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ORIGINAL RESEARCH article

Front. Educ.

Sec. Digital Learning Innovations

Nostalgia-Driven and AI-Empowered: A Tripartite Efficacy Evaluation Framework for Poetic Imagery Translation in Chinese Design Education

Provisionally accepted
  • Yanshan University, Qinhuangdao, China

The final, formatted version of the article will be published soon.

Within the global movement of cultural revival, the modern translation of poetic imagery (defined as the process of transmuting classical poetic symbols along with their emotional and cultural connotations into modern design elements) has emerged as a critical concern in Chinese design education, presenting a central tension between AI-driven efficiency and cultural depth. This study addresses three structural faults in current translation practices: fragmented symbolic extraction, weakened nostalgic drive, and over-reliance on AI tools. It establishes a tripartite efficacy evaluation framework encompassing emotion, cognition, and market dimensions, as well as a dual-cycle educational model featuring critical and iterative phases. A controlled experiment with 22 second-year product design majors (divided into an AI-assisted group and a traditional group) was conducted over a 4-week design psychology course, focusing on war, boudoir, and pastoral poetry themes. Results show that the AI-assisted group outperformed in emotional resonance (4.22±0.38 vs. 3.54±0.47) and market responsiveness (81.3%±8.2% vs. 64.1%±10.7%), while the traditional group maintained an advantage in cognitive completeness (83.7%±5.9% vs. 80.3%±5.1%). The dual-cycle model effectively reduced cultural misinterpretation rates in the AI group from 33% to 12%. Meanwhile, this study proposes the "Nostalgia-Congruent AI Guidelines (NCAI-G)", which regulates AI application from three aspects: symbolic fidelity, nostalgia coherence, and user safety. This study provides a reusable educational framework for balancing AI instrumental rationality and cultural value rationality, advancing traditional cultural design education toward quantitative evaluation-driven iteration.

Keywords: AI empowerment, design education reform, nostalgia-driven, poetic imagery translation, tripartite evaluation framework

Received: 08 Aug 2025; Accepted: 17 Dec 2025.

Copyright: © 2025 Hou. 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: Shijiang Hou

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