| Authors |
Águeda, Marta ; Carro, Luis ; Marconi, Andrea ; Bartoletti, Arianna ; Leone, Renato De ; Montagna, Anita ; Borghi, Pietro ; Karakatič, Sašo ; Pečnik, Špela ; Spanu, Paulina ; Vaiginienė, Erika ; Butkevičienė, Jurgita |
| Abstract [eng] |
This handbook explores how High Intelligent Tutoring Systems (HITS) can support academic success and innovation in higher education by leveraging the latest advances in artificial intelligence. It offers a comprehensive overview of Intelligent Tutoring Systems, from their definition, history, and pedagogical foundations to their current and potential applications in personalized learning, dropout prevention, academic and career guidance, and student performance analysis. The document situates HITS within the evolving international regulatory and ethical landscape, presenting key guidelines and principles from UNESCO, OECD and the European Union, including the EU AI Act and FATE (Fairness, Accountability, Transparency, Ethics) approaches. Particular attention is paid to issues such as bias, transparency, data protection, implementation costs, and user acceptance among students and educators, which are critical for responsible and sustainable deployment. Building on empirical evidence from focus groups and questionnaires with students, professors, and tutors, as well as on real-world case studies (e.g. MATHia, Panther Retention Grant, Brightspace Insights, Course Signals, IBM Watson), the handbook identifies concrete needs and priorities for higher education institutions considering the adoption of ITS. It concludes with practical recommendations and lessons learned to guide the design and implementation of user-centred, inclusive, and ethically grounded HITS, with a clear focus on improving teaching, learning, and assessment processes across diverse educational contexts. |
