The potential of AI in education is vast, particularly in the areas of tutoring, assessment, and personalized learning, and many possibilities are yet to be discovered. While AI innovation in education has evolved from laboratory scenarios to real-life learning contexts, the greatest promise of AI lies in personalizing learning through adaptive learning, machine learning, ontologies, semantic technologies, natural language processing, and deep learning. A learner-focused AI system can help students study a subject, suggest adaptive learning paths to achieve learning goals, predict student performance, identify their strengths and weaknesses, and recommend ways to improve through tests or practices. Despite the worldwide interest in AI, research on its application in higher education is still in its early stages. AI will mainly impact personalized education by providing automated assistance, especially in virtual interaction contexts. VR technologies are also promising in the “Edtech” space due to their immersive nature, ability to offer virtual experiences, and potential to mitigate barriers from cost or distance. Adaptive technologies and VR tools make the educational process more interactive, engaging, and contextual, and VR games and simulations provide highly interactive and engaging learning experiences for learners in risk-prone environments. AI can be applied to control and adapt VR to provide personalized experiences, as well as feedback and analytics that offer deep insights into learning and behavior. HECOF proposes a transdisciplinary approach involving partners from different sectors to push forward the state-of-the-art in learning technologies by creating a VR-immersive and AI-adaptive pedagogical model for chemical engineering students. The HECOF system will integrate VR and AI for simulation-based learning, classify students based on proficiency performance benchmarks, adjust to individual needs detected by AI algorithms, and provide solutions, support, and educational measures that respond to adaptive education models. The project will also involve training teachers on the use of the HECOF system before the pilot activities begin and using a co-design process for system development, prototyping, and testing with users (students and teachers). The project will cater to the needs of students of different genders, disabilities, and learning outcomes by involving them in the co-design process.