Enhancing Human-Generative Artificial Intelligence Online Collaboration Outcomes: The Pivotal Function of Symbiotic Role Design

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Authors: Nuo Cheng, Hongxia Liu, Xiaoqing Xu, Wei Zhao, Lifang Qiao, Guohao Zhang
Cited by: 1

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 higher-order 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.

Fields of Study & Subjects

Innovative Teaching and Learning Methods AI in Service Interactions Intelligent Tutoring Systems and Adaptive Learning

Publication details

Journal / source
The International Review of Research in Open and Distributed Learning
Publisher
Athabasca University Press
Volume
27
Issue
2
Pages
46–66
Publication date
6 May 2026
Language
EN