Shall We Play a Game? Distributed Games with a Generative AI Player
Open accessAbstract
The prevalence of generative AI tools -especially large language models that enable human-like conversation -provides an opportunity to study how human learners interact with AI as collaborative ideators in the learning process.We expand the framework of distributed games (which initially focused on epistemic games of discovery as distributed processes) to investigate learner interaction with generative AI in design tasks.Through a comparative case study of two undergraduates using a generative AI tool in design tasks, we illustrate different ways in which learners orient themselves to the elements of the game (task, form, other players, etc.) and the corresponding complexity of the game played.We discuss implications for the design of learning environments that facilitate interaction with AI tools in distributed creative tasks.
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Several participants noted that they would set parameters or input prompts and then step back to see what the AI produced, engaging in what can be described as "playing" with the tool.
“Several participants noted that they would set parameters or input prompts and then step back to see what the AI produced, engaging in what can be described as “playing” with the tool (Chien et al. 2024; Lee et al. 2025; Matthews et al. 2024).”
From Generative AI in Game Design: Enhancing Creativity or Constraining Innovation? (2025) · cites this paper as Matthews et al. 2024
The Session overview and Barbara’s design-game section describe participants entering prompts, reviewing AI responses, and interacting with the tool as a game. But the Analysis Case selection says the paper examines two participants, John and Barbara, rather than several; it also describes active evaluation of outputs, not simply stepping back to see what the AI produced. Page numbers are unavailable in our copy. (LLM, conf=0.84)
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Generative AI in Game Design: Enhancing Creativity or Constraining Innovation?
Alharthi, S. A. (2025) · Journal of Intelligence · doi:10.3390/jintelligence13060060 · Cited by 27 · see citing works
“Researchers are beginning to address these concerns by exploring hybrid approaches that combine human intuition with model-driven creativity (Matthews et al. 2024; Ranella and Eger 2023).”
- Authors
- Matthews, J., Nguyen, H., & Swanson, H.
- Affiliations
- Utah State University (US)
- Venue
- Proceedings of the International Conference on Computer-supported for Collaborative Learning
- Published
- 2024-06-10
- Pages
- 139-146
- ISSN
- 1573-4552 (ISSN-L)
- 2543-0157
- OpenAlex
- W4399489080
- Cited by
- 3
- References
- 0
- Citations by year
- 2026: 1 · 2025: 2
- FWCI
- 4.61
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Computer-supported collaborative learning/The Computer-Supported Collaborative Learning Conference (publishedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Physical Sciences › Engineering › Mechanical Engineering › Design Education and Practice
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Keywords
- distributed games, generative AI, large language models, human-AI interaction, collaborative ideation, design tasks, game complexity, learning environment design, distributed creativity, epistemic games
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