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<p>AI integration in professional coursework has gained attention in higher education, offering potential improvements in learning and performance. However; the usage rate, accuracy, and patterns of AI tools across disciplines remain unclear. The impact of AI on students’ learning and long-term outcomes still needs further investigation. This study investigates the role of AI-driven learning tools in enhancing professional coursework across various academic disciplines, including Engineering, Natural Sciences, Humanities, Social Sciences, and Arts. Using a multi-stage empirical approach, we evaluate student performance and engagement with AI tools, exploring both the positive outcomes and limitations in each discipline. Our findings show that 1,472 students across different regions and academic fields frequently use AI-driven learning tools in their professional coursework, with generally positive feedback. The accuracy of AI-generated responses to 1,200 questions is commendable, but the tools still demonstrate limitations in areas such as flexibility, contextual adaptation, analytical reasoning, and conceptual synthesis in certain disciplines. We segment 800 representative students based on AI engagement patterns, revealing distinct usage behaviors and preferences across four groups, offering further insights into how AI tools are utilized. Furthermore, the results from assessing the impact of AI-driven learning on the academic performance of 400 students show that AI significantly enhances performance in technical fields like Engineering and Natural Sciences. However, instructors in these fields express concerns about students’ over-reliance on AI, which may hinder independent thinking and creative problem-solving. Despite these concerns, our long-term academic outcome predictions indicate that AI-driven learning tools continue to provide substantial benefits to students.</p>

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Boon or Bane? Evaluating AI-driven learning assistance in higher education professional coursework

  • 期刊论文

  • 发表日期：

    2025年6月12日

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  • Yicheng Sun,
  • Hanbo Yang,
  • Hi Kuen Yu,
  • Richard Suen

摘要

AI integration in professional coursework has gained attention in higher education, offering potential improvements in learning and performance. However; the usage rate, accuracy, and patterns of AI tools across disciplines remain unclear. The impact of AI on students’ learning and long-term outcomes still needs further investigation. This study investigates the role of AI-driven learning tools in enhancing professional coursework across various academic disciplines, including Engineering, Natural Sciences, Humanities, Social Sciences, and Arts. Using a multi-stage empirical approach, we evaluate student performance and engagement with AI tools, exploring both the positive outcomes and limitations in each discipline. Our findings show that 1,472 students across different regions and academic fields frequently use AI-driven learning tools in their professional coursework, with generally positive feedback. The accuracy of AI-generated responses to 1,200 questions is commendable, but the tools still demonstrate limitations in areas such as flexibility, contextual adaptation, analytical reasoning, and conceptual synthesis in certain disciplines. We segment 800 representative students based on AI engagement patterns, revealing distinct usage behaviors and preferences across four groups, offering further insights into how AI tools are utilized. Furthermore, the results from assessing the impact of AI-driven learning on the academic performance of 400 students show that AI significantly enhances performance in technical fields like Engineering and Natural Sciences. However, instructors in these fields express concerns about students’ over-reliance on AI, which may hinder independent thinking and creative problem-solving. Despite these concerns, our long-term academic outcome predictions indicate that AI-driven learning tools continue to provide substantial benefits to students.