An RM-ODP Method to Model PBL Digital Twins for Closed-Loop Supervision

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Abstract
Project-Based Learning (PBL) in software engineering produces heterogeneous evidence across repositories, task boards, classroom activities, and assessments, making timely supervision difficult. This paper presents a two-stage method to model PBL digital twins with the five RM-ODP viewpoints, aligned with ISO/IEC 10746 and ISO/IEC/IEEE 42010 \cite {iso10746, iso42010}. Stage~A models the as-is PBL ecosystem with SADT/IDEF0 and identifies native event points and requirement gaps. Stage~B adds a Digital Twin layer that consumes those events, applies data contracts, correlates patterns through Complex Event Processing (CEP), and delivers near real-time feedback without replacing existing processes. The method structures: goals and governance (enterprise), semantic contracts and traceability (information), event services and CEP rules (computational), distributed pipeline and immutable snapshots (engineering), and implementation choices (technology). An institutional case instantiation demonstrates end-to-end applicability from process modeling to operational supervision signals. The result is a reusable procedure for closed-loop supervision, auditable evidence integration, and longitudinal learning analytics in diverse PBL settings.

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