Topic Editors

Dr. Xin Zhao
Institute of Education, University of Manchester, Manchester M13 9PL, UK
Prof. Dr. Minna Rollins
Richards College of Business, University of West Georgia, Carrollton, GA 30118, USA
Department of Industrial Engineering, University of Salerno, 84084 Fisciano, Italy

Generative Artificial Intelligence in Higher Education

Abstract submission deadline
30 September 2025
Manuscript submission deadline
31 December 2025
Viewed by
2117

Topic Information

Dear Colleagues,

Our Topic explores how generative AI (GenAI) affects higher education at various levels and how it shapes teaching, learning, and leadership in higher education worldwide. With the advent of GenAI, the higher education sector must constantly evolve to keep up with the latest technological advances. In particular, the rapid deployment of new tools based on GenAI has renewed the challenge of adopting new tools. Investigating and understanding the implications of GenAI in higher education is critical, in addition to exploring how to adapt the educational environment to ensure that the next generation of students can benefit from GenAI while efforts are made to limit its negative consequences.

Our Topic includes but is not limited to discussing the experiences and consequences of using Gen AI in curriculum and course implementation and its impact on institutions, instructors, and students. Another important aspect concerns formulating new discussions to create a pathway for standard regulation of disruptive technologies such as GenAI.

The institutional level:

  • Empirical studies on Gen AI policy and practice within and across institutions
  • Innovations in Gen AI from higher education
  • AI literacy and digital skills

The program/curriculum level:

  • Gen AI’s effect on assessment and accreditation
  • Implementing Gen AI into a college curriculum across disciplines

The course level focus:

  • Using Gen AI in classrooms, assignments, and assessments.
  • Different disciplines and Gen AI
  • Learning process and outcomes and Gen AI

The instructor-level focus:

  • Integrating GenAI in the classroom activities and assignments
  • Tech skills and GenAI
  • Pedagogy and GenAI

The Student-level focus:

  • Use of GenAI and ethics
  • Case studies on student behavior with GenAI
  • The expectations of GenAI use in a college classroom

Multiple stakeholders’ perspectives:

  • Ethical use of GenAI in higher education
  • Inclusivity and equality in the context of GenAI in higher education
  • Aligning interests among multiple stakeholders in the use of Gen AI (industry/employers, university staff, and students)

Dr. Xin Zhao
Prof. Dr. Minna Rollins
Dr. Marco Carratu
Topic Editors

Keywords

  • generative AI
  • higher education
  • inclusion
  • design
  • instructional responses
  • GenAI pedagogy

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
AI
ai
5.0 6.9 2020 20.7 Days CHF 1600 Submit
Education Sciences
education
2.6 5.5 2011 29.2 Days CHF 1800 Submit
Electronics
electronics
2.6 6.1 2012 16.8 Days CHF 2400 Submit

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Published Papers (3 papers)

