Revolutionizing Technology Education with Artificial Intelligence and Machine Learning: A Comprehensive Systematic Literature Review - Hakimi, Musawer; Zarinkhail, Mohammad Shuaib; Ghafory, Hamayoon; Hamidi, Shir Ahmad (TIERS Information Technology Journal, 2024)
Machine learning and artificial intelligence in education will help to personalize the student learning process, reduce the time wastage in imploding administration systems, and innovate teaching methods. The article reports the findings of a study on the effects of these technologies on the educational systems of application, benefits, and challenges and looks forward to the implications. This has been realized through a systematic review of peer-reviewed journal articles, government reports, and policy documents published between 2021 and 2024. Results show great benefits, including enhanced personalized learning experiences and administrative efficiencies, but also highlight several challenges, such as equitable access, data privacy, and the need for professional development of educators. Rather, this research outlines the imperatives that there is a need to address challenges for the realization of the potential of AI and ML in education. The paper makes recommendations for key stakeholders and points out areas for possible future research to guide sustainable and ethical integration into educational systems. Further research should be done to understand whether these technologies affect student outcomes in the long term and are applicable with the same efficacy in other cultural and socioeconomic contexts.