Discerning Learner's Erudition Using Data Mining Techniques

ABSTRACT

Association Rule mining can be used in various areas of education data to bring out the interesting rules about the learner’s records. It can be used to bring out the hidden facts in understanding the behavior of the learner in a learning environment, learning style, examination pattern and assessment etc. In this paper Apriori and Tertius rule mining algorithms are used to understand the behavior and attitude of the students towards diverse learning styles. Both the algorithms revealed interesting rules depending on the confidence factor of the dataset. Item sets were generated using the Apriori algorithm giving best rules . Using Tertius algorithm, the most excellent rules were generated based on the number of hypothesis, confidence value, true and false positive rates.

KEYWORDS

Learning styles, EDM, Apriori, Tertius