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

doi:10.1007/978-3-030-28011-6_3

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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 language	English
Title of host publication	Collaboration Technologies and Social Computing - 25th International Conference, CRIWG+CollabTech 2019, Proceedings
Editors	Hideyuki Nakanishi, Hironori Egi, Irene-Angelica Chounta, Hideyuki Takada, Satoshi Ichimura, Ulrich Hoppe
Publisher	Springer Verlag
Pages	36-44
Number of pages	9
ISBN (Print)	9783030280109
DOIs	https://doi.org/10.1007/978-3-030-28011-6_3
State	Published - 2019
Event	25th International Conference on Collaboration Technologies and Social Computing, CRIWG+CollabTech 2019 - Kyoto, Japan Duration: 4 Sep 2019 → 6 Sep 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11677 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	25th International Conference on Collaboration Technologies and Social Computing, CRIWG+CollabTech 2019
Country/Territory	Japan
City	Kyoto
Period	4/09/19 → 6/09/19

Keywords

Collaboration
Eye-tracking
Science learning

Access to Document

10.1007/978-3-030-28011-6_3

Cite this

Hsieh, I. C., Liu, C. C., Tsai, M. J., Wen, C. T., Chang, M. H., Fan Chiang, S. H., & Chang, C. J. (2019). The analysis of collaborative science learning with simulations through dual eye-tracking techniques. In H. Nakanishi, H. Egi, I.-A. Chounta, H. Takada, S. Ichimura, & U. Hoppe (Eds.), Collaboration Technologies and Social Computing - 25th International Conference, CRIWG+CollabTech 2019, Proceedings (pp. 36-44). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11677 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-28011-6_3

Hsieh, I. Chen ; Liu, Chen Chung ; Tsai, Meng Jung et al. / The analysis of collaborative science learning with simulations through dual eye-tracking techniques. Collaboration Technologies and Social Computing - 25th International Conference, CRIWG+CollabTech 2019, Proceedings. editor / Hideyuki Nakanishi ; Hironori Egi ; Irene-Angelica Chounta ; Hideyuki Takada ; Satoshi Ichimura ; Ulrich Hoppe. Springer Verlag, 2019. pp. 36-44 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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{\textquoteright} mental effort in using the simulations. The use of dual eye-tracking techniques is helpful to uncover learners{\textquoteright} visual attention, and thus to better analyze student collaboration in activities. In this paper, the research focus on learners{\textquoteright} 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{\textquoteright} attention. Educators may need to address these problems when simulations are applied to support remote collaborative science learning.",

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author = "Hsieh, {I. Chen} and Liu, {Chen Chung} and Tsai, {Meng Jung} and Wen, {Cai Ting} and Chang, {Ming Hua} and {Fan Chiang}, {Shih Hsun} and Chang, {Chia Jung}",

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Hsieh, IC, Liu, CC, Tsai, MJ, Wen, CT, Chang, MH, Fan Chiang, SH & Chang, CJ 2019, The analysis of collaborative science learning with simulations through dual eye-tracking techniques. in H Nakanishi, H Egi, I-A Chounta, H Takada, S Ichimura & U Hoppe (eds), Collaboration Technologies and Social Computing - 25th International Conference, CRIWG+CollabTech 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11677 LNCS, Springer Verlag, pp. 36-44, 25th International Conference on Collaboration Technologies and Social Computing, CRIWG+CollabTech 2019, Kyoto, Japan, 4/09/19. https://doi.org/10.1007/978-3-030-28011-6_3

The analysis of collaborative science learning with simulations through dual eye-tracking techniques. / Hsieh, I. Chen; Liu, Chen Chung; Tsai, Meng Jung et al.
Collaboration Technologies and Social Computing - 25th International Conference, CRIWG+CollabTech 2019, Proceedings. ed. / Hideyuki Nakanishi; Hironori Egi; Irene-Angelica Chounta; Hideyuki Takada; Satoshi Ichimura; Ulrich Hoppe. Springer Verlag, 2019. p. 36-44 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11677 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Hsieh, I. Chen

AU - Liu, Chen Chung

AU - Tsai, Meng Jung

AU - Wen, Cai Ting

AU - Chang, Ming Hua

AU - Fan Chiang, Shih Hsun

AU - Chang, Chia Jung

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

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Hsieh IC, Liu CC, Tsai MJ, Wen CT, Chang MH, Fan Chiang SH et al. The analysis of collaborative science learning with simulations through dual eye-tracking techniques. In Nakanishi H, Egi H, Chounta IA, Takada H, Ichimura S, Hoppe U, editors, Collaboration Technologies and Social Computing - 25th International Conference, CRIWG+CollabTech 2019, Proceedings. Springer Verlag. 2019. p. 36-44. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-28011-6_3

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

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Keywords

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