Preparing Students for an AI-Driven World: Generative AI and Curriculum Reform in Higher Education
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Preparing Students for an AI-Driven World: Generative AI and Curriculum Reform in Higher Education

14/11/2025 Frontiers Journals

This research article addresses the imperative of curriculum reform in higher education to prepare students for an AI-driven world amid the rapid advancement of Generative AI (GenAI). It proposes a comprehensive framework centered on three core strategies: fostering interdisciplinary AI literacy via tiered courses (foundational concepts, applied uses, advanced techniques) covering technical fundamentals, ethical implications, and practical tool use; shifting pedagogy from rote memorization to problem-solving through active learning (e.g., problem-based learning, project-based learning) and interdisciplinary collaboration; and establishing dynamic curriculum update mechanisms (industry partnerships, modular design, self-directed learning cultivation).

Additionally, the study examines critical implementation considerations, including faculty training, resource allocation, ethical issues (bias, privacy, academic integrity), assessment redesign (prioritizing higher-order thinking), and strategies to preserve academic honesty. It concludes with future research directions and emphasizes institutions’ urgent need to adopt proactive, ethical, and adaptive measures to harness GenAI’s potential for equitable, effective education.

The work titled “Preparing Students for an AI-Driven World: Generative AI and Curriculum Reform in Higher Education”, was published on Frontiers of Digital Education (published on September 15, 2025).
DOI: 10.1007/s44366-025-0067-6

https://journal.hep.com.cn/fde/EN/10.1007/s44366-025-0067-6
Attached files
  • Figure 1 Intersections among GenAI, higher education, and curriculum reform. Intersections represent areas where these domains collaborate to address challenges and opportunities in modern education.
14/11/2025 Frontiers Journals
Regions: Asia, China
Keywords: Applied science, Computing

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