Artificial Intelligence in Science Learning within the Framework of Situated Learning Theory: A Qualitative Investigation of Teachers' Perspectives

Summary

Shang Li (2025) presents a qualitative study grounding AI integration in K-12 science education within Situated Learning Theory (SLT). Drawing on semi-structured interviews and open-ended questionnaires with fourteen Chinese science teachers (elementary through high school; physics, mathematics, chemistry, and general science), the study investigates how AI tools influence students' learning processes and outcomes, transform classroom interaction and social construction, and reshape teachers' pedagogical identities. Findings show that virtual labs, simulations, and intelligent tutoring systems enhance conceptual understanding and higher-order scientific skills, cultivate scientific identity through contextualized low-risk inquiry, and deepen collaborative meaning-making. Teachers' roles shift from knowledge transmitters to facilitators, co-investigators, and ethical supervisors, while teachers simultaneously voice concerns about overreliance and the erosion of core scientific abilities. The study positions AI tools as "mediational artifacts" that extend SLT by enabling digital communities of practice and boundary-crossing between school, real-world, and interdisciplinary contexts.

Key Findings

AI enhances conceptual understanding and higher-order scientific skills. Dynamic simulations and visualizations lower cognitive barriers and deepen comprehension beyond rote memorization, while supporting experimental design, inquiry, hypothesis testing, data analysis, modeling, argumentation, and creative exploration.
AI transforms learner identity and Agency. Students transition from "knowledge learners" to "scientific practitioners," internalizing autonomy, confidence, and a scientific identity through authentic tasks and low-risk experimentation in Feedback-rich environments.
AI deepens classroom interaction and social construction. AI-enabled real-time feedback and shared data foster collaborative inquiry, role division, and critical conversation ("thinking-negotiating-optimizing"), while teachers move to facilitators, questioners, and co-investigators and take on new roles as ethical supervisors of responsible AI use.
AI enables authentic, contextualized, and boundary-crossing learning. Virtual labs and simulations let students experience distant, hazardous, or imperceptible phenomena, bridge virtual and real-world practice, and connect scientific knowledge to real-life and cross-disciplinary contexts.
Teachers are optimistic yet concerned. Teachers envision immersive, personalized AI futures but worry about being replaced and about overreliance degrading independent thinking, hands-on experimentation, and problem-solving abilities.

ng abilities.

Connected Concepts

Connected Articles

Citation

Li, S. (2025). Artificial Intelligence in Science Learning within the Framework of Situated Learning Theory: A Qualitative Investigation of Teachers' Perspectives. Creative Education, 16(11), 1858–1882.