The analysis of collaborative science learning with simulations through dual eye-tracking techniques

I. Chen Hsieh*, Chen Chung Liu, Meng Jung Tsai, Cai Ting Wen, Ming Hua Chang, Shih Hsun Fan Chiang, Chia Jung Chang

*Corresponding author for this work

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

Abstract

Collaborative problem solving is a core ability that has been highly valued in recent years. Collaborative problem solving activities allow learners develop collaboration skills. In science education, collaborative learning with simulations enables learners to manipulate a science problem to explore scientific concepts. However, the collaboration during such a learning context is a complicated process and researchers face difficulties in understanding learners’ mental effort in using the simulations. The use of dual eye-tracking techniques is helpful to uncover learners’ visual attention, and thus to better analyze student collaboration in activities. In this paper, the research focus on learners’ difficulties when they learn together with the simulation in different places. The results show that the techniques are helpful to identify the subtle interaction problem including the problem of lacking coordination, the process misunderstanding problem, and misunderstanding in partners’ attention. Educators may need to address these problems when simulations are applied to support remote collaborative science learning.

Original languageEnglish
Title of host publicationCollaboration Technologies and Social Computing - 25th International Conference, CRIWG+CollabTech 2019, Proceedings
EditorsHideyuki Nakanishi, Hironori Egi, Irene-Angelica Chounta, Hideyuki Takada, Satoshi Ichimura, Ulrich Hoppe
PublisherSpringer Verlag
Pages36-44
Number of pages9
ISBN (Print)9783030280109
DOIs
Publication statusPublished - 2019
Event25th International Conference on Collaboration Technologies and Social Computing, CRIWG+CollabTech 2019 - Kyoto, Japan
Duration: 2019 Sep 42019 Sep 6

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11677 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference25th International Conference on Collaboration Technologies and Social Computing, CRIWG+CollabTech 2019
Country/TerritoryJapan
CityKyoto
Period2019/09/042019/09/06

Keywords

  • Collaboration
  • Eye-tracking
  • Science learning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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