EXPLORING THE IMPACT OF AI-BASED PERSONALIZED LEARNING ON UNIVERSITY TEACHERS’ ENGAGEMENT, MOTIVATION, AND PROFESSIONAL ACHIEVEMENT: A MIXED-METHODS STUDY

Abstract

Artificial Intelligence (AI) has emerged as a transformative technology in higher education, particularly through AI-based personalized learning systems that enhance instructional practices and educational effectiveness. This study explores the impact of AI-based personalized learning on university teachers’ engagement, motivation, and professional achievement using a mixed-methods research design. The study aimed to examine how AI-supported educational technologies influence teachers’ professional experiences and instructional performance in higher education institutions of Pakistan. The quantitative phase involved a sample of 300 university teachers selected through stratified random sampling, while the qualitative phase included semi-structured interviews with 15–20 teachers selected purposively. Data for the quantitative phase were collected using a structured five-point Likert scale questionnaire, while qualitative data were gathered through interviews. Quantitative data were analyzed using descriptive statistics, correlation analysis, multiple regression analysis, and Structural Equation Modeling (SEM). Qualitative data were analyzed through thematic analysis, coding, categorization, and NVivo-based theme development. The findings revealed that AI-based personalized learning significantly and positively influences teacher engagement, motivation, and professional achievement. Teachers reported improved instructional effectiveness, enhanced classroom interaction, increased professional confidence, and better academic productivity through AI integration. The study also identified challenges related to digital literacy, lack of training, technological infrastructure, and ethical concerns regarding AI implementation. Overall, the study concludes that AI-supported personalized learning environments contribute positively to teachers’ professional development and educational innovation in higher education. The findings provide practical implications for educational policymakers, university administrators, and institutions aiming to integrate AI technologies effectively within academic environments.