Abstract:

This exploratory study analyses how undergraduate students perceive the unique contribution of university teachers to learning in a context where generative AI tools are widely available. The sample consists of ten students enrolled in a fourth-year Strategic Management course within the Industrial Organization Engineering degree at the Universitat Politècnica de València.

Students answered two open-ended questions:
(a) what their teacher contributes to the course that generative AI could not provide, and why; and
(b) whether this contribution is similar across all their courses.

A qualitative content analysis reveals several “non-substitutable” functions of the teacher. Students highlight the value of teachers’ professional and life experiences, expressed through real and personally lived examples that connect abstract theory with practical applications. They also emphasize critical judgment, particularly in interpreting concepts, correcting misunderstandings, and aligning explanations with how the assessment will be framed in practice. Social-emotional functions emerge strongly: teachers offer clear, interactive feedback, read the level of interest of the class, adjust activities, and provide empathy, closeness, and intuitive advice that AI is perceived as unable to match.

Regarding differences across subjects, students perceive generative AI as particularly helpful in technical and calculation-based courses (e.g., physics, mathematics, statistics), but still find it limited in explaining reasoning in depth and avoiding conceptual errors. In more applied or management-oriented subjects such as Strategic Management, the teacher’s experiential knowledge and guidance are viewed as especially critical. Overall, students tend to frame generative AI as a powerful support tool, while positioning the teacher as an indispensable source of contextualisation, critical evaluation, and human connection. The article discusses implications for the evolving role of university faculty in AI-rich learning environments.

Keywords:

Generative artificial intelligence, higher education, teacher role, student perceptions, experiential learning, engineering education, human–AI complementarity.