8Df VR Experience Co-Ideation Assistant

Human–AI Collaboration for VR Experience Design grounded in VR theories

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📄 Dimensionality Framework (8Df) Paper:

• Ch’ng E (2026) What’s beyond Presence? Dimensionality, Control and Information Spaces, Presence: Virtual and Augmented Reality 2026(37), MIT Press. Accepted for 2026, Issue 37. doi.org/10.1162/PRES.a.418

• 📊 LLM Comparison Study (ChatGPT / Gemini / DeepSeek):

• Now accepted as Ch'ng E (2026) Human-AI Co-Ideation in VR Experience Design: Using the Dimensionality Framework (8Df) to Structure LLM-Guided Design, Nature Humanities and Social Sciences Communications.
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🎬🎥▶️ Video Explanation:

• What’s Beyond Presence? A Light Look at the VR Dimensionality Framework (8Df) - NotebookLM Podcast Style YouTube
• A Basic View of the VR Dimensionality Framework (8Df) YouTube

In the Chatbot prompt, type 'start' to start using:

• 🔗 ChatGPT Live Demo: [ChatGPT]
• 🔗 Gemini Live Demo: [Gemini]
• 🧠 bot implementation for DeepSeek and other LLMs: [soon]

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1. Overview

The 8Df Co-Ideation Assistant is a human–AI collaborative system that guides users through designing VR experiences using the Dimensionality Framework (8Df)—a theoretical model covering eight VR experiential dimensions:

• Spatial
• Sensory
• Placeness
• Temporal
• Cultural
• Social
• Cognitive
• Psychological

This repository provides the full prompt architecture, workflow logic, and design methodology needed to replicate the assistant across ChatGPT, Gemini, DeepSeek, Claude, and other LLM platforms.

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2. Project Purpose

Why This Project Exists

• To provide a structured, theory-grounded method for VR design
• To evaluate how different LLMs engage in human–AI co-ideation
• To shift VR creation beyond realism toward intentional experience design
• To reduce fragmentation in ideation by guiding designers through eight interdependent dimensions

Goals

• Support creativity with the Dimensionality Framework
• Make VR design accessible to non-experts
• Provide a consistent workflow across AI models
• Produce actionable, implementation-ready output
• Propose visual diagrams and storyboards (depending on modality of the LLM)

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3. The 8Df Co-Ideation Assistant

Core Concept

The assistant functions as:

• A Socratic VR design partner
• A expert mentor enforcing the 8Df framework
• A dialogic generator of scenes, modulations, and effects
• A workflow manager ensuring human-in-the-loop checkpoints

Powered by the ChatBot Brain 🧠

See: bot implementation for DeepSeek and other LLMs:** VR8Df_bot.md

Includes:

• Framework definitions
• Persona, tone, and reasoning rules
• Modulation dials & effects spectrum
• Step-by-step VR design workflow
• Safety, ethics, and feasibility constraints

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4. How to Use

A. ChatGPT or Gemini

1. Go to GPT Builder/Gemini Gems
2. Upload VR8Df_bot.md as system prompt
3. Save as a custom GPT

B. Gemini / Claude / DeepSeek

• Paste the contents of VR8Df_bot.md into the system prompt area
• Recommended: Use “Project Mode” for persistent memory
• Supports long-context workflows

C. Local / Open-Source LLM

• Load the file as system prompt
• Works with Qwen, Llama, Mistral, etc.

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5. 8Df Co-Ideation Workflow

Stage 0 — System Welcome

• Introduces the 8 Dimensional Framework (8Df)
• Provides citation if asked
• Establishes purpose and expectations

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Step 1 — Define VR Experience Goal

The user specifies the primary intent (provide more details):

• Education
• Training
• Empathy
• Culture
• Heritage
• Entertainment
• Research
• and more!

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Step 2 — Scene Planning

• User provides number of scenes and purpose
• If missing, assistant proposes 3–5 scenes
• Ensures coherent pacing + information flow

---

Step 3 — Dimension-by-Dimension Ideation

For each dimension:

1. Provide definition
2. Offer optional tables
3. Suggest modulation dials
4. Explain trade-offs
5. Generate proposals
6. Ask user to confirm → then proceed

Dimensions:

• DM-0 Spatial
• DM-1 Sensory
• DM-2 Placeness
• DM-3 Temporal
• DM-4 Cultural
• DM-5 Social
• DM-6 Cognitive
• DM-7 Psychological

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Step 4 — Human-in-the-Loop Control

• Assistant pauses before each dimension
• Awaits approval
• Maintains workflow state

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Step 5 — Final Synthesis

Output includes:

• Full dimensional summary table
• Scene-by-scene narrative
• Multi-dimensional rationale
• Effects spectrum + modulation summary
• Implementation-ready VR design specification

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6. Core Principles

Framework Principles

• Value-first design → every decision must support the VR goal
• Balanced modulation → dimensions influence each other
• Theoretical fidelity → grounded in 8Df (Ch’ng, 2026)
• Transparency → rationale for every design choice
• Ethical sensitivity → cultural and psychological considerations

AI Collaboration Principles

• AI is a co-ideator, not a replacement for human creativity
• AI structurally supports:
  • Divergent idea generation
  • Reflective analysis
  • Information synthesis
• Human determines final intention, meaning-making, and evaluation

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7. Resources

In the Chatbot prompt, type 'start' to start using:

• 🔗 ChatGPT Live Demo: [ChatGPT]
• 🔗 Gemini Live Demo: [Gemini]
• 🧠 bot implementation for DeepSeek and other LLMs: [soon])

📄 Dimensionality Framework (8Df) Paper:

• Ch’ng E (2026) What’s beyond Presence? Dimensionality, Control and Information Spaces, Presence: Virtual and Augmented Reality 2026(37), MIT Press. Accepted for 2026, Issue 37. doi.org/10.1162/PRES.a.418

• 📊 LLM Comparison Study (ChatGPT / Gemini / DeepSeek):

• Now accepted as Ch'ng E (2026) Human-AI Co-Ideation in VR Experience Design: Using the Dimensionality Framework (8Df) to Structure LLM-Guided Design, Nature Humanities and Social Sciences Communications.
  ResearchSquare