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All Journal JPF : JURNAL PENDIDIKAN FISIKA Mobile and Forensics Jurnal Riset Teknik Komputer
Muh. Al Amin
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science Neuroscience Physics Other

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Journal : Mobile and Forensics

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Design and Expert Validation of AI-Supported Collaborative Digital Learning Model for Introductory Multimedia Course SPADA Indonesia Muh. Al Amin; Ahmad Fatoni Dwi Putra
Mobile and Forensics Vol. 8 No. 1 (2026)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v8i1.15407

Abstract

This study develops and conceptually validates an AI-Supported Collaborative Digital Learning (AI-CDL) model for an Introduction to Multimedia course delivered through the national LMS, SPADA Indonesia. Using a Design and Development Research approach aligned with early-stage Design-Based Research, the study followed four phases: (1) contextual and needs analysis of course outcomes,  commonly referred to as CPL (Capaian Pembelajaran Lulusan) and CPMK (Capaian Pembelajaran Mata Kuliah), existing learning activities, and available LMS affordances; (2) conceptual model design grounded in collaborative learning theory and multimedia learning principles; (3) development of project-based collaborative scenarios and supporting artefacts (learning paths, assessment rubrics, and responsible AI-use guidelines); and (4) conceptual validation through expert review and alignment with recent evidence syntheses on AI-supported collaboration in higher education. The resulting AI-CDL model operationalizes AI support across three layers intelligent content support, AI-supported collaboration, and AI-augmented production workflows mapped to key multimedia topics and implemented through SPADA activities. Expert feedback informed iterative refinements, particularly in task orchestration, assessment transparency, and ethical safeguards. This study contributes a validated design blueprint and transferable design principles for integrating AI into collaborative multimedia learning within a national-scale LMS. Future work will empirically evaluate learning processes and outcomes through classroom implementation and learning analytics.
Co-Authors Ahmad Fatoni Dwi Putra Juniarti Iryani Nurwahid Syam, Nurwahid Rakhmadi Rahman