The Impacts of Collective Intelligence on Students’ Online Collaborative Learning: A Systematic Literature Review

Collective intelligence is the type of intelligence that emerges beyond the level of individual intelligence through the interaction between organisms<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</sup>. Online collaboration learning refers to the interaction of multiple learners through a common learning goal network for synchronous or asynchronous online learning and collaborative problem solving a way of learning<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</sup>. Previous researches have described the development and implications of collective intelligence and collaborative learning. Thus far, there is little literature on the impact of crowd intelligence and decision-making on students' collaborative learning. Thus, the central aim of this review study was to explore how collective intelligence decision-making can drive online collaborative learning. The search strategy was restricted to articles published in established scholarly databases (CNKI(China national knowledge infrastructure),IEEE(The Institute of Electrical and Electronics Engineers) and WOS(Web of science) ), 20 articles were extracted and qualified for inclusion in this review study. Finally, a thematic analysis was conducted to analyze the articles and three themes were generated: i) human swarming amplify the intelligence of groups ii) collective intelligence algorithms drive online collaborative learning iii) Realize online collaborative learning on real-world platforms through conversational swarm Intelligence (CSI) and other methods. This review study provides a contribution to science education research, indicating that the collective intelligence can nudge online collaborative learning. However, this review offers a future opportunity for teacher educators, students and science education academics, and other interested parties to promote students’ online learning.

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Published
2024-09-13
DOI
https://doi.org/10.1109/icet62460.2024.10868149
Primary Topic
Technology-Enhanced Education Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

The Impacts of Collective Intelligence on Students’ Online Collaborative Learning: A Systematic Literature Review

Ying Zhou, Sitong Ran
Technology-Enhanced Education Studies
article

The Impacts of Collective Intelligence on Students’ Online Collaborative Learning: A Systematic Literature Review

Ying Zhou, Sitong Ran
article en

Abstract

Collective intelligence is the type of intelligence that emerges beyond the level of individual intelligence through the interaction between organisms<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</sup>. Online collaboration learning refers to the interaction of multiple learners through a common learning goal network for synchronous or asynchronous online learning and collaborative problem solving a way of learning<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</sup>. Previous researches have described the development and implications of collective intelligence and collaborative learning. Thus far, there is little literature on the impact of crowd intelligence and decision-making on students' collaborative learning. Thus, the central aim of this review study was to explore how collective intelligence decision-making can drive online collaborative learning. The search strategy was restricted to articles published in established scholarly databases (CNKI(China national knowledge infrastructure),IEEE(The Institute of Electrical and Electronics Engineers) and WOS(Web of science) ), 20 articles were extracted and qualified for inclusion in this review study. Finally, a thematic analysis was conducted to analyze the articles and three themes were generated: i) human swarming amplify the intelligence of groups ii) collective intelligence algorithms drive online collaborative learning iii) Realize online collaborative learning on real-world platforms through conversational swarm Intelligence (CSI) and other methods. This review study provides a contribution to science education research, indicating that the collective intelligence can nudge online collaborative learning. However, this review offers a future opportunity for teacher educators, students and science education academics, and other interested parties to promote students’ online learning.

Chongqing University of Posts and Telecommunications (CN), Nanjing University of Posts and Telecommunications (CN)
National Natural Science Foundation of China, Major Project of Philosophy and Social Science Research in Colleges and Universities of Jiangsu Province
Openalex Percentile: Top 62%
Technology-Enhanced Education Studies
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