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21 pages, 1536 KiB  
Systematic Review
Navigating the Complexity of Generative Artificial Intelligence in Higher Education: A Systematic Literature Review
by Birago Amofa, Xebiso Blessing Kamudyariwa, Fatima Araujo Pereira Fernandes, Oluyomi Abayomi Osobajo, Faith Jeremiah and Adekunle Oke
Educ. Sci. 2025, 15(7), 826; https://doi.org/10.3390/educsci15070826 - 29 Jun 2025
Viewed by 127
Abstract
Technological innovation has transformed educational settings, enabling artificial intelligence (AI)-driven teaching and learning processes. While AI is still in its embryonic stage in education, generative artificial intelligence has evolved rapidly, significantly shifting the teaching and learning context. With no clarity about the impacts [...] Read more.
Technological innovation has transformed educational settings, enabling artificial intelligence (AI)-driven teaching and learning processes. While AI is still in its embryonic stage in education, generative artificial intelligence has evolved rapidly, significantly shifting the teaching and learning context. With no clarity about the impacts of generative artificial intelligence on education, there is a need to synthesise research findings to demystify generative artificial intelligence and address concerns regarding its application in the teaching and learning process. This paper systematically synthesises studies on generative artificial intelligence in teaching and learning to understand key arguments and stakeholders’ perceptions of generative artificial intelligence in teaching and learning. The systematic review reveals five main domains of research within the field: (i) current awareness (understanding) of generative artificial intelligence, (ii) stakeholder perceptions, (iii) mechanisms for adopting generative artificial intelligence, (iv) issues and challenges of implementing generative artificial intelligence, and (v) contributions of generative artificial intelligence to student performance. This review examines the practical and policy implications of generative artificial intelligence, providing recommendations to address the concerns and challenges associated with generative artificial intelligence-driven teaching and learning processes. Full article
(This article belongs to the Topic Generative Artificial Intelligence in Higher Education)
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23 pages, 2283 KiB  
Article
AI-ENGAGE: A Multicentre Intervention to Support Teaching and Learning Engagement with Generative Artificial Intelligence Tools
by Keelin Leahy, Ekin Ozer and Eoin P. Cummins
Educ. Sci. 2025, 15(7), 807; https://doi.org/10.3390/educsci15070807 - 23 Jun 2025
Viewed by 375
Abstract
The emergence of generative artificial intelligence (GenAI) chatbots, such as ChatGPT, presents unique challenges and opportunities in an educational setting; however, they lack empirical evidence as teaching and learning tools. This study sought to investigate the impact of teacher-led AI-focused interventions in higher [...] Read more.
The emergence of generative artificial intelligence (GenAI) chatbots, such as ChatGPT, presents unique challenges and opportunities in an educational setting; however, they lack empirical evidence as teaching and learning tools. This study sought to investigate the impact of teacher-led AI-focused interventions in higher education institutions in different subject areas. Our aims were to support student engagement, explore the impact of AI tools for learning engagement and efficiency and skill development, and promote awareness of the strengths and limitations of GenAI tools in an educational context. This study was carried out with three distinct cohorts; Physiology, Initial Teacher Education, and Engineering, with year 3 and 4 undergraduate students. Each cohort received two 50 min teacher-led AI-focused interventions, including practical exercises relevant to the specific discipline. Following the interventions, students from all three cohorts received a common (optional) survey that quantitatively and qualitatively evaluated their experiences. Data from the three cohorts was pooled for analysis, with individual cohort analyses for Physiology, Initial Teacher Education, and Engineering provided. Our data indicates that teacher-led introductions to AI tools have positive effects on student engagement with peers, educators, and most notably the subject the students engage in. Students also reported very positive supportive effects with respect to learning engagement, learning efficiency, and critical thinking skills. Students found GenAI tools most useful for gathering knowledge and research purposes, while notable limitations included challenges associated with generating prompts and the accuracy of information. Students noted plagiarism as a significant ethical concern. Taken together, our data collected from diverse teaching and learning contexts support the use of teacher-led AI-focused interventions, specifically ChatGPT, in third-level education. Approaches like this are highly relevant to the university teaching of Physiology, Initial Teacher Education, and Engineering but are also more broadly applicable to third-level education in general to inform opportunities, limitations, and ethical considerations of GenAI in education. Full article
(This article belongs to the Topic Generative Artificial Intelligence in Higher Education)
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13 pages, 1415 KiB  
Article
The Digitisation of Writing in Higher Education: Exploring the Use of Wordtune as an AI Writing Assistant
by Xin Zhao, Laura Sbaffi and Andrew Cox
Electronics 2025, 14(6), 1194; https://doi.org/10.3390/electronics14061194 - 18 Mar 2025
Cited by 1 | Viewed by 722
Abstract
Background: Accelerated by the advent of AI-powered writing assistants, writing, as a crucial aspect of higher education assessment and practice, has undergone rapid digitisation in recent decades. However, there is a paucity of empirical research on its use in the everyday practice of [...] Read more.
Background: Accelerated by the advent of AI-powered writing assistants, writing, as a crucial aspect of higher education assessment and practice, has undergone rapid digitisation in recent decades. However, there is a paucity of empirical research on its use in the everyday practice of students and staff. This study explores the use of Wordtune, an AWCF tool, to determine its benefits and limits from a user perspective. Methods: The research was conducted through a large-scale survey of Wordtune users. Descriptive statistics were generated, exploratory and confirmatory factor analysis was performed, and open-ended questions were analysed using content analysis. Results: Wordtune users are typically confident English speakers and use it alongside other tools such as Grammarly and Google translate. Wordtune is perceived by users as offering low-order benefits in terms of rephrasing and writing more grammatically but also as having high-order benefits such as overcoming mental blocks and creating opportunities for language learning. Users acknowledged very few drawbacks to using Wordtune. Conclusions: Our paper concludes with pedagogic suggestions for educators to support the use of AI writing assistants for student language learning. Full article
(This article belongs to the Topic Generative Artificial Intelligence in Higher Education)
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