<p>The release of ChatGPT in late 2022 marked the beginning of a rapid transformation in higher education, soon followed by the development of multimodal generative AI programs. As this technology becomes increasingly integrated into teaching and learning, it is crucial to evaluate its current use and impact. This systematic literature review captures the initial academic response to generative AI, providing insights into how higher education has adopted this transformative technology in its first two years. The findings indicate that while some themes from the pre-ChatGPT era persist, new and emerging trends—particularly in fostering creativity, critical thinking, learning autonomy, and prompt literacy—are now taking shape. This shift underscores a growing emphasis on the pedagogical integration of generative AI. However, the review also highlights a key tension: while generative AI enhances efficiency, it raises concerns about overreliance, potentially leading to the outsourcing of critical cognitive and metacognitive skills. To address these challenges and fully harness the potential of generative AI, future research should focus on exploring multimodal generative AI tools and fostering student–teacher-AI collaboration.</p>

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Pedagogical Applications of Generative AI in Higher Education: A Systematic Review of the Field

  • Yufeng Qian

摘要

The release of ChatGPT in late 2022 marked the beginning of a rapid transformation in higher education, soon followed by the development of multimodal generative AI programs. As this technology becomes increasingly integrated into teaching and learning, it is crucial to evaluate its current use and impact. This systematic literature review captures the initial academic response to generative AI, providing insights into how higher education has adopted this transformative technology in its first two years. The findings indicate that while some themes from the pre-ChatGPT era persist, new and emerging trends—particularly in fostering creativity, critical thinking, learning autonomy, and prompt literacy—are now taking shape. This shift underscores a growing emphasis on the pedagogical integration of generative AI. However, the review also highlights a key tension: while generative AI enhances efficiency, it raises concerns about overreliance, potentially leading to the outsourcing of critical cognitive and metacognitive skills. To address these challenges and fully harness the potential of generative AI, future research should focus on exploring multimodal generative AI tools and fostering student–teacher-AI collaboration.