Adaptation of Artificial Intelligence in Learning and Teacher Professional Well-Being in the Era of Educational Transformation
Keywords:
Artificial Intelligence in Education, Teacher Professional Well-Being, Educational Transformation, Digital Adaptation, AI IntegrationAbstract
Digital transformation has fundamentally altered the educational landscape, positioning artificial intelligence (AI) as a catalyst for significant pedagogical innovation. This study examines the adaptation of AI in learning processes and its implications for teacher professional well-being during the era of educational transformation. Employing a library research methodology, this study systematically analyzed peer-reviewed articles, books, and academic documents retrieved from Google Scholar, Scopus, and Web of Science databases, published between 2020 and 2026, using content analysis technique. The findings reveal three interconnected themes: (1) the rapid development of AI adoption in education, driven by generative technologies and the growing need for adaptive, data-driven learning; (2) the dual nature of AI implementation, presenting opportunities such as personalized learning, administrative efficiency, and enhanced pedagogical decision-making, alongside challenges including digital competence gaps, ethical concerns, and unequal technology access; and (3) the varied implications for teacher professional well-being, where effective AI integration can enhance work efficiency, self-efficacy, and professional satisfaction, while insufficient support structures risk increasing cognitive load and occupational stress. These findings underscore the necessity of sustained institutional support, targeted digital competence training, and evidence-based policy frameworks to maximize the benefits of AI for both teachers and learners in an increasingly technology-mediated educational environment.
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