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May 2, 2026Discover Artificial Intelligence0 citationsOpen Access

Modeling the dynamic interplay between student creativity and Gen-AI

MIM. Javed IdrisiMUM. Shahbaz UllahNSNazish Ahmad Shamsi

Key Points

  • The study aims to explore the dynamic interaction between student creativity and generative AI usage in educational settings.
  • Developed a heuristic nonlinear dynamical framework to model creativity and AI usage as coupled variables.
  • Applied the framework to a classroom setting of 100 undergraduate students in a design-based learning course.
  • Assessed creativity through rubric-based evaluations and AI usage via surveys and interaction logs.
  • Identified four equilibrium states, including a balanced coexistence regime with simultaneous creativity and AI use under certain conditions.
  • Numerical simulations and phase-plane analysis supported the existence of a stable coexistence equilibrium.
  • The integration of generative AI tools can enhance creative engagement when moderated by intrinsic creativity.

Abstract

This study proposes a heuristic nonlinear dynamical framework to explore the evolving interaction between student creativity and the use of generative artificial intelligence tools such as ChatGPT. Creativity and AI usage are modeled as coupled, bounded variables whose interaction captures both constructive and suppressive influences, giving rise to multiple equilibrium regimes that represent distinct educational scenarios. The analysis identifies four equilibrium states, including a balanced coexistence regime in which creativity and AI usage persist simultaneously under appropriate conditions, and local stability analysis is used to characterize the qualitative behavior of the system near these equilibria. The model is intended as a conceptual and phenomenological tool rather than a mechanistic representation of cognitive processes, with the goal of providing qualitative insight into long-term interaction patterns and stability structures in AI-rich learning environments. To illustrate plausibility, the framework is applied to a small-scale classroom setting involving 100 undergraduate students enrolled in a design-based learning course, where creativity was assessed using rubric-based evaluations of student work and ChatGPT usage was measured through surveys and interaction logs. Illustrative parameter choices consistent with observed trends yield a stable coexistence equilibrium, supported by numerical simulations and phase-plane analysis. Overall, the study contributes a transparent mathematical lens for reasoning about creativity–AI interaction and highlights how balanced integration of generative AI tools can support creative engagement when reliance is moderated by intrinsic creative activity, while serving as a foundation for further theoretical refinement and empirical investigation rather than a predictive model of individual learning behavior.

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Cite This Study

Idrisi et al. (2026) studied this question.

synapsesocial.com/papers/69f593f271405d493affebf1https://doi.org/10.1007/s44163-026-01284-2
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