AI-Empowered Teaching & Learning in General Education Psychology: A Longitudinal Empirical Study

Critical thinking and creativity are widely recognized as foundational skills in higher education and the modern workforce, yet their cultivation remains a persistent challenge. Academic writing, a cornerstone of higher education, offers a powerful avenue for developing these skills, but its effectiveness hinges on consistent, high-quality feedback—an often resource-intensive endeavour. Large language models (LLMs) present a transformative solution: generative AI can serve as automated writing evaluators, delivering scalable feedback to support student writing.

This study details the development of an AI assistant tailored to academic writing in general education psychology classrooms. Built on LLM technology, the assistant was trained on discipline-specific writing samples and feedback frameworks, with iterative refinements to enhance its ability to address critical thinking and creativity.

Over six independent writing assignments within a semester, the AI assistant provided targeted feedback to students, with results revealing significant improvements in overall writing quality, critical thinking, and creativity—effects that strengthened with each iteration of the tool. Notably, student ratings of AI-generated feedback consistently outperformed those of human feedback in terms of timeliness, specificity, and actionable guidance, leading to more frequent and substantial revisions.

A key advancement was the improved AI assistant’s capacity to directly target critical thinking and creativity through deliberate writing practices.

These findings demonstrate that AI-empowered feedback is not only a scalable alternative to human feedback but can actively foster higher-order cognitive skills.