An approach to detect learning types based on triple-factor in e-learning process

Sfenrianto, Zainal Arifin Hasibuan, Heru Suhartanto, Nungki Selviandro

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

In previous studies, it was revealed that the importance of learning styles, motivation, and knowledge ability factors are facilitated diverse learners in e-learning. However, the overall of factors are not yet fully accommodated in e-learning process. Meanwhile, the results of preliminary study of this research indicated that the existence of these factors as the inherent structure that reflect the relationship among learning styles and motivation to the knowledge ability (Triple-Factor) in elearning process. In order to accommodate the existence of inherent structure, this study explores the learning types based on triple-factor in e-learning process. The approach can be used as the basis for the learning recommendation and personalization in e-learning process. The approach consists of three steps: (1) identifying activity and evaluation of learning outcome, (2) forming Triple-Factor, and (3) detecting learning types based on Triple-Factor. The approach use 36 types of learning which consists of: 18 learning types that has the ability of knowledge good or very good, irrespective of the learning styles and motivation; and 18 learning types that has the ability of knowledge fail or sufficient, irrespective of the learning styles and motivation. Furthermore, the experiment for testing steps was carried by dividing two stages: the first stage did not implement the approach, second stage using learning recommendation and personalization. Result of the testing of these two stages are: step of " identifying activity and evaluation of learning outcome " at the second stage, showed that there was a significant increase on the activity of learning (0.007<0.05), and discussion forums (0.006<0.05), meanwhile the evaluation of learning outcomes (0.227>0.05) did not increase significantly. Step of "forming Triple-Factor", and " detecting learning type base on Triple-Factor" at the second stage showed: learning styles and motivation with the knowledge ability of good and very good increased from 57 to 69 students. In contrast learning styles and motivation with the knowledge ability of fail and sufficient decreased from 61 to 49. The results show that the approach used in the study successfully improve the learning process and its outcomes through learning recommendation and personalization.

Original languageEnglish
Pages (from-to)9-15
Number of pages7
JournalJournal of Next Generation Information Technology
Volume5
Issue number1
Publication statusPublished - 1 Jan 2014

Keywords

  • E-learning
  • Knowledge abilities
  • Learning style
  • Learning type
  • Motivation
  • Triple-factor

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