The integration of Virtual Worlds (VW) and Intelligent Tutoring Systems (ITS) represents a transformative advancement in education, combining immersive, interactive learning with AI-driven personalization. This study explores the synergies between these technologies, analyzing their benefits, challenges, and applications in domains such as medical training, STEM education, and language learning. Findings highlight their shared characteristics of adaptability, real-time feedback, and collaborative learning. However, challenges such as computational demands, pedagogical complexity, and ethical concerns must be addressed. Future research should focus on hybrid models leveraging blockchain, IoT, and augmented reality to enhance adaptive and scalable learning experiences.

University dropout rates in Europe pose a significant challenge to achieving the European Union’s target of 45% higher education attainment among 25–34-year-olds by 2030. This pilot study introduces an innovative framework, the Integrated Theory-Driven ML Dropout (ITMD) Model, which integrates advanced Machine Learning (ML) techniques with established educational theories, including Tinto’s Dropout Theory, Expectancy-Value Theory, Self-Determination Theory, and the Hardré and Reeve Model. The UnitelmaSapienza (2021) dataset was employed for this initial study to develop and implement a stacked classifier architecture. The model integrates Random Forest, Support Vector Machine (SVM), and Gradient Boosting at the base level, with eXtreme Gradient Boosting (XGBoost) serving as the meta-learner, creating a robust and efficient predictive framework. The model achieves 93% accuracy, precision and recall rates of 91–95%, and an AUC-ROC of 0.94, demonstrating robust and balanced dropout prediction. This ITMD Model proposed an ensemble-based approach that significantly improves over traditional methods, particularly in the early identification of at-risk students, offering educators and policymakers a powerful tool for targeted interventions. By bridging ML advancements with theoretical foundations, the research presents a novel and impactful solution to address dropout challenges globally and especially for European higher education, supporting both institutional and societal goal.