Artificial intelligence for teaching and learning in schools: The need for pedagogical intelligence

Abstract

Artificial intelligence (AI) has been hailed for its potential to revolutionize teaching and learning practices. Undoubtedly, there has been development, but has it transferred to a new pedagogical trend? Indeed, research shows more tools, software, etc., built through AI, but there is still a limited understanding of its pedagogical impact. This review aims to assess whether AI has indeed led to new pedagogical trends in education using a Human Center AI framework. To accomplish this, a systematic review of research on the pedagogical applications of AI in K-12 contexts was conducted, following the PRISMA guidelines. The review involved an inductive coding analysis of a comprehensive search across WoS, Scopus, and EBSBU. From a pool of 3277 publications spanning 2019 to 2023, 183 papers met the inclusion criteria for detailed analysis. Six categories emerged: Behaviorism, Cognitivism, Constructivism, Social Constructivism, Experiential Learning, and Community of Practices. The findings of this research provide a promising perspective on synthesizing the results based on the pedagogical framework that describes AI implementation. While technological advancements have improved AI capabilities, the application of AI in education largely follows the same principles of previous technologies. This research suggests that the failure to transform education through AI stems from a lack of consideration of Gardner's proposed ninth intelligence type—pedagogical intelligence. Furthermore, this paper offers a critical analysis of the HCAI framework and proposes an adaptation called Pedagogical Centered AI (PCAI) for designing and using AI in K-12 education. Final discussions highlight the implications and future perspectives of AI in educational settings.