Development and Expert Validation of SciTin AR Learning: Integrating Augmented Reality, Problem-Based Learning, and the Local Tin Mining Context into Junior High School Science

The integration of digital technology and contextual learning has become increasingly important for improving the quality of science education. Although mobile learning, Augmented Reality (AR), and Problem-Based Learning (PBL) have individually demonstrated positive contributions to science learning, few studies have integrated these approaches with local environmental contexts into a single mobile learning platform. To address this gap, this study developed SciTin AR Learning, an innovative science mobile learning application that integrates AR, PBL, and the local tin mining context to support meaningful junior high school science learning. This study aimed to develop and conduct expert validation of SciTin AR Learning. This research employed a Research and Development approach using the Analysis, Design, and Development phases of the ADDIE model. The product was evaluated by four expert validators consisting of two university experts and two professional science teachers using content and media validation instruments. Prior to product evaluation, the instruments demonstrated high content validity based on Aiken's V coefficients, with mean values of 0.987 for the content validation instrument and 0.979 for the media validation instrument. The results showed that SciTin AR Learning achieved a Very Good level of validity, with mean scores of 3.96 for content validity and 3.94 for media validity. Expert feedback led to improvements in application functionality, contextual learning content, literacy integration, and interactive worksheet features. These findings indicate that SciTin AR Learning is a valid instructional product and provides a foundation for subsequent studies evaluating its practicality and effectiveness in junior high school science learning.