Impact of GenAI-Powered Adaptive Learning Environments on Student- Centred Learning Outcomes in Built Environment Education

This descriptive survey examined the impact of GenAI-powered adaptive learning environments on student- centred learning outcomes in built environment education in South East Nigerian universities. Guided by two research questions and one null hypothesis, data were collected using a convenience sample of 1000 respondents through validated structured questionnaire (QGALESCLOBEE), with a Cronbach Alpha reliability coefficient of 0.84 and were administered by the researchers and five assistants. Data were analyzed using mean and standard deviation and t-test statistics at a 0.05 significance level. Findings revealed implementation challenges as constant technical disruptions, limited software access, institutional resistance, limited digital literacy and lack of awareness about GenAI’s benefits. It further revealed significant impacts on student-centred learning outcomes, including personalized learning pathways, fostered active learning and problem-solving, accommodation of diverse learning styles such as visual, auditory, delivery of actionable insights for instructors, and development of industry-specific technical proficiency. The study concluded that GenAI-powered adaptive learning environments can revolutionize student-centred learning outcomes in built environment education by personalizing learning, fostering engagement, supporting diverse styles, and building industry-relevant skills. It recommended that universities should invest in reliable, high-speed internet infrastructure and up-to-date software; educators should integrate personalized pathways, active problem-solving and diverse learning styles into curricula. Pedagogical Integration of Artificial Intelligence and Digital Construction Technologies in Quantity Surveying and Construction Management Education in Nigeria Arijeloye, Bamidele Temitope1, Ramabodu, Stephan Molusiwa2 and Chikafalimani, Samuel Herald3 Department of Construction Management and Quantity Surveying,