Designing an Interdisciplinary Artificial Intelligence Curriculum for Engineering: Evaluation and Insights from Experts

TL;DR

This paper explores the development and evaluation of an interdisciplinary AI curriculum for engineering students, highlighting stakeholder perspectives, curriculum alignment, and the impact of educator involvement on perceived quality.

Contribution

It introduces a novel interdisciplinary AI curriculum for engineering and provides insights into stakeholder perceptions and the influence of educator participation on curriculum quality.

Findings

Curriculum aligns with targeted AI competencies

Stakeholder perceptions vary between educators and industry

Educator involvement influences perceived curriculum quality

Abstract

As Artificial Intelligence (AI) increasingly impacts professional practice, there is a growing need to AI-related competencies into higher education curricula. However, research on the implementation of AI education within study programs remains limited and requires new forms of collaboration across disciplines. This study addresses this gap and explores perspectives on interdisciplinary curriculum development through the lens of different stakeholders. In particular, we examine the case of curriculum development for a novel undergraduate program in AI in engineering. The research uses a mixed methods approach, combining quantitative curriculum mapping with qualitative focus group interviews. In addition to assessing the alignment of the curriculum with the targeted competencies, the study also examines the perceived quality, consistency, practicality and effectiveness from both academic and industry perspectives, as well as differences in perceptions between educators who were involved in the development and those who were not. The findings provide a practical understanding of the outcomes of interdisciplinary AI curriculum development and contribute to a broader understanding of how educator participation in curriculum development influences perceptions of quality aspects. It also advances the field of AI education by providing a reference point and insights for further interdisciplinary curriculum developments in response to evolving industry needs.