This study aims to critically examine the strategic integration of artificial intelligence (AI) solutions within higher education, with a focus on transforming teaching practices and enhancing student learning outcomes.
A systematic review of the literature was conducted to identify the current use of AI in higher education teaching and learning. The paper also identifies, explains and critically discusses the benefits and limitations of AI integrated with different theoretical frameworks.
AI tools enhance teaching practices and student learning experiences by streamlining repetitive tasks, enabling personalized learning and facilitating early interventions. However, integrating AI in higher education is not without challenges, such as technical challenges like interoperability and scalability, organizational challenges, privacy and data issues and algorithmic bias and security, among others.
This study is constrained by its reliance on a literature review, potentially overlooking perspectives better explained through empirical methods. Future research should use mixed-method and longitudinal designs to develop a more detailed understanding of how AI integration is applied.
Effective AI integration in higher education requires a strategic approach, including comprehensive faculty training, interdisciplinary cooperation and intensive stakeholder involvement.
Using AI technologies can greatly enhance student outcomes, improve access and equity and prepare learners for success in the 21st century, fostering inclusive and supportive educational environments.
This study explains AI’s transformative potential in higher education and highlights essential considerations for its responsible implementation. It gives particular insight into how AI might influence future learning and teaching, focusing on ethical guidelines and interdisciplinary cooperation.
