STEM Faculty Perspectives on Generative AI in Higher Education
- URL: http://arxiv.org/abs/2603.04001v1
- Date: Wed, 04 Mar 2026 12:46:26 GMT
- Title: STEM Faculty Perspectives on Generative AI in Higher Education
- Abstract summary: Generative artificial intelligence (GenAI) tools are increasingly present in higher education.<n>While some faculty have embraced GenAI for pedagogical purposes, others approach these tools with caution.<n>We present findings from a focus group study with 29 STEM faculty members at a large public university in the United States.
- Score: 2.63946599983876
- License: http://creativecommons.org/licenses/by/4.0/
- 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.
Related papers
- Beyond Detection: Redesigning Assessment and Governande of Generative AI at the Universidad Politécnica de Madrid (UPM) [39.92037610044293]
Most institutions frame the debate around AI detection, plagiarism, academic integrity and a presumed drop in student effort as defensive.<n>Other group of pioneering universities is pursuing deeper adoption, and assuming that any policy built on prevention or sanction will not hold.<n>What universities need instead is a coordinated effort to set clear, course-by-course rules for GenAI use.<n>UPM is developing a strategic and sustainable AI policy and adoption framework structured around six dimensions.
arXiv Detail & Related papers (2026-06-04T18:04:50Z) - Exploring Student Perception on Gen AI Adoption in Higher Education: A Descriptive Study [1.978884131103313]
This study examines how students perceive, use, and evaluate Generative Artificial Intelligence (GenAI)<n>Data were collected through a questionnaire administered to 436 postgraduate Computer Science students at the University of Hertfordshire.
arXiv Detail & Related papers (2026-03-29T17:19:39Z) - Integrating Generative AI-enhanced Cognitive Systems in Higher Education: From Stakeholder Perceptions to a Conceptual Framework considering the EU AI Act [0.7945222903786706]
GenAI is expected to enhance cognitive systems by enabling personalized learning and streamlining educational services.<n> stakeholders perceptions of GenAI in higher education remain divided, shaped by cultural, disciplinary, and institutional contexts.<n>This study investigates how GenAI is perceived within the disciplines of Information Technology and Electrical Engineering.
arXiv Detail & Related papers (2026-02-11T12:44:03Z) - Understanding Student Attitudes and Acceptability of GenAI Tools in Higher Ed: Scale Development and Evaluation [22.35484281040714]
This study introduces a validated survey instrument designed to assess students' perceptions of generative AI (GenAI)<n>The instrument includes six thematic domains: institutional understanding, fairness and trust, academic and career influence, societal concerns, and GenAI use in writing and coursework.<n>Students from multilingual households perceived greater clarity in institutional policy, while first-generation students reported a stronger belief in GenAI's impact on future careers.
arXiv Detail & Related papers (2025-08-03T21:22:34Z) - Generative AI in Education: Student Skills and Lecturer Roles [0.0]
This study aims to identify and evaluate the key competencies students need to effectively engage with GenAI in education.<n>The literature review identified 14 essential student skills for GenAI engagement, with AI literacy, critical thinking, and ethical AI practices emerging as the most critical.<n>In our study of lecturer strategies, we identified six key areas, with GenAI Integration and Curriculum Design being the most emphasised.
arXiv Detail & Related papers (2025-04-28T10:58:30Z) - Early Adoption of Generative Artificial Intelligence in Computing Education: Emergent Student Use Cases and Perspectives in 2023 [38.83649319653387]
There is limited prior research on computing students' use and perceptions of GenAI.
We surveyed all computer science majors in a small engineering-focused R1 university.
We discuss the impact of our findings on the emerging conversation around GenAI and education.
arXiv Detail & Related papers (2024-11-17T20:17:47Z) - Framework for Adoption of Generative Artificial Intelligence (GenAI) in Education [0.032771631221674334]
This study focuses on examining the university education system and assessing the opportunities and challenges related to incorporating GenAI in teaching and learning.
