AI use enhances creativity only when students think critically

A new study suggests the real impact of artificial intelligence (AI) in education may lie not just in access to tools, but in how confidently students use them. Research examining second language learners shows that students who feel more capable of using AI systems are significantly more likely to think creatively, particularly when supported by strong digital literacy and critical thinking habits.

The study, titled "The Influence of AI on Critical Thinking and Creativity in L2 Learning Contexts: A Social Cognitive Perspective," published in the Journal of Intelligence, links AI self-efficacy to creativity through multiple cognitive pathways.

Confidence in AI use emerges as a key driver of creative thinking

The study discusses the concept of AI self-efficacy, defined as a learner's confidence in their ability to use artificial intelligence tools effectively. The research finds that this confidence is not a peripheral factor but a central driver of creative performance in AI-supported learning environments.

Across both substudies, students with higher AI self-efficacy consistently demonstrated stronger creative output. In the first study, which used divergent thinking tasks to measure creativity, AI self-efficacy showed a significant positive relationship with both AI literacy and creative performance. In the second study, which measured creativity through everyday ideational behavior, similar patterns emerged, reinforcing the robustness of the findings across different methods.

Students who feel capable of interacting with AI systems are more likely to engage deeply with learning tasks. Rather than passively accepting AI-generated outputs, these learners experiment with prompts, refine responses, and explore multiple possibilities. This iterative engagement aligns closely with the cognitive processes underlying creativity, including flexibility, exploration, and idea generation.

The study situates these findings within social cognitive theory, which emphasizes the role of belief systems in shaping behavior. Confidence influences not only whether students use AI tools, but how they use them. High self-efficacy encourages persistence, experimentation, and reflective engagement, all of which are critical for creative thinking.

The research cautions against assuming a direct causal relationship. While AI self-efficacy predicts creativity, it does so in combination with other factors, particularly cognitive skills and evaluative habits that mediate this relationship.

AI literacy and critical thinking shape creative outcomes

The study identifies the mechanisms through which AI self-efficacy translates into creativity. The research finds that this relationship is mediated by two critical factors: AI literacy and critical thinking disposition.

AI literacy refers to a learner's ability to understand, use, evaluate, and reflect on AI technologies. Students with higher AI literacy are better equipped to treat AI systems as tools for inquiry rather than sources of final answers. They revise prompts, compare outputs, integrate external knowledge, and adapt AI-generated content to meet task requirements. These behaviors require cognitive flexibility and control, both of which are essential for creativity.

The study demonstrates that AI self-efficacy positively predicts AI literacy. Students who are confident in their ability to use AI are more likely to explore its functions and persist in learning how to use it effectively. This engagement leads to higher levels of competence, which in turn supports creative thinking.

Critical thinking disposition, defined as a tendency to engage in reflective evaluation and evidence-based reasoning, plays an equally important role. The research shows that students with higher AI self-efficacy are more likely to question AI outputs, assess their validity, and refine them based on logical reasoning. This evaluative process enhances the quality and originality of ideas, linking critical thinking directly to creative performance.

Importantly, the study finds that both AI literacy and critical thinking disposition operate as independent mediators. Each contributes separately to the relationship between AI self-efficacy and creativity, highlighting the multifaceted nature of cognitive engagement in AI-supported learning.

Statistical analysis confirms that AI self-efficacy is positively correlated with AI literacy, critical thinking disposition, and creativity, while both mediators are also significantly associated with creative outcomes. These relationships remain robust even after controlling for language proficiency and learning background, suggesting that the observed effects are not driven by external variables.

A sequential pathway reveals how AI skills build creative thinking

The study identifies a sequential pathway linking AI self-efficacy, AI literacy, critical thinking, and creativity. This chain mediation model provides a deeper understanding of how different cognitive components interact in AI-supported learning.

According to the findings, AI self-efficacy first enhances AI literacy by encouraging active engagement with technology. As learners develop a better understanding of AI tools, they become more capable of evaluating outputs critically. This leads to stronger critical thinking disposition, which ultimately supports creative idea generation and refinement.

The statistical model confirms that this sequential pathway is significant, indicating that the two mediators operate in a coordinated manner rather than in isolation. AI literacy provides the knowledge and skills needed to engage with AI, while critical thinking disposition ensures that this engagement is reflective and purposeful.

This layered process reflects a broader cognitive framework in which competence and disposition reinforce each other. Learners who understand AI are more likely to use it critically, and those who think critically are better able to generate creative outcomes. This pathway does not imply a rigid progression but rather a dynamic interaction among factors. Creativity emerges not from a single variable but from the combined influence of confidence, competence, and evaluative thinking.

Implications for AI Integration in education

The study challenges the assumption that access to AI tools alone is sufficient to enhance learning outcomes. Instead, it highlights the importance of developing students' confidence, skills, and critical thinking abilities alongside technological adoption.

For educators, this means designing learning environments that encourage active and reflective use of AI. Tasks that require students to evaluate AI outputs, compare alternatives, and justify their decisions can foster both AI literacy and critical thinking disposition. Collaborative projects, iterative writing exercises, and problem-solving activities can further enhance creative engagement.

The research also calls for balanced AI use. While AI can support creativity, overreliance on automated outputs may reduce cognitive effort and lead to homogenized thinking. Encouraging students to generate initial ideas independently before using AI, and to revise outputs critically, can help mitigate these risks.

At a policy level, the study points to the importance of integrating AI literacy into curricula. As AI becomes a standard tool in education and the workplace, the ability to use it effectively and critically will be essential for future workforce readiness. This includes not only technical skills but also ethical awareness and reflective judgment.