISBN: 978-3-540-31716-6
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