Human-AI Educational Collaboration: Facing Learning Challenges in the Digital Age

Digital transformation in education has driven the integration of artificial intelligence (AI) as a key element in personalising learning, managing educational institutions, and supporting pedagogical decision-making processes. However, the application of AI also raises ethical challenges, access gaps, and fundamental changes in the role of teachers. This research aims to identify and classify the primary dimensions of human-AI collaboration in education through a qualitative approach, utilising a systematic literature review of 50 scientific articles published over the last five years. The articles were selected based on their thematic relevance from the Google Scholar and Scopus databases and analysed using NVivo software to cluster the dominant codes in the literature. The analysis resulted in four main components: Adaptive Learning with Artificial Intelligence (ALEAI), Artificial Intelligence in Education (AIED), Ethical Challenges in AI Education (EAIED), and Teacher Roles in AI-assisted learning (TRAIL). The findings indicate that AI has significant potential to enhance the efficiency and inclusivity of learning but also necessitates robust regulations in data protection, algorithm bias mitigation, and teacher training. This research contributes to the formulation of a conceptual framework for developing fair, ethical, and sustainable AI-based education policies.