Papers investigate human-AI collaboration in learning, comparing peer versus AI assistance in graph theory and examining cognitive, social, and metacognitive dimensions of student-student-LLM problem solving. Other talks design multi-agent AI systems and use deliberately biased chatbots to prepare teachers for collaboration.
Papers examine perceptions of innovation and change, with several analyzing teacher and STEM-educator sentiments about generative AI through social media discourse on X and Reddit. Other talks cover participatory design for AI in teacher education, reconceptualizing conversational AI as a learning medium, and NGSS implementation.
Four long papers use multimodal data to study how emotions and teacher support are regulated during collaborative learning. Topics range from emotion regulation in student dyads building computational models to teacher orchestration load, proximity effects, and scaffolding via classroom chatbots.
An in-person poster session spanning collaborative learning research, with strong threads on AI literacy games, epistemic agency, and knowledge building alongside SEL, VR and maker collaboration, and equity-focused design. Studies range from a Turing-test game and weaving-based ML curricula to ceremonial Indigenous designs and belonging infrastructure in research-practice partnerships.