Association Rules Based Opinion Mining for E-Learning and Electronic Literature Reading

Authors

  • Shubham Dubey Faculty of Informatics, University of Debrecen, Hungary
  • Ispany Marton Faculty of Informatics, University of Debrecen, Hungary

Keywords:

ICT Supported Learning, Apriori Algorithms, Association Rule, Content Availability, Resource Divergence, Electronic Reading

Abstract

The revolution in Information technology has transformed our academics and projected it in the new dimension. ICT supported learning is best facilitating learners’ needs. With some pros there are some cons as well which are affiliated with e-learning. This study is analyzing the opinions of respondents towards e-learning and electronic literature reading. To analyze the response authors employed Apriori algorithm of association rule mining approach. The support and confidence values or the analysis were kept high (≥85) to achieve good quality of association among such factors. Study finds stress generated while adopting e-learning and e-reading has higher association with content availability in web resources. This very inferable that the wide content range results more surfing and searching and resulting stress. Study also found that the distractions caused by resource divergence are strongly associated with stress and problems faced in eyes. The study is giving significant contribution towards policy making and analysis of factors that affects the learners’ choices and problems the most.

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Published

15-05-2021

How to Cite

Dubey, S., & Marton, I. (2021). Association Rules Based Opinion Mining for E-Learning and Electronic Literature Reading. Asian Journal of Science and Applied Technology, 10(1), 41–45. Retrieved from https://ojs.trp.org.in/index.php/ajsat/article/view/2817