Goals Achieved and Missed

This page is based on the binding target agreement (Zielvereinbarung) (project-management practice project SS 2026, signed by client Lily Dausch, Bundeswehrkrankenhaus Berlin — represented by head of nursing Dagmar Klauck —, course lead Prof. Dr. Heike Wiesner, and Kâan Turan). An earlier version of this page documented the mid-project state; it was updated to the final state after the final presentation (14.07.2026).

Overall result: mission accomplished

All eight goals of the target agreement were achieved:

Priority Achieved
MUST 2 / 2 ✓
SHOULD 2 / 2 ✓
COULD 4 / 4 ✓

The eight goals in detail

MUST goals

No. Goal Success criterion Result
1 Introduction of different patient profiles (age, gender, origin, skin color, body type, mobility) Integration of 5 additional patient models Fulfilled: 6 diverse profiles (A–F) in DB, frontend, and Unity scene — child, non-binary person, middle-aged woman, senior with dementia, obese patient with amputation, patient with language barrier / homelessness (Patient Models)
2 Assessment for improving accessibility (e.g. motion sickness, color blindness) Status quo + written recommendations (approx. ½–1 page) Fulfilled: written assessment by Erik Wlochal — status quo plus prioritized recommendations for future development (Assessment Barrierefreiheit, DOCX); color-vision modes implemented in the frontend (protanopia, deuteranopia, tritanopia, achromatopsia)

SHOULD goals

No. Goal Success criterion Result
3 VR patient file as preparation for further (diversity-oriented) error sources Clickable patient file exists; completeness flexible ✅ Interactive clipboard in VR (PatientFileUI): multi-page file per patient, with file errors and decision dialogs (interpreter, missing address, allergy)
4 Fixing technical errors and improving stability At least 50 % of the improvements raised by Kâan resolved 100% Goals Fulfilled: Incl. PostgreSQL migration, native UUIDs, Zod validation of all endpoints, startup config validation, error logging, WebSocket layer, patient-bed decoupling in Unity

COULD goals

No. Goal Success criterion Result
5 Comprehensive manual for hosts and users First draft / concept proposals sufficient Exceeded (two complete manuals instead of a first draft): detailed German user manual for hosts and non-technical users by Semi Kaan Baskaya (Manual Room of Horror, DOCX) plus a VR-focused manual for trainers and lecturers by Jacob Gotter (Nutzerhandbuch Room of Horror VR, PDF); additionally setup and workflow guides (Local Setup, Game Start), FAQ page in the frontend, tutorial video (room-of-horror-assets/Room of Horror Tutorial.mp4), onboarding tour in the dashboard
6 Diversity-oriented expansion of existing error sources 1 new error source added Exceeded: 13 new errors (IDs 19–31), all diversity-related — incl. child bed, bariatric bed, dementia sensor mat, interpreter decision (Error Catalog)
7 Weighting of errors by severity of medical consequences + revision of the results dashboard Revision of the weighting ✅ Weighted error catalog (weight 1–5, criticality, categories), rule-based evaluation engine, new results dashboard (EvaluationPanel with category breakdown and trainer feedback)
8 Evaluation / prototypical integration of AI-supported functions with diversity relevance Short feasibility study outlining application areas ✅ Feasibility study by Jan Busson — Room of Horror 3.0: KI-Machbarkeitsstudie (PDF): three solution approaches (AI-generated audio tracks, controlled speech interaction, dynamic virtual patient) with Unity roadmaps, diversity application areas, and open questions for future teams; AI patient conversations deliberately not implemented in 2.0

Deliberately excluded (per target agreement, section “Delineation”)

  • Complete redevelopment of the application
  • Production-ready launch / app-store release
  • Photorealistic rendering of the scenarios

Additionally de-scoped during the project (stability before feature count): implemented AI patient conversations, multilingualism, hint system, subtitles — see Requirements Catalog.

Reflection

What went well:

  • Early and regular alignment with Lily Dausch kept the requirements realistic
  • Focusing on stability instead of feature count proved itself
  • Iterative approach with weekly feedback rounds

What we would do differently:

  • Fix requirements in writing earlier (target agreement only in week 9)
  • Consider accessibility from the start instead of as a downstream task

Information sources

Last build: 19 Aug 2026, 05:20+00:00


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