Machine Learning in Education: Innovations, Impacts, and Ethical Considerations

Machine Learning (ML) has recently emerged as a powerful tool with significant potential to revolutionize education, bringing about fundamental changes in pedagogy and research. Its applications span various domains within academia, including administration, instructional method enhancement, and grade prediction. This study illustrates how ML can enhance the effectiveness of research, instruction, and study strategies by adapting to student needs and leveraging new communication tools within virtual learning environments. The literature review included various research articles sourced IEEE Xplore, Scopus, Web of Science, PubMed, Google Scholar, and ScienceDirect. The inclusion criteria encompassed studies that explicitly defined Artificial Intelligence (AI) within the medical education sector and were published in English with peer review. This study delves into the potential applications of ML and its associated benefits, which can aid researchers in implementing AI-based educational systems.