An Innovative Multimodal Learning System Based on Robot and Tangible Objects for Chinese Numeral-Classifier-Noun Phrase Learning

Fu Hui Hsu, Yu Tang Hsueh, Wei Lun Chang, Yen Ting R. Lin, Yu Ju Lan, Nian Shing Chen

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

1 Citation (Scopus)

Abstract

Learning Chinese Numeral-Classifier-Noun (NCN) phrases is one of the most challenging tasks for Chinese language learners. In this study, we developed learning applications based on a multimodal robot and IoT tangible objects (R&T) learning system to help Chinese language learners, adopting technologies suiting language learning, and implementing instructional design by professional Chinese language teachers. This study adopted the ASSURE model to develop and investigate the effect of the learning system and applications. Participants were divided into two groups: learning after a human teacher and learning with the R&T learning system. Findings from Table 1 show that learning Chinese NCN Phrases with the R&T learning system is comparable to the human teacher. This study contributes to Chinese language teaching and learning by providing an alternative method for Chinese language learners learning Chinese NCN phrases or a teaching assistant system for Chinese language teachers.

Original languageEnglish
Title of host publicationProceedings - 2022 International Conference on Advanced Learning Technologies, ICALT 2022
EditorsMaiga Chang, Nian-Shing Chen, Mihai Dascalu, Demetrios G Sampson, Ahmed Tlili, Stefan Trausan-Matu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages221-223
Number of pages3
ISBN (Electronic)9781665495196
DOIs
Publication statusPublished - 2022
Event22nd International Conference on Advanced Learning Technologies, ICALT 2022 - Bucharest, Romania
Duration: 2022 Jul 12022 Jul 4

Publication series

NameProceedings - 2022 International Conference on Advanced Learning Technologies, ICALT 2022

Conference

Conference22nd International Conference on Advanced Learning Technologies, ICALT 2022
Country/TerritoryRomania
CityBucharest
Period2022/07/012022/07/04

Keywords

  • ASSURE
  • CAL
  • Chinese
  • RALL
  • classifier

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Media Technology
  • Experimental and Cognitive Psychology
  • Education

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