A systematic review of literature reviews on artificial intelligence in education (AIED): a roadmap to a future research agenda - Muhammad Yasir Mustafa; Ahmed Tlili; Georgios Lampropoulos; Ronghuai Huang; Petar Jandrić; Jialu Zhao; Soheil Salha; Lin Xu; Santosh Panda; Kinshuk; Sonsoles López-Pernas; Mohammed Saqr (Smart Learning Environments)
Abstract Despite the increased adoption of Artificial Intelligence in Education (AIED), several concerns are still associated with it. This has motivated researchers to conduct (systematic) reviews aiming at synthesizing the AIED findings in the literature. However, these AIED reviews are diversified in terms of focus, stakeholders, educational level and region, and so on. This has made the understanding of the overall landscape of AIED challenging. To address this research gap, this study proceeds one step forward by systematically meta-synthesizing the AIED literature reviews. Specifically, 143 literature reviews were included and analyzed according to the technology-based learning model. It is worth noting that most of the AIED research has been from China and the U.S. Additionally, when discussing AIED, strong focus was on higher education, where less attention is paid to special education. The results also reveal that AI is used mostly to support teachers and students in education with less focus on other educational stakeholders (e.g. school leaders or administrators). The study provides a possible roadmap for future research agenda on AIED, facilitating the implementation of effective and safe AIED.