PUBLICATIONS

Artificial intelligence (AI) technologies generate increasingly sophisticated non-human cognition; however, foundational learning theories only contemplate human cognition, and current research conceptualizes AI as a pedagogical tool. We argue that the incipient abilities of AI for mutual engagement with people could allow AI to participate as a legitimate member in social constructivist learning environments and suggest some potential structures and activities to explore AI's capabilities for full participation. "Participation is an active process, but I will reserve the term for actors who are members of social communities. For instance, I will not say that a computer “participates” in a community of practice…. (Wenger, 1998, p. 56)" Twenty-five years ago, Etienne Wenger published his influential book Communities of practice: Learning, meaning, and identity (Wenger, 1998), where he specifically discounted computers as potential members of a community of practice (CoP). Recently, however, the abilities of computational systems like generative artificial intelligence (AI) oblige us to reconsider the roles non-human cognition could play in communities of practice centered on learning. Recently, the editorial article “Artificial Intelligence and the Journal of Research in Science Teaching” (Sadler et al., 2024) describes the potential for AI technology to transform science education, but notes that “the science education research community is not as far along as it needs to be in terms of understanding, theorizing, and studying the intersections of AI and science education.” (p. 742). In response, this commentary presents our theorization and conceptualization of AI in science education. We apply the lens of social constructivism (Wenger, 1998) to theorize about this question and we argue that the nature of generative AI allows it to transcend an instrumental role and achieve full participation in a CoP. We are convinced that socio-constructivist theory in general, and CoP specifically, can provide conceptual tools and theoretical underpinnings to guide the use of AI in education. In this commentary, we synthesize ideas from current literature to construct a theoretical framework and offer suggestions for the transformative use of generative AI.