Human Agency and Creativity in AI-Assisted Learning Environments

2025-12-07

AI Summary

This study investigates how generative AI fosters student creativity in learning, addressing the core question: *How does AI reshape learner agency to influence creative learning?* Drawing on a four-dimensional agency framework—instrumentality, effortfulness, dynamic emergence, and authorship—and integrating the Mini-c creativity model, we propose the “AI-agentic participation” theoretical framework. This framework elucidates how cognitive adaptation, relational negotiation, and ethical reflection jointly mediate personalized meaning-making. A key theoretical innovation lies in coupling authorial agency with Mini-c creativity, shifting creative learning from product-oriented outcomes toward meaning-generation processes. The resulting AI-augmented learning environment model offers a novel paradigm for conceptualizing human–AI co-creative processes and identifies critical avenues for future empirical research. (132 words)

Technology Category

• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Multiagent Systems: Agent/AI Theories and Architectures
• Philosophy and Ethics of AI: Artificial General Intelligence

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Agentic search

Abstract

This chapter explores human creativity in AI-assisted learning environments through the lens of student agency. We begin by examining four theoretical perspectives on agency, including instrumental, effortful, dynamically emergent, and authorial agency, and analyze how each frames the relationship between agency and creativity. Under each theoretical perspective, we discuss how the integration of generative AI (GenAI) tools reshapes these dynamics by altering students' roles in cognitive, social, and creative processes. In the second part, we introduce a theoretical framework for AI agentic engagement, contextualizing agency within specific cognitive, relational, and ethical dynamics introduced by GenAI tools. This framework is linked to the concept of Mini-c creativity, emphasizing personal relevance and self-directed learning. Together, these perspectives support a shift from viewing creativity as product-oriented to understanding it as a process of agentive participation and meaning-making. We conclude with two directions for future research focused on the creative process and performance in AI-assisted learning.

Problem

• Explores human creativity and agency in AI-assisted learning environments
• Analyzes how generative AI tools reshape student roles and creativity dynamics
• Proposes a framework linking AI agentic engagement to Mini-c creativity

Innovation

• Theoretical framework for AI agentic engagement
• Shifts creativity view to agentive participation process
• Links agency to Mini-c creativity and self-directed learning