AI-Mediated Interactional Competence and Multimodal Assessment.

Evaluations of technology-enhanced teaching in higher education increasingly rely on learning analytics, student evaluations, and outcome-based indicators embedded within institutional quality assurance systems. While influential in monitoring performance, engagement, and compliance, these approaches provide limited insight into how responsibility for learning is structurally distributed through pedagogical design, as accountability is inferred primarily from learner behaviour rather than institutional design decisions. This study examines institutional design responsibility as a distinct evaluand within educational evaluation by developing and applying the 5C Rubric, an artefact-based framework for analysing how responsibility for learning is embedded in course design. Grounded in Self-Determination Theory, Cognitive Load Theory, and Self-Regulated Learning, the rubric operationalises five interrelated design principles: Coherence, Cognitive Load, Competence, Completion, and Connection. Applied to a semester-long corpus of educator-generated course artefacts, the analysis identifies a recurring structural pattern in which alignment and mastery progression are consistently embedded, while accountability, reflective integration, and load-sensitive scaffolding remain unevenly institutionalised. The study contributes an artefact-based and ethically proportionate approach to evaluation and accountability in technology-enhanced higher education.