Generative Co-Learners: Enhancing Cognitive and Social Presence of Students in Asynchronous Learning with Generative AI
Tianjia Wang, Tong Wu, Huayi Liu, Chris Brown, Yan Chen

TL;DR
This paper presents Generative Co-Learners, an AI system that uses generative agents to improve cognitive and social presence in asynchronous learning, making online education more engaging and supportive.
Contribution
It introduces a novel AI-powered co-learning system that enhances interaction and presence in asynchronous learning environments, addressing key communication challenges.
Findings
System improves cognitive and social presence in online learning.
Participants reported increased engagement and support.
Generative agents effectively simulate interactive learning environments.
Abstract
Cognitive presence and social presence are crucial for a comprehensive learning experience. Despite the flexibility of asynchronous learning environments to accommodate individual schedules, the inherent constraints of asynchronous environments make augmenting cognitive and social presence particularly challenging. Students often face challenges such as a lack of timely feedback and support, a lack of non-verbal cues in communication, and a sense of isolation. To address this challenge, this paper introduces Generative Co-Learners, a system designed to leverage generative AI-powered agents, simulating co-learners supporting multimodal interactions, to improve cognitive and social presence in asynchronous learning environments. We conducted a study involving 12 student participants who used our system to engage with online programming tutorials to assess the system's effectiveness. The…
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Taxonomy
TopicsOnline Learning and Analytics
