Instructional gestures are essential for teaching, enhancing communication and student comprehension. Current training methods for developing these skills can be time-consuming, isolating, or overly prescriptive, e.g., watching lengthy, one-size-fits-all videos. Conversely, research suggests that developing these tacit, experiential skills requires teachers’ peer learning, where they learn from each other and build shared knowledge. While much HCI exploration has applied learning-by-teaching to students’ peer learning, little has explored this approach for teacher professionalization. We present Novobo, an apprentice AI-agent stimulating teachers' peer learning of instructional gestures through verbal and bodily inputs. An evaluation with 30 teachers in 10 collaborative sessions showed Novobo prompted teachers to externalize and share tacit knowledge through dialogue and movement. Teaching an AI mentee together reduced their pressure, facilitating peer exchange and the co-construction of practical knowledge. This work contributes a novel design and empirical insights into how teachable AI-agents can facilitate peer learning in teacher professionalization.
ACM CHI Conference on Human Factors in Computing Systems