ChatGPT and Me: Collaborative Creativity in a Group Brainstorming with Generative AI

Han Kyul Kim; Aleyeh Roknaldin; Shriniwas Prakash Nayak; Xiaoci Zhang; Muyao Yang; Marlon Twyman; Angel Hsing-Chi Hwang; Stephen Lu

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Conference: 2024 ASEE Annual Conference & Exposition
Location: Portland, Oregon
Publication Date: June 23, 2024
Start Date: June 23, 2024
End Date: July 12, 2024
Conference Session: Teaching with ML and Generative AI
Tagged Division: Computers in Education Division (COED)
Permanent URL: https://peer.asee.org/48457

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Paper Authors

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Han Kyul Kim University of Southern California

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Han Kyul Kim is a Ph.D. student in the Department of Industrial and Systems Engineering at the University of Southern California. He earned his M.S. in Industrial Engineering from Seoul National University and holds B.S. degrees in Industrial & Systems Engineering and Business and Technology Management from KAIST. Previously, he worked as a data scientist and software engineer at Deloitte Consulting, Samsung Electronics, and Seoul National University Hospital. His research interests include machine learning, natural language processing, and learning analytics.

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Aleyeh Roknaldin University of Southern California

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Aleyeh Roknaldin is earning her Ph.D. in industrial and systems engineering from the Daniel J. Epstein Department of Industrial and Systems Engineering at the University of Southern California (USC). Aleyeh earned an M.S. in Engineering Management in 2022 from USC and her B.S. in Chemical Engineering from the University of California, Davis in 2020. Her research interests include learning analytics to investigate how students learn from one another in computer-supported collaborative learning environments and how students interact with generative artificial intelligence in learning contexts.

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Shriniwas Prakash Nayak University of Southern California

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Xiaoci Zhang University of Southern California

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Xiaoci Zhang received his Bachelor’s in Industrial
Engineering and a minor in Mathematics from the
Pennsylvania State University in 2021. Currently, he
is pursuing his Master’s in Industrial and System
Engineering at the University of Southern California.
His research interests include machine learning, data
analysis, and mathematical optimizations.

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Human-AI Interaction Research

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Stephen Lu University of Southern California

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Stephen Lu is the David Packard Chair in Manufacturing Engineering at University of Southern California. His current professional interests include design thinking, collaborative engineering, technological innovation, and education reform. He has over 330

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Abstract

The growing popularity of generative AI (genAI), particularly ChatGPT, has sparked enthusiasm and caution among education practitioners and researchers. To harness the full potential of generative AI in educational contexts, it is crucial to thoroughly analyze its impact and suitability for different educational purposes. This work serves as an initial step towards our long-term research goal of integrating generative AI as a "brainstorming partner" in the context of computer-supported collaborative learning (CSCL). Rather than immediately outlining requirements and developing components for ChatGPT to function as an independent brainstorming partner, the primary objective of this paper is to examine ChatGPT's impact in a collaborative creative ideation process.

As an example of CSCL, this paper delves into students' creative group brainstorming activities. In this educational context, the learning objective lies in encouraging students to creatively apply their factual knowledge without rigid concerns about correctness. Diverging from recent concerns about hallucination and academic integrity involving genAI in education, our paper introduces a unique application of genAI where these concerns hold relatively less significance. Furthermore, we quantitatively analyze the influence of ChatGPT on the creativity of ideas emerging from group brainstorming sessions. Specifically, we describe how students incorporate ChatGPT into their ideation process and observe its impact on the perceived creativity levels of the generated ideas. Additionally, we explore whether leveraging ChatGPT leads to more homogeneous ideas among students, potentially challenging the collaborative and diversity-centric learning objective of group brainstorming.

Our investigation involves a statistical analysis and natural language processing techniques to digital logs, discussion messages and product design ideas generated by 33 students over a two-week period in a graduate-level product engineering class. The students were randomly organized into teams comprising of 4 to 5 individuals to engage in group discussions in an online platform. Their task was to brainstorm and discuss new product ideas that aligned with specific user requirements. In select groups, ChatGPT was introduced as an additional member, providing students with the capability to direct questions during their ideation process.

