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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.04365 |
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| _version_ | 1866910635221057536 |
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| author | Wang, Tianjia Wu, Tong Liu, Huayi Brown, Chris Chen, Yan |
| author_facet | Wang, Tianjia Wu, Tong Liu, Huayi Brown, Chris Chen, Yan |
| contents | 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 results show that by implementing features to support textual and visual communication and simulate an interactive learning environment with generative agents, our system enhances the cognitive and social presence in the asynchronous learning environment. These results suggest the potential to use generative AI to support students learning at scale and transform asynchronous learning into a more inclusive, engaging, and efficacious educational approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_04365 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Generative Co-Learners: Enhancing Cognitive and Social Presence of Students in Asynchronous Learning with Generative AI Wang, Tianjia Wu, Tong Liu, Huayi Brown, Chris Chen, Yan Human-Computer Interaction 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 results show that by implementing features to support textual and visual communication and simulate an interactive learning environment with generative agents, our system enhances the cognitive and social presence in the asynchronous learning environment. These results suggest the potential to use generative AI to support students learning at scale and transform asynchronous learning into a more inclusive, engaging, and efficacious educational approach. |
| title | Generative Co-Learners: Enhancing Cognitive and Social Presence of Students in Asynchronous Learning with Generative AI |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2410.04365 |