Enhancing Human-Generative Artificial Intelligence Online Collaboration Outcomes: The Pivotal Function of Symbiotic Role Design.
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| Title: | Enhancing Human-Generative Artificial Intelligence Online Collaboration Outcomes: The Pivotal Function of Symbiotic Role Design. |
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| Authors: | Cheng, Nuo1, Liu, Hongxia1, Xu, Xiaoqing1, Zhao, Wei1, Qiao, Lifang2, Zhang, Guohao3 |
| Source: | International Review of Research in Open & Distributed Learning. May2026, Vol. 27 Issue 2, p46-66. 21p. |
| Subject Terms: | *Collaborative learning, *Cognitive load, Technology Acceptance Model |
| Abstract: | While generative artificial intelligence (GAI) has emerged as a vital support tool for collaborative learning, further exploration is required to achieve effective human-machine symbiosis in online collaborative processes. Grounded in symbiosis theory, our study developed a role-based intervention strategy to empower learners and their artificial intelligence (AI) partners through clearly defined responsibilities and collaborative interaction rules. In a quasi-experimental pretest-posttest design involving 58 graduate students, we employed statistical analyses and lag sequential analysis to evaluate the impact of the role intervention on online collaborative learning. The results indicated that the role design (a) significantly enhanced the quality of collaborative knowledge construction, (b) facilitated transitions among higherorder collaborative behaviors, and (c) improved perceived usefulness and ease of use of GAI among learners, although it also led to a moderate increase in collaborative cognitive load. These findings validated the core value of symbiosis theory-based role design for optimizing human-AI collaboration. Our study offered both a theoretical perspective on human-machine co-development and valuable insights for instructors to integrate AI tools and design more effective online collaborative learning activities. [ABSTRACT FROM AUTHOR] |
| Copyright of International Review of Research in Open & Distributed Learning is the property of Governors of Athabasca University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 193542265 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Enhancing Human-Generative Artificial Intelligence Online Collaboration Outcomes: The Pivotal Function of Symbiotic Role Design. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Cheng%2C+Nuo%22">Cheng, Nuo</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Liu%2C+Hongxia%22">Liu, Hongxia</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Xu%2C+Xiaoqing%22">Xu, Xiaoqing</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Zhao%2C+Wei%22">Zhao, Wei</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Qiao%2C+Lifang%22">Qiao, Lifang</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Guohao%22">Zhang, Guohao</searchLink><relatesTo>3</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Review+of+Research+in+Open+%26+Distributed+Learning%22">International Review of Research in Open & Distributed Learning</searchLink>. May2026, Vol. 27 Issue 2, p46-66. 21p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Collaborative+learning%22">Collaborative learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Cognitive+load%22">Cognitive load</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Acceptance+Model%22">Technology Acceptance Model</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: While generative artificial intelligence (GAI) has emerged as a vital support tool for collaborative learning, further exploration is required to achieve effective human-machine symbiosis in online collaborative processes. Grounded in symbiosis theory, our study developed a role-based intervention strategy to empower learners and their artificial intelligence (AI) partners through clearly defined responsibilities and collaborative interaction rules. In a quasi-experimental pretest-posttest design involving 58 graduate students, we employed statistical analyses and lag sequential analysis to evaluate the impact of the role intervention on online collaborative learning. The results indicated that the role design (a) significantly enhanced the quality of collaborative knowledge construction, (b) facilitated transitions among higherorder collaborative behaviors, and (c) improved perceived usefulness and ease of use of GAI among learners, although it also led to a moderate increase in collaborative cognitive load. These findings validated the core value of symbiosis theory-based role design for optimizing human-AI collaboration. Our study offered both a theoretical perspective on human-machine co-development and valuable insights for instructors to integrate AI tools and design more effective online collaborative learning activities. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Review of Research in Open & Distributed Learning is the property of Governors of Athabasca University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 46 Subjects: – SubjectFull: Collaborative learning Type: general – SubjectFull: Cognitive load Type: general – SubjectFull: Technology Acceptance Model Type: general Titles: – TitleFull: Enhancing Human-Generative Artificial Intelligence Online Collaboration Outcomes: The Pivotal Function of Symbiotic Role Design. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Cheng, Nuo – PersonEntity: Name: NameFull: Liu, Hongxia – PersonEntity: Name: NameFull: Xu, Xiaoqing – PersonEntity: Name: NameFull: Zhao, Wei – PersonEntity: Name: NameFull: Qiao, Lifang – PersonEntity: Name: NameFull: Zhang, Guohao IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 14923831 Numbering: – Type: volume Value: 27 – Type: issue Value: 2 Titles: – TitleFull: International Review of Research in Open & Distributed Learning Type: main |
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