A Framework for Effective Utilisation of Artificial Intelligence in Education

Purpose: The continuously evolving Artificial Intelligence (AI) oriented artefacts are transforming every facet of daily life, including the education sector. Recognising education’s critical role in enhancing citizens’ quality of life, it becomes essential to explore how AI can revolutionise education, including learning and teaching processes, educational settings, learning outcomes, among other components. However, the complexity and scale of AI developments pose significant challenges to its effective implementation in educational contexts.

Method: Integrating AI in education has substantial implications on learning and teaching. On the one hand, AI might increase the accessibility to personalised and satisfactory learning experiences. On the other hand, challenges such as bias, privacy and digital divide, exacerbate the difficulties associated with deploying AI effectively in educational settings. A detailed qualitative analysis of principal AI frameworks, models and theoretical foundations has been undertaken to identify and assess factors influencing these challenges.

Findings: This study presents an holistic examination of AI in education, focusing on theoretical frameworks, models and practical implications. It derives a conceptual framework aimed at promoting high-quality education, thereby supporting the achievement of Sustainable Development Goal (SDG) 4, which emphasises Quality Education.

Originality: This conceptual framework uniquely addresses the gap between the efficient use of AI in education and the attainment of SDG 4. Furthermore, it lays the groundwork for combining research efforts to address the ever-expanding research gap concerning effective employment of AI in education and broader life contexts. The study also suggests several directions for developing contextualised strategies for the implementation of AI in education.

Research Limitations: This study aims at gaining meaningful insights from the application of AI in education; however, it cannot accommodate every single educational or learning approach. Therefore, testing this framework with real world contextualised scenarios remains essential to avoid abstract outcomes.