The Creative Team Member: A Study of the Influence of AI Integration Timing on Brainstorming and Ideation
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Artificial Intelligence First (Early Integration), Artificial Intelligence Last (Late Integration).
- Who it may be relevant to
- Registry conditions: Creativity. Basic parameters: No limits · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Canada
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
The Effect of Artificial Intelligence Integration Timing on Group Brainstorming and Ideation in Undergraduate Students: A Randomized Controlled Trial
Overview
This study aims to examine how the timing of artificial intelligence (AI) integration during group brainstorming activities affects the creativity and ideation of participants. Undergraduate student participants will be randomly allocated into teams of four to complete a structured 12-minute brainstorming task. The study utilizes a three-group experimental design to compare three conditions: no AI access, AI access from the outset of the session, and AI access introduced halfway through the session. The standardized generative AI tool used is ChatGPT Pro. The creative output produced by each group will be evaluated by a panel of independent expert judges using the Consensual Assessment Technique (CAT).
Detailed description
Artificial intelligence (AI) tools are increasingly used in academic and professional environments, yet little is known about how the timing of AI's introduction during a collaborative brainstorming process shapes the creativity of the ideas produced. While recent literature suggests that human-AI collaboration can increase the likelihood of successful idea generation when AI is present throughout an entire session, the specific effect of integration timing remains a gap in the literature. This study aims to provide early data on whether AI functions more effectively as an early collaborator, a later resource, or whether its absence supports more creative thinking.
The study recruits undergraduate students enrolled in a summer research program, who are then randomly assigned to teams of four using a digital randomizer. Over the course of nine sessions, these teams participate in structured, 12-minute collaborative brainstorming tasks focused on designing strategies to address common university student challenges. To mitigate the influence of individual baseline characteristics on the group output, participants are re-randomized into new teams for each separate session.
To standardize the technological intervention and eliminate technical confounders, the study utilizes ChatGPT Pro (GPT-4o architecture) on pre-set devices. At the conclusion of the timed task, a designated team scribe submits the group's collaboratively generated idea list and their selected best idea via a secure, digital case report form.
Following data collection, all session outputs are immediately de-identified and assigned neutral identifiers. A panel of independent expert judges, blinded to the condition assignments, evaluate the output of each group.
Interventions
- Behavioral Artificial Intelligence First (Early Integration)
The introduction of ChatGPT Pro (GPT-4o architecture) at the beginning (minute 0) of a 12-minute group brainstorming session. A single prompt containing the scenario is submitted to generate an initial set of ideas, with no further back-and-forth dialogue permitted. This single artificial intelligence output serves as the baseline for the team's subsequent human ideation. - Behavioral Artificial Intelligence Last (Late Integration)
The introduction of ChatGPT Pro (GPT-4o architecture) at the midpoint (minute 6) of a 12-minute group brainstorming session. A single prompt containing both the scenario and the team's already-generated human ideas is submitted, with no further back-and-forth dialogue permitted. This single artificial intelligence output is used to guide the team's human ideation for the remaining 6 minutes.
Primary outcome measures
- Creativity Score of the Selected Best Idea [Time frame: Evaluated cross-sectionally upon the conclusion of each 12-minute session, across the 9 study sessions.]
Secondary outcome measures (3)
- Overall Creativity Score of Full Idea List [Time frame: Evaluated cross-sectionally upon the conclusion of each 12-minute session, across the 9 study sessions.]
- Number of Ideas Generated During the 12-Minute Session [Time frame: Evaluated cross-sectionally upon the conclusion of each 12-minute session, across the 9 study sessions.]
- Qualitative Resemblance of the Team's Output to Typical AI-Generated Responses [Time frame: Evaluated cross-sectionally upon the conclusion of each 12-minute session, across the 9 study sessions.]
Eligibility criteria
Inclusion criteria
- Enrolled as a student in the designated summer research program
- Able to provide voluntary informed consent
- Proficient in reading and communicating in English (required to engage with the scenarios and the artificial intelligence tool)
Exclusion criteria
-Not enrolled as an undergraduate student
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Single blind
- Primary purpose
- Other
Study locations
Canada · 1 center
- McMaster University — Hamilton
Publications
- Çelik, T. İ., & Akay, C. (2025). The Impact of Brainstorming Technique on Academic Achievement and Creative Thinking: A Meta-Analysis Study. Sage Open, 15(3). 62
- Muller, M., Houde, S., Gonzalez, G., Brimijoin, K., Ross, S. I., Silva Moran, D. A., & Weisz, J. D. (2024). Group brainstorming with an AI agent: Creating and selecting ideas. Proceedings of the 15th International Conference on Computational Creativity (ICCC 2024). https://computationalcreativity.net/iccc24/papers/ICCC24_paper_18.pdf
- Amabile, Teresa. (1982). Social psychology of creativity: A consensual assessment technique. Journal of Personality and Social Psychology. 43. 997-1013. 10.1037/0022-3514.43.5.997
- Koo TK, Li MY. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. J Chiropr Med. 2016 Jun;15(2):155-63. doi: 10.1016/j.jcm.2016.02.012. Epub 2016 Mar 31. PMID 27330520
- Zhang C, Shao Y, Yuan Y, Shen W. Artificial Intelligence Reshapes Creativity: A Multidimensional Evaluation. Psych J. 2025 Dec;14(6):831-840. doi: 10.1002/pchj.70042. Epub 2025 Aug 5. PMID 40764253
- Lee BC, Chung JJ. An empirical investigation of the impact of ChatGPT on creativity. Nat Hum Behav. 2024 Oct;8(10):1906-1914. doi: 10.1038/s41562-024-01953-1. Epub 2024 Aug 12. PMID 39134737
Identifiers
NCT: NCT07693803 · 20358