The Evolution of AI’s Role

AI is evolving from a passive tool to an active facilitator in learning and innovation. This study focuses on the high-pressure “60-minute Mini Design Sprint” to explore how AI can effectively support creative tasks and advance future AI educational practices.

The Knowledge Gap

We lack a deep understanding of how AI functions as a true collaborator in creative learning environments.

• Gap 1: How do different levels of AI guidance affect a learner’s cognitive load and perceived success?
• Gap 2: How does a learner’s perception of the AI’s role (mentor, teammate, tool) shape their interaction patterns and trust?

Context Dependency

Core Hypothesis: The effectiveness of an AI agent is context-dependent, varying with guidance level and user perception.

The high-guidance group is expected to have lower cognitive load, while the low-guidance group may feel more autonomy but greater stress. Trust is a key mediating variable.

Multi-Method Inquiry

Three-Stage Analysis

• Data Collection: Interaction text logs, scale data, and qualitative interview data.
• Analysis Process:
  1. Semantic Coding
  2. Thematic Coding
  3. Retroductive Inference
• Challenges & Mitigation: Mitigating researcher’s “pro-innovation bias” through reflexive practices.

Beyond “Does It Work?”

This research aims to move beyond simply evaluating if an AI tool “works” to deeply investigate the underlying mechanisms of “how it works.” The expected contribution is to provide context-sensitive insights to design future AI learning environments as true facilitators of human creativity and innovation.

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