Novobo: Supporting Teachers' Peer Learning of Instructional Gestures by Teaching a Mentee AI-Agent Together
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866908379976302592 |
|---|---|
| author | Jiang, Jiaqi Huang, Kexin Martinez-Maldonado, Roberto Zeng, Huan Gong, Duo An, Pengcheng |
| author_facet | Jiang, Jiaqi Huang, Kexin Martinez-Maldonado, Roberto Zeng, Huan Gong, Duo An, Pengcheng |
| contents | Instructional gestures are essential for teaching, as they enhance communication and support student comprehension. However, existing training methods for developing these embodied skills can be time-consuming, isolating, or overly prescriptive. Research suggests that developing these tacit, experiential skills requires teachers' peer learning, where they learn from each other and build shared knowledge. This paper introduces Novobo, an apprentice AI-agent stimulating teachers' peer learning of instructional gestures through verbal and bodily inputs. Positioning the AI as a mentee employs the learning-by-teaching paradigm, aiming to promote deliberate reflection and active learning. Novobo encourages teachers to evaluate its generated gestures and invite them to provide demonstrations. An evaluation with 30 teachers in 10 collaborative sessions showed Novobo prompted teachers to share tacit knowledge through conversation and movement. This process helped teachers externalize, exchange, and internalize their embodied knowledge, promoting collaborative learning and building a shared understanding of instructional gestures within the local teaching community. This work advances understanding of how teachable AI agents can enhance collaborative learning in teacher professional development, offering valuable design insights for leveraging AI to promote the sharing and construction of embodied and practical knowledge. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_17557 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Novobo: Supporting Teachers' Peer Learning of Instructional Gestures by Teaching a Mentee AI-Agent Together Jiang, Jiaqi Huang, Kexin Martinez-Maldonado, Roberto Zeng, Huan Gong, Duo An, Pengcheng Human-Computer Interaction Instructional gestures are essential for teaching, as they enhance communication and support student comprehension. However, existing training methods for developing these embodied skills can be time-consuming, isolating, or overly prescriptive. Research suggests that developing these tacit, experiential skills requires teachers' peer learning, where they learn from each other and build shared knowledge. This paper introduces Novobo, an apprentice AI-agent stimulating teachers' peer learning of instructional gestures through verbal and bodily inputs. Positioning the AI as a mentee employs the learning-by-teaching paradigm, aiming to promote deliberate reflection and active learning. Novobo encourages teachers to evaluate its generated gestures and invite them to provide demonstrations. An evaluation with 30 teachers in 10 collaborative sessions showed Novobo prompted teachers to share tacit knowledge through conversation and movement. This process helped teachers externalize, exchange, and internalize their embodied knowledge, promoting collaborative learning and building a shared understanding of instructional gestures within the local teaching community. This work advances understanding of how teachable AI agents can enhance collaborative learning in teacher professional development, offering valuable design insights for leveraging AI to promote the sharing and construction of embodied and practical knowledge. |
| title | Novobo: Supporting Teachers' Peer Learning of Instructional Gestures by Teaching a Mentee AI-Agent Together |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2505.17557 |