Our findings illustrate that students predominantly utilize ChatGPT during their initial ideation stage, injecting their own modifications and enhancements to its responses. Surprisingly, ideas generated with ChatGPT are perceived as more creative by the students, potentially attributed to their relatively detailed descriptions. Furthermore, our observations indicate that the use of ChatGPT does not necessarily lead to homogenous ideas, as students' prompts to ChatGPT and its responses exhibit linguistic diversity.

This paper not only offers a unique application of genAI in the educational landscape but also provides valuable insights into the nuanced dynamics of integrating ChatGPT as a collaborative partner during creative ideation. Our results pave the way for further exploration, showcasing the potential of genAI to enhance collaborative learning experiences while fostering creativity among students.

Citation
Format

Kim, H. K., & Roknaldin, A., & Nayak, S. P., & Zhang, X., & Yang, M., & Twyman, M., & Hwang, A. H., & Lu, S. (2024, June), ChatGPT and Me: Collaborative Creativity in a Group Brainstorming with Generative AI Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/48457

TY - CPAPER
AB - The growing popularity of generative AI (genAI), particularly ChatGPT, has sparked enthusiasm and caution among education practitioners and researchers. To harness the full potential of generative AI in educational contexts, it is crucial to thoroughly analyze its impact and suitability for different educational purposes. This work serves as an initial step towards our long-term research goal of integrating generative AI as a &quot;brainstorming partner&quot; in the context of computer-supported collaborative learning (CSCL). Rather than immediately outlining requirements and developing components for ChatGPT to function as an independent brainstorming partner, the primary objective of this paper is to examine ChatGPT&#39;s impact in a collaborative creative ideation process.

As an example of CSCL, this paper delves into students&#39; creative group brainstorming activities. In this educational context, the learning objective lies in encouraging students to creatively apply their factual knowledge without rigid concerns about correctness. Diverging from recent concerns about hallucination and academic integrity involving genAI in education, our paper introduces a unique application of genAI where these concerns hold relatively less significance. Furthermore, we quantitatively analyze the influence of ChatGPT on the creativity of ideas emerging from group brainstorming sessions. Specifically, we describe how students incorporate ChatGPT into their ideation process and observe its impact on the perceived creativity levels of the generated ideas. Additionally, we explore whether leveraging ChatGPT leads to more homogeneous ideas among students, potentially challenging the collaborative and diversity-centric learning objective of group brainstorming.

Our investigation involves a statistical analysis and natural language processing techniques to digital logs, discussion messages and product design ideas generated by 33 students over a two-week period in a graduate-level product engineering class. The students were randomly organized into teams comprising of 4 to 5 individuals to engage in group discussions in an online platform. Their task was to brainstorm and discuss new product ideas that aligned with specific user requirements. In select groups, ChatGPT was introduced as an additional member, providing students with the capability to direct questions during their ideation process.

Our findings illustrate that students predominantly utilize ChatGPT during their initial ideation stage, injecting their own modifications and enhancements to its responses. Surprisingly, ideas generated with ChatGPT are perceived as more creative by the students, potentially attributed to their relatively detailed descriptions. Furthermore, our observations indicate that the use of ChatGPT does not necessarily lead to homogenous ideas, as students&#39; prompts to ChatGPT and its responses exhibit linguistic diversity.

This paper not only offers a unique application of genAI in the educational landscape but also provides valuable insights into the nuanced dynamics of integrating ChatGPT as a collaborative partner during creative ideation. Our results pave the way for further exploration, showcasing the potential of genAI to enhance collaborative learning experiences while fostering creativity among students.

AU - Han Kyul Kim
AU - Aleyeh Roknaldin
AU - Shriniwas Prakash Nayak
AU - Xiaoci Zhang
AU - Muyao Yang
AU - Marlon Twyman
AU - Angel Hsing-Chi Hwang
AU - Stephen Lu
CY - Portland, Oregon
DA - 2024/06/23
PB - ASEE Conferences
TI - ChatGPT and Me: Collaborative Creativity in a Group Brainstorming with Generative AI
UR - https://peer.asee.org/48457
ER -