Augmented Reality, Deep Learning, and Junior High School Students’ Learning Motivation: A Systematic Literature Review

Augmented reality (AR) provides interactive visualization, whereas the term deep learning may refer either to artificial intelligence algorithms or to a pedagogical approach. Conflating the two meanings risks overstating claims about their combined influence on learning motivation. This systematic literature review re-examines the relevant evidence for junior high school (SMP) students, distinguishing AR research without integration from pedagogical deep learning interventions and computationally integrated systems, and critically examines the study selection records in the initial manuscript. A review guided by PRISMA principles was used to structure the reported search process, eligibility criteria, and narrative evidence synthesis. The initial draft reported 512 records identified and 48 articles included. However, the list of each article and its search records is not yet available for independent verification. The traceable studies indicate that AR has the potential to support motivation and engagement when used under appropriate learning conditions, including research on Indonesian junior high school students that reported higher motivation in AR classes than in comparison classes. Direct evidence that neural-network-based AR provides an additional motivational benefit specifically for junior high school students remains insufficient in the available material. More replicable screening records and direct comparative studies are needed before stronger claims of effectiveness can be made.