ORIGINAL RESEARCH article
Front. Educ.
Sec. Assessment, Testing and Applied Measurement
Volume 10 - 2025 | doi: 10.3389/feduc.2025.1630073
Enhancing Graduate AI Education through Practical and Values-Driven Curriculum Integration
Provisionally accepted
- Gansu Agricultural University, Lanzhou, China
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With the rapid advancement of artificial intelligence (AI) technologies, the demand for highly skilled, application-oriented professionals in graduate education continues to grow. This study presents the development and implementation of a curriculum system that organically integrates practical skill cultivation with values-oriented guidance-specifically, fostering professional responsibility, ethical awareness, and societal concern-throughout the training process for AI master's students. Grounded in systematic industry needs analysis and curricular reform practice, the program achieves synergistic enhancement of both technical competence and holistic qualities through course design, case-based instruction, project-driven learning, and interdisciplinary collaboration. Feedback collected through multiple evaluation channels (including student and faculty surveys, focus group discussions, and performance metrics such as project outcomes and academic competition results) indicates that this approach effectively fosters greater student initiative, a stronger sense of social responsibility, and improved critical thinking.The key innovation lies in the subtle integration of ethical and societal considerations within the framework of technical training, offering a comprehensive pathway for AI talent development.While the case is based on a single institution, the model and experience provide useful insights for AI education reform and high-quality talent cultivation, and offer a theoretical foundation for future studies across diverse educational contexts.
Keywords: artificial intelligence, Graduate education, Practical Curriculum, Values Guidance, Educational effectiveness
Received: 26 May 2025; Accepted: 17 Jul 2025.
Copyright: © 2025 Zhong, Wei and Mo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Linjing Wei, Gansu Agricultural University, Lanzhou, China
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