The Mediating Role of Artificial Intelligence-Driven Learning Personalization in the Relationship between Smart Classroom Integration and Student Adaptive Performance in the Education Industry Jordan

Abstract

The fast pace of digitalization and growing expectations of future-competencies are forcing educational facilities to restructure the process of teaching and learning so as to improve the adaptability and performance of students. In an attempt to meet this objective, in Jordan, institutions are incorporating smart classroom technologies and implementing AI-based learning personalization in adaptive learning ecosystems. Nonetheless, earlier studies indicate that the adoption of smart technologies does not necessarily result in significant gains to adaptive performance by students. This paper, therefore, examines the effects of smart classroom integration on adaptive performance of students in the form of mediator AI-based learning personalization in the Jordan education sector. The study model was created and tested on the sample of 372 educational establishments, with the help of PLS-SEM. The research model suggests 4 hypotheses related to the constructs. The results indicate that adaptive performance of students increases tremendously when smart classroom integration is effectively implemented. Moreover, the findings reveal that learning personalization via AI is a key mediating factor in enhancing student adaptive performance/smart classroom integration. The paper is theoretically relevant to the extent that it gives empirical evidence in favor of applying adaptive learning ecosystem views to Social Cognitive Theory and Technological Pedagogical Content Knowledge (TPACK), with a mediating role of AI-based personalization. Practically, the study provides useful ideas to educational policymakers and institutions in Jordan to develop data-driven and individualized learning plans to facilitate student flexibility and future readiness in dynamic learning environments.