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This study investigates the perceptions and concerns of engineering educators at the National Technological University (Universidad Tecnológica Nacional, UTN)—Buenos Aires School (FRBA) regarding the integration of artificial intelligence (AI) tools in undergraduate courses. Employing a survey methodology, the research explores faculty attitudes across five dimensions, including their current use of AI tools, perceived benefits, barriers to adoption, and motivational factors influencing change. The study aims to identify strategies for leveraging AI to enhance teaching and learning while addressing institutional and pedagogical challenges. Preliminary results indicate a mixed perception of AI's potential in education. Faculty members recognize its ability to support innovative teaching methods but express concerns over their lack of familiarity with AI tools, resistance to change, and potential misuse by students. These findings highlight the need for targeted professional development and the establishment of policies and frameworks to support effective AI integration. The research provides actionable insights for designing institutional initiatives that foster faculty adoption of generative AI tools, ultimately improving educational practices and promoting inclusivity in engineering education.

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Artificial Intelligence in Argentine Engineering Education: Perceptions and Concerns Among Faculties

  • 会议论文

  • 发表日期：

    2026年

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  • Uriel R. Cukierman,
  • Juan M. Palmieri,
  • Diego Grasselli de Lima,
  • Andrea Fleischman

摘要

This study investigates the perceptions and concerns of engineering educators at the National Technological University (Universidad Tecnológica Nacional, UTN)—Buenos Aires School (FRBA) regarding the integration of artificial intelligence (AI) tools in undergraduate courses. Employing a survey methodology, the research explores faculty attitudes across five dimensions, including their current use of AI tools, perceived benefits, barriers to adoption, and motivational factors influencing change. The study aims to identify strategies for leveraging AI to enhance teaching and learning while addressing institutional and pedagogical challenges. Preliminary results indicate a mixed perception of AI's potential in education. Faculty members recognize its ability to support innovative teaching methods but express concerns over their lack of familiarity with AI tools, resistance to change, and potential misuse by students. These findings highlight the need for targeted professional development and the establishment of policies and frameworks to support effective AI integration. The research provides actionable insights for designing institutional initiatives that foster faculty adoption of generative AI tools, ultimately improving educational practices and promoting inclusivity in engineering education.