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The recent surge of artificial intelligence (AI) in science education has heightened interest among the NARST community—a curiosity about how technology can transform education that has lasted for decades. This growing interest is evidenced by the launch of the Research in Artificial Intelligence-Involved Science Education (RAISE) Research Interest Group in 2022 and the increasing number of AI-related studies presented at NARST conferences. Despite the growth, limited studies have shed light on how the community members integrate AI into science education and the challenges. We systematically reviewed 36 AI-related papers presented at the 2024 NARST conference to address this gap.

The Language, Culture, and Knowledge-building through Science (LaCuKnoS) project tests and refines a model of science teaching and learning that brings together current research on the role of language in science communication, the role of cultural and community connections in science engagement, and the ways people apply science knowledge to their daily decision making. One key component of the model brings families together as co-learners and co-teachers through family learning experiences. We describe our work to promote more robust family conversations about science in our lives within an existing research practice partnership, using a two-tiered qualitative conversational analysis to compare the family conversations that result from three family engagement models: (a) family science festivals; (b) family science workshops; and (c) family science home learning.

Fostering student engagement with mathematical reasoning and proving requires a special kind of teacher knowledge – Mathematical Knowledge for Teaching Proof (MKT-P). One important component of MKT-P is Knowledge of Content and Teaching specific to Proof (KCT-P), which is knowledge of pedagogical practices for supporting student learning of proof. Providing effective feedback on students' mathematical arguments is one of the key aspects of KCT-P. This study examined the qualitative differences in written feedback of secondary teachers, undergraduate mathematics and computer science majors, and pre-service teachers participating in a capstone course focused on mathematical reasoning and proving.

General educators rarely receive adequate training for supporting students with disabilities (SWDs). We suggest a key contributing factor is the longstanding gap between special and general education researchers, which is especially pronounced in mathematics.

General educators rarely receive adequate training for supporting students with disabilities (SWDs). We suggest a key contributing factor is the longstanding gap between special and general education researchers, which is especially pronounced in mathematics.

In this brief, The Potential of Using AI to Improve Student Learning in STEM: Now and in the Future, the authors examine the promise of AI as learning partner for students that offers personalized support and scaffolding.

AI in education has many potential uses as well as limits, challenges, and dangers. In this brief, the authors explore how to promote equitable and just educational futures with AI.

What are the opportunities and challenges for establishing community partnerships among K–12 STEM education researchers and Black and Brown communities? CADRE partners interviewed five community partners from diverse backgrounds in STEM education to understand how STEM education researchers can better engage with communities and share their insights in this brief.

On June 11, 2024, NSF program officers provided clarification on the NSF DRK-12 solicitation's partnership development project type. On June 11, 2024, NSF program officers provided clarification on the NSF DRK-12 solicitation's partnership development project type. View the slides, chat log resources, and recording from this information session.