AI-Integrated Science Teaching Through Facilitating Epistemic Discourse in the Classroom

Abstract

We have entered the Fourth Industrial Revolution, which has brought widespread digital transformation with advanced and broadened technologies including artificial intelligence (AI). To help students prosper in a world full of AI applications, it is important for us to offer students sufficient AI-integrated learning opportunities across different subjects, including science. In this position paper, a pedagogical approach to AI-integrated science education through facilitating epistemic discourse is proposed. To establish a foundation for this integration, epistemic similarities and differences between how scientific knowledge is constructed and how AI agents learn are compared, referring to Chinn et al.’s (2014) epistemic cognition framework that attends to epistemic aims, ideals, and processes. Four bins of instructional strategies for facilitating epistemic discourse in AI-integrated science classrooms is suggested, which will help students more readily act as informed knowledge constructors, critics, and users of AI and science, who can pose questions that matter to their lives.

Integrating artificial intelligence into science lessons: teachers’ experiences and views

“…We were interested in investigating the relationship that teachers perceive between AI and science while enacting the curriculum. When science teachers could make connections between AI and science, they would be more willing to integrate AI into their science curriculum (Kim, 2022). However, teacher buy-in to curriculum change could be facilitated if they know in advance challenges to expect and actively engage them in the design and development of the curriculum.…”

“…Since science has various forms of practice, it is necessary to explicitly indicate what aspects of science can be linked to involve AI components as an intersectional area of AI and science. Kim (2022) discussed the similarities between AI and science in terms of their nature of epistemic processes. Although there are different epistemic aims-science traditionally focuses on knowledge claims while AI focuses on generating solutions and predictions-scientific methods allow for validation and improvement of the intellectual outcomes, such as models, in both AI and science.…”

“…Teachers' use of unpacked black boxes in their lessons indeed relates to epistemic practices of AI and science. Although AI and science demand evidence-based high-quality outcomes involving inherent possibilities of error (Kim, 2022), they differ relatively in the transparency of the processes in school settings. Traditionally, scientific inquiry in classrooms has been done through the human agency of teachers and students, which has given more opportunities for epistemic practices.…”

Artificial intelligence in science education: A bibliometric review

“…Similarly, Mahroof et al (2020) tested using a chatbot gadget powered by AI in coaching chemistry and determined that it was powerful in helping scholars get to know and improving instructional achievement. Likewise, Kim (2022) proposed that AI had the potential to enable personalized and adaptive learning experiences, which might assist college students in achieving greater educational outcomes in technology education. Moreover, Farahmand (2021) provided an overview of the integration of cybersecurity and AI research in cybersecurity education and the implementation of a module in an already-existing undergraduate cybersecurity engineering course.…”