STEM Faculty Perspectives on Generative AI in Higher Education

2026-03-04

AI Summary

The rapid integration of generative artificial intelligence (GenAI) into higher education has sparked divergent faculty perceptions and practical challenges concerning pedagogical integration, learning outcomes, and academic integrity. This study addresses these tensions through focus group interviews with 29 STEM instructors at U.S. public universities, employing qualitative thematic analysis to systematically uncover their ambivalent attitudes toward GenAI. Findings reveal that while faculty actively explore its potential in course design, assessment, and content generation, they remain cautious about its broader educational implications. The research innovatively argues that effective GenAI integration necessitates concurrent reforms in assessment frameworks, pedagogical approaches, and institutional governance. Furthermore, it identifies critical faculty needs regarding appropriate application contexts and core concerns, offering a nuanced foundation for policy and practice in GenAI-enhanced teaching environments.

Technology Category

• Philosophy and Ethics of AI: Artificial General Intelligence
• Application Domains: Humanities & Computational Social Science
• Humans and AI: Game Design — Procedural Content Generation & Storytelling

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

Generative artificial intelligence (GenAI) tools are increasingly present in higher education, yet their adoption has been largely student-driven, requiring instructors to respond to technologies already embedded in classroom practices. While some faculty have embraced GenAI for pedagogical purposes such as content generation, assessment support, and curriculum design, others approach these tools with caution, citing concerns about student learning, assessment validity, and academic integrity. Understanding faculty perspectives is therefore essential for informing effective pedagogical strategies and institutional policies. In this paper, we present findings from a focus group study with 29 STEM faculty members at a large public university in the United States. We examine how faculty integrate GenAI into their courses, the benefits and challenges they perceive for student learning, and the institutional support they identify as necessary for effective and responsible adoption. Our findings highlight key patterns in how STEM faculty engage with GenAI, reflecting both active adoption and cautious use. Faculty described a range of pedagogical applications alongside concerns about student learning, assessment, and academic integrity. Overall, the results suggest that effective integration of GenAI in higher education requires rethinking assessment, pedagogy, and institutional governance in addition to technical adoption.

Problem

• Generative AI
• STEM education
• faculty perspectives
• academic integrity
• higher education

Innovation

• generative AI
• STEM education
• faculty perspectives
• pedagogical integration
• academic integrity