Artificial intelligence-enhanced STE(Agri)M-based Physics and its effects on pre-service teachers' cognitive adaptability

Abstract

This study investigated how STE(Agri)M-Based Physics with Artificial Intelligence (STPAI) affects pre-service teachers’ cognitive adaptability. From the total of 134 pre-service teacher respondents, this experimental re-search gathered quantitative data through a pre-test and post-test to assess changes in the cognitive adaptability after the teaching approaches. The result highlighted that both STE(Agri)M-Based Physics (STP) and STE(Agri)M-Based Physics with Artificial Intelligence (STPAI) teaching approaches signifi-cantly improved cognitive adaptability (χ²(2) = 26.05, p < .001) of pre-service teachers. However, although no statistically significant differences were found between the STP and STPAI groups (p = 0.822), descriptive analysis showed that the STPAI group offered an advantage, since the aver-age performing students in the STP group align with the lowest performing students in the STPAI. The study concludes that both STE(Agri)M-Based Physics (STP) and STE(Agri)M-Based Physics with Artificial Intelligence (STPAI) teaching approaches significantly improved cognitive adaptability of pre-service teachers as compared to the Conventional Approach in Teaching Physics (CATP).