The learning behaviors analysis in a language learning support system – a pilot study

Jingyun Wang, Ching ju Chao, Likun Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present an ontology-based visualization language learning support system (VLLSS) which provide learning materials based on topic maps. A pilot experiment was conducted to study the learning behaviors features of learners who studied with VLLSS. One class of 11 intermediates and one class of 19 beginners from a university in Taiwan studied with the system for learning Japanese grammar. Not only the reported learning perception but also the learning logs recorded by VLLSS are analyzed. In terms of learning perception, no significant difference was found in other scales except in a tendency of significant difference in mental load. It is found that compared to intermediates who studied more difficult grammar points, the beginners reported significant higher pressure when studied with the system. In terms of learning logs, we analyzed the ratio of studied related grammar points to the target grammar points, the ratio of studied relations to the target ones, and the number of the target grammar points. We also studied the relation between those three parameters and the learning habit.

Original languageEnglish
Title of host publicationHCI International 2020 - Posters - 22nd International Conference, HCII 2020, Proceedings
EditorsConstantine Stephanidis, Margherita Antona
PublisherSpringer
Pages349-355
Number of pages7
ISBN (Print)9783030507282
DOIs
Publication statusPublished - 2020
Event22nd International Conference on Human-Computer Interaction, HCII 2020 - Copenhagen, Denmark
Duration: Jul 19 2020Jul 24 2020

Publication series

NameCommunications in Computer and Information Science
Volume1225 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference22nd International Conference on Human-Computer Interaction, HCII 2020
CountryDenmark
CityCopenhagen
Period7/19/207/24/20

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

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