土木工程教育中的人工智能和软技能:具有全球影响的拉丁美洲课程差距

Q1 Economics, Econometrics and Finance
Julio César Pino Tarragó, Dunia Lisbet Domínguez Gálvez, Julio Johnny Regalado Jalca, Erik Gabriel Villavicencio Cedeño
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引用次数: 0

摘要

本研究分析了厄瓜多尔国立大学Manabí (UNESUM)土木工程项目中人工智能(AI)和软技能发展的整合。通过定性文献分析,该研究检查了20个课程大纲和机构课程框架,以评估社会情感能力和新兴技术的存在。研究结果显示,软技能缺乏整合,主要局限于横向课程,完全缺乏与人工智能相关的教学内容——即使是在与技术相关的科目中。这些差距表明,在毕业生概况和实施课程之间存在结构性偏差。该研究主张对课程进行全面的重新设计,将技术指导与横向能力相结合,并利用人工智能作为教学资源。虽然基于单一的拉丁美洲机构,但结果突出了整个发展中地区工程教育面临的更广泛的系统性挑战,提供了与类似背景相关的见解。本文对工业4.0时代课程创新的全球讨论有所贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence and soft skills in civil engineering education: A Latin American curriculum gap with global implications
This study analyzes the integration of Artificial Intelligence (AI) and the development of soft skills within the Civil Engineering program at the Universidad Estatal del Sur de Manabí (UNESUM) in Ecuador. Using a qualitative documentary analysis, the research examined 20 course syllabi and institutional curricular frameworks to assess the presence of socio-emotional competencies and emerging technologies. The findings reveal a fragmented and insufficient incorporation of soft skills, mainly restricted to transversal courses, and a complete absence of AI-related pedagogical content—even in technology-relevant subjects. These gaps indicate a structural misalignment between the graduate profile and the implemented curriculum. The study argues for a comprehensive curricular redesign that combines technical instruction with transversal competencies and leverages AI as a pedagogical resource. While based on a single Latin American institution, the results highlight broader systemic challenges in engineering education across developing regions, offering insights relevant to similar contexts. This paper contributes to the global discussion on curriculum innovation in the era of Industry 4.0.
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来源期刊
Research in Globalization
Research in Globalization Economics, Econometrics and Finance-Economics, Econometrics and Finance (miscellaneous)
CiteScore
8.00
自引率
0.00%
发文量
31
审稿时长
79 days
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