It identifies a gap and the absence of a comprehensive framework that obstructs the effective integration of GenAI within the academic environment.
arXiv Detail & Related papers (2024-07-21T12:02:28Z) - Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach [25.903775277417267]
Recent advances in generative AI (gen AI) have created excitement about the potential of new technologies to offer a personal tutor for every learner and a teaching assistant for every teacher.
We argue that this is primarily due to the difficulties with verbalising pedagogical intuitions into gen AI prompts and the lack of good evaluation practices.
Here we present our work collaborating with learners and educators to translate high level principles from learning science into a pragmatic set of seven diverse educational benchmarks.
arXiv Detail & Related papers (2024-05-21T19:27:59Z) - Scaffolding Language Learning via Multi-modal Tutoring Systems with Pedagogical Instructions [34.760230622675365]
Intelligent tutoring systems (ITSs) imitate human tutors and aim to provide customized instructions or feedback to learners.
With the emergence of generative artificial intelligence, large language models (LLMs) entitle the systems to complex and coherent conversational interactions.
We investigate how pedagogical instructions facilitate the scaffolding in ITSs, by conducting a case study on guiding children to describe images for language learning.
arXiv Detail & Related papers (2024-04-04T13:22:28Z) - Generative AI in Higher Education: Seeing ChatGPT Through Universities' Policies, Resources, and Guidelines [11.470910427306569]
This study analyzes academic policies and guidelines established by top-ranked U.S. universities regarding the use of GenAI.
Results show that the majority of these universities adopt an open but cautious approach towards GenAI.
Findings provide four practical implications for educators in teaching practices.
arXiv Detail & Related papers (2023-12-08T18:33:11Z) - Maestro: A Gamified Platform for Teaching AI Robustness [32.755807742417495]
Maestro is an open-source game-based platform that contributes to the advancement of robust AI education.
We assessed Maestro's influence on students' engagement, motivation, and learning success in robust AI.
arXiv Detail & Related papers (2023-06-14T04:35:56Z) - Students' Voices on Generative AI: Perceptions, Benefits, and Challenges
in Higher Education [2.0711789781518752]
This study explores university students' perceptions of generative AI (GenAI) technologies, such as ChatGPT, in higher education.
Students recognized the potential for personalized learning support, writing and brainstorming assistance, and research and analysis capabilities.
Concerns about accuracy, privacy, ethical issues, and the impact on personal development, career prospects, and societal values were also expressed.
arXiv Detail & Related papers (2023-04-29T15:53:38Z) - AGI: Artificial General Intelligence for Education [41.45039606933712]
This position paper reviews artificial general intelligence (AGI)'s key concepts, capabilities, scope, and potential within future education.
It highlights that AGI can significantly improve intelligent tutoring systems, educational assessment, and evaluation procedures.
The paper emphasizes that AGI's capabilities extend to understanding human emotions and social interactions.
arXiv Detail & Related papers (2023-04-24T22:31:59Z) - Reinforcement Learning Tutor Better Supported Lower Performers in a Math
Task [32.6507926764587]
Reinforcement learning could be a key tool to reduce the development cost and improve the effectiveness of intelligent tutoring software.
We show that deep reinforcement learning can be used to provide adaptive pedagogical support to students learning about the concept of volume.
arXiv Detail & Related papers (2023-04-11T02:11:24Z) - Creation and Evaluation of a Pre-tertiary Artificial Intelligence (AI)
Curriculum [58.86139968005518]
The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created an AI curriculum for pre-tertiary education.
A team of 14 professors with expertise in engineering and education collaborated with 17 principals and teachers from 6 secondary schools to co-create the curriculum.
The co-creation process generated a variety of resources which enhanced the teachers knowledge in AI, as well as fostered teachers autonomy in bringing the subject matter into their classrooms.
arXiv Detail & Related papers (2021-01-19T11:26:19Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.