human-ai-collaboration
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- PaperComputers & Education1 Jul 2026
A community of inquiry perspective on human–AI co-facilitation within micro-blended learning
Zilong Pan, Zilu Jiang, Shen Ba, Kui Xie
Applies the Community of Inquiry framework to explore human–AI co-facilitation in micro-blended learning contexts. Findings likely highlight how AI can augment instructor presence and support learner engagement within short, blended modules.
- PaperComputers & Education23 Jun 2026
Equipping elementary school students with self-regulated learning through human-AI collaboration in online learning
Xinyi Luo, Sikai Wang, Khe Foon Hew
The study explores how human-AI collaboration in online learning environments can equip elementary school students with self-regulated learning skills.
- PaperComputers and Education: Artificial Intelligence9 Jun 2026
Human-AI collaboration in higher education: Exploring the impact of technology expectations and distrust
Liana Razmerita, Xiaojiang Zheng, Jonathan P. Allen
A survey of 245 higher education students using GenAI found that effort and performance expectations positively influence confirmation and intentions to collaborate with AI, but distrust negatively moderates these relationships, extending ECT in the context of human-AI collaboration.
Original abstract
: Drawing on expectation confirmation (ECT) theory, this study explores the factors that impact Human-Artificial Intelligence (AI) collaboration and investigates the effect of students' distrust towards GenAI. An online survey was administered to students in higher education using GenAI (N=245). This study found positive and significant relationships between effort expectation and performance technology expectation, as predicted by ECT, with positive confirmation of GenAI collaboration significantly influencing intentions and positively impacting student behavior. This study further revealed that GenAI distrust negatively moderates the relationships between (1) effort expectation and performance expectation; and (2) expectation confirmation toward collaborating with GenAI and intentions to collaborate with GenAI. Accordingly, this research contributes to the understanding of the role of distrust into Human-AI collaboration and extends the theoretical boundaries of ECT in higher education context. Practically, our findings provide insights for educators and GenAI practitioners to develop strategic approaches that effectively bridge students' distrust and initial expectations with responsible Human-AI collaboration behaviors.