Artificial Intelligence Integration in Competency-Based Teaching: Prospects and Challenges

Abstract

The rapid development of artificial intelligence technologies has brought significant changes to various fields, particularly education. These technologies have contributed to the emergence of more interactive, flexible, and adaptive teaching methods that respond to learners’ individual differences and educational needs. In this context, competency-based teaching has become an important educational approach that seeks to enable learners to mobilize their knowledge, skills, and attitudes in order to address complex academic and real-life situations, rather than merely memorizing and reproducing information. Based on the convergence between the potential of artificial intelligence and the objectives of competency-based teaching, this study examines how artificial intelligence applications can be employed in designing educational activities, personalizing learning pathways, providing immediate feedback, and developing assessment methods based on learners’ actual performance and achievement. It also discusses the impact of artificial intelligence on the educational process and its role in enhancing teachers’ digital competence. In addition, the study addresses several challenges, including inadequate digital infrastructure, insufficient teacher training, algorithmic bias, data privacy concerns, and the limitations of artificial intelligence systems in processing certain linguistic and contextual features of the Arabic language. The study adopts a descriptive-analytical approach to present the main concepts and analyze the opportunities and challenges associated with the topic. It concludes that the effective integration of artificial intelligence into competency-based teaching requires pedagogically informed use, continuous teacher training, and clear ethical and institutional frameworks that ensure the improvement of learning quality without diminishing the teacher’s role or the learner’s autonomy.