With the recent advances in computer technology along with pervasive internet accesses, data analytics is getting more attention than ever before. In addition, research areas on data analysis are diverging and integrating lots of different fields such as a business and social sector. Especially, recent researches focus on the data analysis for a better intelligent decision making and prediction system. This paper analyzes data collected from current IT learners who have already studied various IT subjects to find the IT learners’ learning patterns. The most popular learning patterns are identified through an association rule data mining using an arules package running under R studio. Experimental results are used to recommend the IT learning path to rudimentary IT learners. It is expected that our research promotes IT learning field and results in a platform of IT learning helpful to IT learners.
Hong, Seong-Yong; Cho, Juyun; and Hwang, Yonghyun
"Prediction And Recommendations On The It Leaners' Learning Path As A Collective Intelligence Using A Data Mining Technique,"
Journal of International Technology and Information Management: Vol. 25:
3, Article 6.
Available at: https://scholarworks.lib.csusb.edu/jitim/vol25/iss3/6
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