The impact of functional interdependencies of computer simulations on collaborative learning: Evidence from multiple sources

被引:3
作者
Liu, Chen-Chung [1 ]
Lin, Tsun-Wei [2 ]
Cheng, Chia-Hui [1 ]
Wen, Cai-Ting [2 ]
Chang, Ming-Hua [1 ]
Chiang, Shih-Hsun Fan [1 ]
Tsai, Meng-Jung [3 ]
Lin, Hung-Ming [4 ]
Hwang, Fu-Kwun [5 ]
机构
[1] Natl Cent Univ, Dept Comp Sci & Informat Engn, 300 Jhongda Rd, Taoyuan 32001, Taiwan
[2] Natl Cent Univ, Grad Inst Network Learning Technol, Taoyuan, Taiwan
[3] Natl Taiwan Normal Univ, Program Learning Sci, Taipei, Taiwan
[4] Minghsin Univ Sci & Technol, Dept Business Adm, Hsinchu, Taiwan
[5] Natl Taiwan Normal Univ, Dept Phys, Taipei, Taiwan
关键词
collaborative learning; computer simulation; eye tracking method; functional interdependency; science learning; COGNITIVE LOAD; EYE-MOVEMENTS; POSITIVE INTERDEPENDENCE; ACQUISITION; TECHNOLOGY; PERCEPTION; ATTENTION; KNOWLEDGE; FRAMEWORK; QUALITY;
D O I
10.1111/jcal.12625
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Background Collaborative computer simulations are available on some online platforms which support students at distributed locations to synchronously collaborate on the simulations to learn sciences. However, how students collaborate with each other in collaborative simulations is not clear. Objectives The aim of this study was to investigate whether functional interdependency would influence learning. Methods Two collaborative learning models with different functional interdependencies were examined (the synchronous model and the distributed accountability model). Multiple data sources obtained from 64 students were collected and analyzed. We discuss the collaborative learning with two levels of factors: the individual-level factors (i.e., individual perceptions of teamwork quality, visual attention and learning performance before and after a simulation activity) and the pair-level factors (i.e., discourse data and joint attention). Given that the pair-level factors in the collaborative learning environment may affect the individual-level factors, we further discuss the interactions of the two levels of factors in different collaborative learning models with hierarchical linear modeling (HLM) analysis. Results and Conclusions The analytical results of the individual-level factors found participants in the distributed accountability model demonstrated more frequent and longer attention to the learning activity. Furthermore, the results indicated that the two simulation learning activities would enhance the participants' learning performance except in Q2. For the pair-level factors, the results demonstrated that the participants in the distributed accountability model showed more active discourse segments but similar joint attention patterns in the learning activity. The results of the HLM analysis indicated that the students in the distributed accountability model had to collaborate with their partners through more constructive dialogue, and focused on the same areas of interest to enhance their learning performance, as the complexity of the distributed accountability design was implemented in a simulation learning activity. Major takeaways We found that the increase of functional interdependency cannot guarantee students' learning effect in collaborative learning and may hinder the communication that is needed during collaboration. Researcher may need to consider other collaboration tools to enhance the reciprocal reflection.
引用
收藏
页码:455 / 469
页数:15
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