Navigating the AI Revolution in Engineering Management Education: Strategies for Detection, Integrity, and Pedagogical Enhancement

Abstract

Abstract The accessibility of Artificial Intelligence (AI) resources has led to a profound transformation of the educational landscape, redefining how students gather, organize, and absorb information. In engineering management education, students have traditionally engaged in assignments to deepen their knowledge and cultivate their professional expertise. However, the proliferation of advanced AI resources has brought about a significant shift in this paradigm, with students increasingly turning to AI platforms to expedite their assignments, often with minimal personal input and limited learning outcomes. This study investigates the utilization and detection of AI-generated content within the context of engineering management education, emphasizing the critical importance of upholding academic integrity. It explores the far-reaching impact of AI on the education sector, highlighting the emergence of AI detection tools that resemble plagiarism detection tools aimed at evaluating the authenticity of student-submitted work. This study examines the efficacy of several leading AI detection tools, offering insights into their accuracy and dependability. Engineering management, with its diverse subfields encompassing leadership, organizational management, strategic planning, financial resource management, project management, and legal considerations, faces opportunities and challenges in integrating AI-generated material into educational curricula. This study assesses the implications of AI integration within these subfields and its potential impact on students' skill development and comprehension.

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