Generative Artificial Intelligence (GAI) is rapidly reshaping pedagogical practices and offering new opportunities to advance sustainability within higher education. This study investigates the extent to which postgraduate students utilize GAI to support Sustainable and Environmentally Responsible Teaching Practices (SERTPs), and examines whether this use varies across demographic, academic, and technological characteristics. A descriptive quantitative design was employed, involving 310 postgraduate students from the College of Education at King Khalid University. Data were collected using a validated and highly reliable instrument measuring five dimensions of GAI-supported sustainable teaching. Descriptive and inferential analyses, including t tests, one-way ANOVA, and LSD post hoc comparisons, were conducted. The findings reveal that postgraduate students demonstrate a moderate overall level of GAI use in advancing SERTPs, with the highest engagement occurring in the promotion of sustainable educational practices. Significant differences were only found in relation to students’ levels of technology use and students’ levels of GAI use, indicating that frequent and sophisticated engagement with AI tools is the strongest predictor of sustainable teaching practices. No significant differences emerged across gender, age, academic department, program level, or specialization. The study highlights the need for targeted training and institutional strategies that enhance students’ AI proficiency, thereby enabling GAI to serve as a catalyst for environmentally responsible and sustainable teaching practices in higher education.
Al-Shamrani et al. (Tue,) studied this question.