Empowering Distance Education with Artificial Intelligence

Abstract

This article investigated the integration of Artificial Intelligence (AI) in the context of Distance Education (DE), with the aim of exploring its advantages, disadvantages, and the challenges faced by teachers and students. The research focused on how AI can be employed to promote meaningful learning, using a bibliographic research methodology, as proposed by Severino (2007). This approach involved the critical analysis of existing literature, including relevant case studies and theories pertinent to the use of AI in education. The main authors cited were Castro (2002) and Tavares, Meira, and Amaral (2020), whose works provided insights on the application of Intelligent Tutoring Systems (ITS) and other AI technologies in education. The literature review highlighted the potential of AI to personalize the learning experience and the associated challenges, such as the need for adequate infrastructure, digital skills, and ethical considerations. A case study from Georgia State University illustrated a successful practical application of AI to prevent student dropout, offering a model for future implementations in DE. The analysis showed that, despite obstacles, the integration of AI in DE has the potential to positively transform education, offering opportunities for more adaptive and personalized learning. In conclusion, the article emphasized the importance of addressing technical, ethical, and pedagogical challenges in adopting AI in education, highlighting the need for careful strategies that ensure the effectiveness and inclusivity of technological interventions in DE.