Sense-Making Curves

Visualizing the Dynamics of Creativity and Interaction

Creative processes unfold through time.

People explore ideas, coordinate with collaborators, encounter surprises, revise their understanding, and generate new possibilities. These dynamic processes are often difficult to observe directly. Traditional creativity research frequently focuses on final outcomes while overlooking the evolving interactions that give rise to them.

Sense-Making Curves provide a way to visualize these interaction dynamics.

Developed within the Creative Sense-Making framework, Sense-Making Curves transform sequences of interactions into trajectories that reveal how creative processes evolve through time. Rather than treating creativity as a static event, the curves make visible the ongoing movement between exploration, coordination, novelty generation, stabilization, and shared understanding.

The curves do not measure creativity itself. Instead, they visualize patterns of interaction that are associated with creative activity.

By representing interaction as a dynamic trajectory, Sense-Making Curves help researchers, designers, educators, and practitioners understand how participants navigate uncertainty, discover new possibilities, and construct meaning together.

Why Sense-Making Curves Matter

Creativity Unfolds Through Time

Creative processes consist of evolving interactions rather than isolated moments of insight.

Interaction Becomes Visible

The curves provide a way to observe patterns that would otherwise remain hidden within large interaction datasets.

Co-Creation Can Be Measured

Human-human and human-AI collaboration can be analyzed through interaction trajectories.

Exploration and Coordination Become Observable

The curves reveal how participants move between divergent exploration and convergent coordination.

Explore Sense-Making Curves

What is a Sense-Making Curve?

Learn the theoretical foundations of the framework and how interaction dynamics become visual trajectories.

Reading a Curve

Understand how to interpret peaks, valleys, transitions, oscillations, and long-term trends.

High vs Low Sense-Making

Explore the distinction between exploratory and coordinative interaction dynamics.

Examples

View Sense-Making Curves generated from drawing studies, collaborative creativity experiments, and human-AI co-creation systems.

From Interaction to Insight

Sense-Making Curves represent one of the central contributions of the Creative Sense-Making framework. They provide a bridge between theory and measurement, allowing interaction dynamics to be visualized, analyzed, and compared across diverse creative contexts.

By transforming interaction into trajectories, the framework offers a new way to understand how creativity emerges through participation.

The creative sense-making curve generating tool is available on Google Drive at this link, To use the tool follow the instructions below: 

1. Open the setup.html file

2. Copy and past the code from a YouTube video into the text box provided. For example, if the youtube link is: https://www.youtube.com/watch?v=iFUs7E8liZU, the part you want to past is after the ?v, so in this case, it would be iFUs7E8liZU.

3. Press the submit button

4. Play the video 

5. Ensure that the appropriate behavioral markers have been assigned to the coding values of the tool. The values of the tool are -1 to 1. In this scheme, clamped cognition would be 0, and unclamped cognition would either be above or below that value.

6. To activate the coding selection mechanism click on the square along the vertical spectrum on the right side of the screen. 

7. To move the coding selector, use the arrow keys up and down. 

8. To slow down the video, click the gear icon in the YouTube video player and select a playback speed. 

9. To turn on captions, click closed captions (if available). 

10. To download the data, click the download data file. 

11. Generate a separate sense-making curve for each participant in the interaction. 

To analyze the curve, see technique in Davis et al. 2017, which is essentially using the CumSum function in excel to generate a running cumulative sum of each individual sense-making curve. Then, apply stochastic analysis to the curve to classify different interaction patterns that may be present. 

© Nicholas Davis 2022