Aug 2026· Frontiers in Education· 0 citations· 38 references
TL;DR
The concept of the “illusion of teaching competence” is introduced as a distinct theoretical construct, referring to the overestimation of pedagogical expertise derived from technological fluency and instrumental performance, and differentiating it from related constructs such as self-efficacy and competence overestimation.
Abstract
The accelerated integration of artificial intelligence (AI) in education has intensified debates on the reconfiguration of teaching competence and the professional status of the teaching profession. Although recent research has increasingly examined teachers’ digital competence, AI literacy, and attitudes toward technological tools, the pedagogical and professional dimensions of teaching competence remain under-theorized. This study presents a critical integrative review incorporating systematic elements of international literature published between 2018 and 2025, aiming to examine how teaching competence is conceptualized and redefined in the context of AI use in education. The final corpus comprises 15 studies selected through explicit inclusion and exclusion criteria and analyzed using thematic and interpretive synthesis. The findings indicate a recurring tendency to operationalize teaching competence in terms of technological proficiency, AI tool use, perceived usefulness, and instructional efficiency, while the situated, relational, reflective, and decision-making dimensions of teaching are less systematically addressed. Across the reviewed literature, a discrepancy emerges between high levels of self-efficacy in AI use and limited evidence of pedagogically grounded justification, suggesting a gap between perceived competence and pedagogically grounded professional expertise. Building on this synthesis, this study introduces the concept of the “illusion of teaching competence” as a distinct theoretical construct, referring to the overestimation of pedagogical expertise derived from technological fluency and instrumental performance, and differentiating it from related constructs such as self-efficacy and competence overestimation. By articulating this concept, the study provides a theoretical lens for understanding how evaluative criteria centered on technological performance may obscure the pedagogical foundations of teaching competence in AI-mediated contexts. The findings suggest that AI contributes to the professionalization of teaching only when integrated within pedagogically grounded frameworks that support reflective practice, pedagogical judgment, and context-sensitive decision-making.
The study proposes the incorporation of “epistemic hygiene,” understood as the systematic development of competencies in critical judgment, comparison, and validation of knowledge generated by algorithmic systems.
Artificial Intelligence (AI) is rapidly transforming educational practices and challenging conventional understandings of teaching, learning and teacher professionalism. The emergence of generative AI, intelligent tutoring systems, adaptive learning platforms and AI-supported assessment has created new possibilities for improving educational efficiency, personalisation and accessibility, while simultaneously raising concerns related to accuracy, bias, privacy, academic integrity, professional autonomy and human agency. Against this backdrop, the present study explores how teacher education can be reimagined for an AI-intensive educational environment through a human-centred pedagogical perspective. The study adopts a qualitative, review-based approach, drawing upon scholarly literature, systematic reviews, international frameworks and Indian educational policy documents. The findings indicate that teacher education in the AI era requires a broader conception of teacher competence encompassing AI literacy, pedagogical integration, ethical and critical judgement, human–AI collaboration and continuous professional learning. The study further identifies the need to integrate AI across teacher education curricula rather than treating it as an isolated technological component. Based on the synthesis of the reviewed literature, a Human-Centred AI-Integrated Teacher Education Framework is proposed, comprising six interconnected dimensions: human purpose, AI literacy, AI pedagogical integration, ethical governance, professional agency and continuous professional learning. The study argues that AI should augment rather than replace teachers' professional judgement, creativity, relational capacities and ethical responsibility. Reimagining teacher education through this framework can support the development of reflective, technologically capable, ethically responsible and human-centred teachers prepared to navigate the evolving educational landscape.
Prasamita Mohanty, Dr. Pranay Pandey· EPRA international journal o...· 0 citations
By isolating the crucial components of fairness, accountability, and agency which underpin the factors most predictive of teacher readiness, this study lays a framework for leaders and policy makers searching to translate teacher doubt into enthusiastic and responsible carrying out of AI tools.
Laurence Ajaka, Mireille Saba Redford, Randa Saliba Chidiac et al.· Journal of Intelligent Decis...· 0 citations
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.
Dr. Pooja· International journal of res...· 0 citations
A systematic review of peer-reviewed studies published between 2015 and 2024 concludes that while tools such as generative artificial intelligence, intelligent tutoring systems, virtual and augmented reality, and predictive analytics are increasingly present, their adoption is concentrated in specific areas, particularly problem-solving, simulation, and assessment.
Firas Almasri· International journal of tec...· 0 citations
The rapid advancement of artificial intelligence (AI) has transformed educational practices and generated critical debates regarding whether AI enhances teacher performance or threatens the continuity of the teaching profession. This study aims to examine the role of AI in education by analyzing its contributions, limitations, and potential relationship with human teachers. Employing a non-empirical qualitative literature review approach, this research synthesizes international scholarly publications concerning generative AI, personalized learning, classroom management, human-AI collaboration, and the human dimensions of teaching. The findings indicate that AI significantly improves educational efficiency through automation, adaptive learning support, and data-driven instructional assistance. Nevertheless, AI remains limited in performing affective, ethical, and relational functions that constitute essential components of effective teaching. The study concludes that AI is unlikely to replace teachers entirely but will reshape their professional roles through collaborative human-AI models. This research contributes to the theoretical development of hybrid intelligence perspectives in education and provides a comprehensive understanding of technology integration that preserves the centrality of human pedagogical expertise.
Nida Ul Hasanah, Amar Ali Aulia, Muhammad Azhar Abdillah et al.· International Journal of Soc...· 0 citations
