The goal of this research is to stimulate active, student-centered learning by integrating multi-user virtual environments (MUVEs) supplemented by computational intelligence in sociology education. It aims to revolutionize existing teaching approaches in sustainability education. Urbanization, migration, and social stratification are all real-world sociological issues that MUVEs help students model through interactive, personalized, and immersive experiences powered by cutting-edge AI algorithms. The study used a quantitative approach and included 37 undergraduates who took an MUVE-based eight-week sociology course. Pre- and post-tests, surveys, and group projects yielded results showing considerable gains in both academic achievement and participation. The findings of the posttest showed a significant improvement when compared to the pretest, and the results were more consistent overall, as seen by the lower standard deviation. Students praised MUVEs for their ability to improve digital literacy, critical thinking, and teamwork via the use of gamified features, interactive simulations, and AI-driven situations. Results show that MUVEs help students develop computational intelligence abilities by driven AI tools to learn the social phenomena and ethical reasoning in addition to bridging the gap between theory and practice. The study highlights the power of MUVEs to build learning ecosystems that are inclusive, engaging, and adaptive, even when there are obstacles such as uneven access to technology and different degrees of digital literacy. Further research is necessary to optimize instructional designs and practices that address these obstacles while ensuring equitable and sustainable implementation in diverse educational environments. The study concludes that MUVEs are essential in updating schools to match the needs of a technologically advanced society.