Strategies for Multimedia Learning Object Recommendation in a Language Learning Support System: Verbal Learners Vs. Visual Learners

Jingyun Wang, Takahiko Mendori, Tore Hoel

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

For the purpose of exploring strategies for multimedia learning object (LO) suggestion in customizable language learning support systems, particularly suggestion for learners with visual and verbal cognitive style preferences, a learning style based experiment was conducted in a Japanese grammar course. The support system under examination offers two learner modes: Open mode, which provides learners with both visual and verbal LOs, and Style-Matching mode, which provides visual learners with only visual LOs and verbal learners with only verbal LOs. Ninety students were assigned to three groups on the basis of their visual/verbal learning styles preferences and their previously measured learning achievement. Experimental group A studied with Open mode; experimental group B studied with Style-Matching mode; and the control group studied with verbal LOs from the course textbook. Learning performance differences among the three groups were examined in terms of (a) learning perception (including technology acceptance measures, cognitive load and satisfaction with learning mode) and (b) achievement differences. The control group had significantly lower scores on visual tasks than experimental groups, but no significant differences in scores were found on verbal tasks among these three groups. Moreover, despite the learners’ report of significantly higher distraction in Open mode, the learning motivation of learners with stronger visual style preference improved more in Open mode than in Style-Matching mode.

Original languageEnglish
Pages (from-to)345-355
Number of pages11
JournalInternational Journal of Human-Computer Interaction
Volume35
Issue number4-5
DOIs
Publication statusPublished - Mar 16 2019

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics
  • Human-Computer Interaction
  • Computer Science Applications

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