Experimentation of BIM and AI software to support Adaptive Learning System in interior design course

Current undergraduate students, particularly Generation Z, are digital natives who have grown up with digital technology and exhibit unique learning characteristics that necessitate new approaches in higher education. An Adaptive Learning System in education involves leveraging technology to accommodate individual students' unique needs and preferences. This research aims to enhance learning effectiveness and design processes in interior design courses, with the case study Interior Design II course at Telkom University, Indonesia. The course currently offers limited software options for interior layout design, which may hinder students' abilities and preferences. This study compares three software tools—Autodesk AutoCAD, Building Information Modeling (BIM) software Autodesk Revit, and Artificial Intelligence (AI)-based plugin PlanFinder—to determine which is most effective in improving students' understanding and simplifying the design process. The research methodology employs a mixed-method approach, integrating qualitative methods such as literature reviews and Focus Group Discussions (FGDs) with quantitative methods like experimentation workshops and pre-test and post-test questionnaires analyzed using SPSS software. The results demonstrate that Autodesk Revit, a BIM software, notably enhances the design process's effectiveness, particularly within the Interior Design II course context. Consequently, the study recommends the implementation of Adaptive Learning Systems that allow students to select software based on their capabilities and preferences. The three software tools/plugins examined in this study can be considered for integration into interior design courses. Furthermore, future research should seek to broaden the sample size and evaluate additional AI tools in interior design courses for comparative analysis