标题： 人工智能在计算机辅助工程中的更好用户体验：学术界是否跟上了产业需求？ 多视角文献综述 显示英文标题

标题： AI for Better UX in Computer-Aided Engineering: Is Academia Catching Up with Industry Demands? A Multivocal Literature Review

摘要： 计算机辅助工程（CAE）使仿真专家能够优化复杂模型，但在用户体验（UX）方面面临挑战，这限制了效率和可访问性。 虽然人工智能（AI）已显示出增强CAE流程的潜力，但以UX为重点将这些领域结合的研究仍显得支离破碎。 本文提出了一项多视角文献综述（MLR），探讨AI如何在学术研究和行业实施中提升CAE软件的用户体验。 我们的分析揭示了学术探索与行业应用之间的显著差距，公司正在积极实施大语言模型（LLMs）、自适应用户界面（UIs）和推荐系统，而学术研究主要集中在技术能力上，缺乏对用户体验的验证。 关键发现表明，在AI驱动的指导、自适应界面和工作流自动化方面存在尚未被当前研究充分探索的机会。 通过映射这些领域的交集，本研究为未来工作提供了基础，以解决所确定的研究差距，并推动AI的整合以改善CAE用户体验。 显示英文摘要

摘要： Computer-Aided Engineering (CAE) enables simulation experts to optimize complex models, but faces challenges in user experience (UX) that limit efficiency and accessibility. While artificial intelligence (AI) has demonstrated potential to enhance CAE processes, research integrating these fields with a focus on UX remains fragmented. This paper presents a multivocal literature review (MLR) examining how AI enhances UX in CAE software across both academic research and industry implementations. Our analysis reveals significant gaps between academic explorations and industry applications, with companies actively implementing LLMs, adaptive UIs, and recommender systems while academic research focuses primarily on technical capabilities without UX validation. Key findings demonstrate opportunities in AI-powered guidance, adaptive interfaces, and workflow automation that remain underexplored in current research. By mapping the intersection of these domains, this study provides a foundation for future work to address the identified research gaps and advance the integration of AI to improve CAE user experience.