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).

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.

Inclusion Criteria:

Enrolled as an undergraduate 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).

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Exclusion Criteria:

Not enrolled as an undergraduate student in the designated summer research program.

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Individual participant data (IPD) will not be shared publicly due to an elevated risk of deductive re-identification. While numeric outcomes could be anonymized, the primary data consists of raw qualitative text (transcribed group brainstorming ideas and solutions) generated by a highly specific, geographically localized cohort of undergraduate students enrolled in the 2026 summer research program. Because the 2026 cohort size is small and the context is unique, sharing raw textual transcripts poses a risk of accidentally exposing the identities of the participants through specific phrasing, examples, or contextual clues, despite de-identification efforts. Therefore, to ensure participant confidentiality in accordance with institutional ethics guidelines, the raw data will remain confidential within the primary research team.