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Agentic Course Redesign

GIAN PETER OCHSNER · Education & Research

ChatGPTApp

◆ LECTURER / TEACHER CONTROL • You retain every consequential decision. The Course Redesign Orchestrator is the sole lecturer-facing interface. ◆ SPECIALIST TEAM (10) • Course Mapper and Learning-Outcomes Auditor; Active-Learning Researcher; AI Integration and AI-Competence Researcher; Student Experience, Accessibility and Workload Proxy Critic; Assessment and Constructive-Alignment Designer. • Source Verification and Citation Auditor; Evidence and Feasibility Red Team; Learning Designer; Learning Material Designer; Artefact Accessibility and Visual QA Auditor. The student-experience role is a design-review proxy and never authorises identifiable student data. ◆ GATED WORKFLOW • Gate 0A: verify ownership/processing authority, sensitivity, student data, protected assessment and environment before any source path or content. • Gate 0: confirm sources, rights, tools and egress. Gate 1: confirm the course brief and a fresh run. • HITL 1: approve focus after preliminary mapping. Research, source verification, cross-specialist synthesis, assessment integration and red-team review lead to HITL 2. • Gate 3: approve the integrated blueprint and file plan. Material production creates only approved working copies, followed by evidence, accessibility, visual, alignment and assessment-security QA. • Verify production handoff before HITL 3; accept, revise or reject each artefact. • Request or decline final system review; the accepted run becomes complete and dormant until a later manual or separately approved scheduled trigger creates a fresh run. ◆ DECISION DIALOGUE • One unresolved question at a time. • Use a card only if the live host can show the complete option set plus custom answer. Verified current Codex in Plan mode: 2–3 explicit choices plus automatic Other. • If capacity is unknown, unavailable or exceeded, use ordinary chat with every valid numbered option plus Other, then wait. Never prune, hide or combine valid options to fit a card. • Long sets may use dependency-based chunks with every option visible; the lecturer may split, merge, reorder or rename them. • Preserve custom answers verbatim, show editable recaps, never preselect recommendations and fail closed on uncertainty. ◆ BOUNDARY • The plugin does not register schedules, start runs, publish content, add connectors or change permissions.

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