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.
Long papers focus on pre-service teachers and dialogic conversation, including science teachers rehearsing questioning with AI-based and VR classroom simulators. Other talks examine an AI-feedback co-design intervention for math tutors' productive talk and learning-analytics-supported reflective assessment for knowledge building.
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.
Four papers on teaching and studying AI ethics across age groups and methods. Approaches include a literature review of AI ethics in ISLS proceedings, tabletop and scenario-based games for fostering multidimensional and ethical thinking, and laddering methodology for surfacing young children's values in design.
Four papers examining how authority and agency are distributed among students, teachers, and AI tools during learning. Threads include authority in elementary science modeling, how students remix AI chatbots into dialogic tools, epistemic agency in student-LLM math problem solving, and analytics-supported reflective assessment for pre-service teachers.
Four papers on how programming environments and AI are reshaping computer science education. Topics include balancing usability and expressiveness in block-based modeling, Parsons puzzles paired with self-explanation, teachers' shifting conceptions of AI/ML and algorithmic justice, and norms around when copying code is acceptable.