Artificial Intelligence Literacy for STEM Teachers: A PRISMA-Based Systematic Review

Abstract

Rapid advancement of the Artificial Intelligence (AI) transformed the education system and particularly the STEM. In this case AI literacy has entered into scene as a requisite skill that educators need to possess to effectively integrate AI technologies in teaching and learning processes. The present study article is a scientific literature review of the research subject of AI literacy in STEM educators according to PRISMA (Preferred Reporting Items to Systematic Reviews and Meta-Analyses) template. The review presents the findings of selected peer-reviewed articles in order to comment on the conceptualization, central dimensions, educational practices, issues, and the emergent trends of AI literacy. The findings reveal that AI literacy is a multidimensional construct which constitutes of five broad dimensions which include conceptual understanding, technical skills, pedagogical integration, ethical awareness and data literacy. Though it was only in recent studies that the issue of holistic competencies has been addressed, all the prior studies were highly technical, and did not give much consideration to pedagogical and ethical factors. Other AI-based pedagogical applications cited in the review are intelligent tutoring system, adaptive learning system and AI-powered assessment and feedback system which can be used to enhance the efficiency of teaching and to make learning personal. Despite such developments, it has also come with several challenges that include teacher training, poor infrastructure, ethical and privacy issues, and unwillingness to adopt technology among the learners and policy loopholes. At the same time, new directions covered by AI-driven curriculums, inter-disciplinary pedagogy, career progression and growth, institutional and academic reforms of the policy level imply the growing institutional and academic interest in AI literacy. The article concludes that the literacy regarding AI is the solution to educating teachers in STEM disciplines to meet the demands of the increasingly technological educational landscape. However, the unavailability of the standardized hierarchy of AI literacy can be regarded as the primary flaw that needs to be filled by further studies to develop the frameworks and methods of its evaluation on the same platform. The findings of this review may be educative to teachers, policymakers, and researchers and contribute to the creation of the strategy that is efficient to integrate AI in STEM education.