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In successful peer discussions students respond to each other and benefit from supports that focus discussion on one another’s ideas. We explore using artificial intelligence (AI) to form groups and guide peer discussion for grade 7 students. We use natural language processing (NLP) to identify student ideas in science explanations. The identified ideas, along with Knowledge Integration (KI) pedagogy, informed the design of a question bank to support students during the discussion. We compare groups formed by maximizing the variety of ideas among participants to randomly formed groups. We embedded the chat tool in an earth science unit and tested it in two classrooms at the same school. We report on the accuracy of the NLP idea detection, the impact of maximized versus random grouping, and the role of the question bank in focusing the discussion on student ideas. We found that the similarity of student ideas limited the value of maximizing idea variety and that the question bank facilitated students’ use of knowledge integration processes. 

We explore how a Teacher Action Planner (TAP) that synthesizes student ideas impacts teacher noticing. The TAP uses Natural Language Processing (NLP) to detect student ideas in written explanations. We compared teacher noticing while using the TAP to noticing when reviewing student explanations. The TAP helped teachers deepen their analysis of student ideas. We did not see any impact on immediate instructional practice. We propose redesigns to the TAP to better connect noticing to instruction.