Journal of International Technology and Information Management
Document Type
Article
Abstract
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.
Recommended Citation
Hong, Seong-Yong; Cho, Juyun; and Hwang, Yonghyun
(2016)
"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:
Iss.
3, Article 6.
DOI: https://doi.org/10.58729/1941-6679.1321
Available at:
https://scholarworks.lib.csusb.edu/jitim/vol25/iss3/6
Included in
Business Intelligence Commons, Communication Technology and New Media Commons, Computer and Systems Architecture Commons, Data Storage Systems Commons, Digital Communications and Networking Commons, E-Commerce Commons, Information Literacy Commons, Management Information Systems Commons, Management Sciences and Quantitative Methods Commons, Operational Research Commons, Science and Technology Studies Commons, Social Media Commons, Technology and Innovation Commons