A Systematic Review of AI-Based Mobile Learning Environments: Unveiling Trends and Future Directions

Abstract

The diversity of mobile devices and the increasing availability of technology solutions support the growth and popularity of mobile learning environments. The ubiquitous nature of mobile devices has revolutionized learning, fostering the rise of mobile learning (mlearning). In combination with AI applications, m- learning environments further increase the potential for providing individualized solutions. This literature review delves into the current landscape of AI-based m-learning research. The findings are expected to unveil the immense potential of AI in transforming mlearning. Artificial intelligence's capabilities to personalize the learning experience, optimize the assessment process, and automate content adaptation and creation provide the opportunity to make mlearning more engaging and interactive with the potential offered by learning anytime, anywhere. The aim of this systematic review is to assess the current situation regarding the coordinated use of mobile learning and artificial intelligence applications. Recent studies in the last five years (2019-2023) were analyzed in Web of Science and Scopus databases. The systematic review was conducted in accordance with the PRISMA guidelines, and the relevant studies were analyzed with MAXQDA 24. The results include trends in research on applications used, personalized learning experience, independent learning, performance assessment and feedback, interaction, theoretical frameworks. Suggestions for future research are discussed based on the research results