The DOI matches its Crossref record; 46 of the 50 references it cites were found in a registry or an index.
University teachers' perceptions of responsibility and artificial intelligence in higher education - An experimental philosophical study
Open accessAbstract
This study investigates university teachers’ relationships with emerging technologies by focusing on the uptake of artificial intelligence in higher education practices. We utilise an experimental philosophy approach to i) determine university teachers’ intuitions around universities’ responsibilities to adopt new artificial intelligence technologies, ii) understand the conditions under which university teachers consider artificial intelligence defensible and, hence, would be willing to introduce such tools and services into their daily practice and iii) specify teachers’ self-reported knowledge of artificial intelligence. An online survey, where participants were sent one of three different cases (Case A related to first-generation students, Case B, an archetypical student, Case C, students with a learning disability), and 18 identical questions across all three cases. The survey was distributed among 1773 teachers. Based on the responses of 194 university teachers, we identify differences related to responsibility, equity, and knowledge about artificial intelligence. Our quantitative data exhibited that in Case A and Case C, the respondents ranked to a higher degree that universities should use artificial intelligence tools and systems to achieve equitable outcomes. Data revealed no statistically significant associations among the respondents with regard to background variables in Case A. However, Case B and Case C disclosed statistically significant associations concerning gender, age, faculty, and academic position among the participants. Moreover, we identify teachers’ fears and scepticism about artificial intelligence in higher education, concerns about fairness and responsibility, and lack of knowledge about artificial intelligence and resources to engage with artificial intelligence in teaching practices.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Additionally, teachers have expressed concerns about fairness, accountability, and a lack of institutional support or resources for integrating GAI into teaching. 4”
In the citing paper
“An experimental philosophical study (McGrath et al., 2023) of university teachers' perceptions of responsibility and AI in higher education found a broad consensus among participants that universities should provide AI educational tools, especially to support first-generation students and those with learning disabilities, reflecting a commitment to equity and fairness, as argued by Prinsloo and Sl”
From Artificial intelligence in higher education: exploring faculty use, self-efficacy, distinct profiles, and professional development needs (2024) · cites this paper as McGrath et al., 2023
In the citing paper
“This study found that ChatGPT and other AI tools can help students produce more grammatically correct and fluent texts, which is in line with previous research [9, 17].”
From Evaluating the impact of using ChatGPT on EFL students’ argumentative skills (2026) · cites this paper as [17]
In the citing paper
“In particular, Mcgrath et al. (2023) found that Swedish university teachers consider that higher education institutions have a responsibility to use AI educational technologies to support students, especially those from disadvantaged groups such as students with a learning disability.”
From Exploring the role of generative AI in higher education: Semi-structured interviews with students with disabilities (2025) · cites this paper as McGrath et al., 2023
In the citing paper
“The study also highlighted the difficulty of adopting AI-based technologies due to a lack of resources and time (McGrath et al., 2023).”
From Exploring the role of generative AI in higher education: Semi-structured interviews with students with disabilities (2025) · cites this paper as McGrath et al., 2023
In the citing paper
“On the one hand, it supports the argument made by McGrath et al. (2023) that universities have a responsibility to adopt AI tools.”
From Exploring the role of generative AI in higher education: Semi-structured interviews with students with disabilities (2025) · cites this paper as McGrath et al. (2023)
In the citing paper
“of which ChatGPT is the most known (Mah & Groß, 2024; McGrath et al., 2023; Rajabi et al., 2024).”
From Planets, cars, and personas: Toward an understanding of faculty perceptions of artificial intelligence through visual metaphors and projective techniques (2025) · cites this paper as McGrath et al., 2023
In the citing paper
“Research suggests there are similarities across institutions regarding limited awareness of AI and access to GenAI tools”
From Planets, cars, and personas: Toward an understanding of faculty perceptions of artificial intelligence through visual metaphors and projective techniques (2025) · cites this paper as McGrath et al., 2023
In the citing paper
“Finally, there have been instances of students without any learning disabilities that state that the use of assistive technology constitutes an unfair advantage for students with disabilities and hinders the educational process [54].”
From Impact of Artificial Intelligence and Virtual Reality on Educational Inclusion: A Systematic Review of Technologies Supporting Students with Disabilities (2024) · cites this paper as [54]
In the citing paper
“Finally, the literature also focuses on the issue of promoting ethical and responsible methods of integrating these assistive tools, so that they can effectively and appropriately complement every part of the learning experiences for the students [54].”
From Impact of Artificial Intelligence and Virtual Reality on Educational Inclusion: A Systematic Review of Technologies Supporting Students with Disabilities (2024) · cites this paper as [54]
In the citing paper
“As emphasised in the literature [50,54], platforms developed with the assistance of AI have enabled teachers and educators to tailor their content and educational material to the specific needs and preferences of students with disabilities, promoting the fostering of personalised instruction.”
From Impact of Artificial Intelligence and Virtual Reality on Educational Inclusion: A Systematic Review of Technologies Supporting Students with Disabilities (2024) · cites this paper as [54]
In the citing paper
“There seems to exist a significant difficulty in efficiently incorporating AI and VR technologies in teaching processes [54]”
From Impact of Artificial Intelligence and Virtual Reality on Educational Inclusion: A Systematic Review of Technologies Supporting Students with Disabilities (2024) · cites this paper as [54]
In the citing paper
“which can be explained both through the inadequate training teachers have received when it comes to the utilisation of new technologies [50,54], as well as through the teachers' own doubts and fears surrounding the use of assistive technologies in their classes, and the subsequent impact they would have in their work [54].”
From Impact of Artificial Intelligence and Virtual Reality on Educational Inclusion: A Systematic Review of Technologies Supporting Students with Disabilities (2024) · cites this paper as [54]
Citations
Cites
Increasing Returns, Path Dependence, and the Study of Politics
Pierson, P. (2000) · American Political Science Review · doi:10.2307/2586011 · Cited by 8,094
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-019-0171-0 · Cited by 7,242
The ethics of algorithms: Mapping the debate
Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016) · Big Data & Society · doi:10.1177/2053951716679679 · Cited by 4,567
Pretesting survey instruments: An overview of cognitive methods
Collins, D. (2003) · Quality of Life Research · doi:10.1023/a:1023254226592 · Cited by 1,520
(2016) · Open Research Online (The Open University) · Cited by 1,410
State of the art and practice in AI in education
Holmes, W., & Tuomi, I. (2022) · European Journal of Education · doi:10.1111/ejed.12533 · Cited by 1,093
ORGANIZATIONAL PATH DEPENDENCE: OPENING THE BLACK BOX.
SYDOW, J., SCHREYÖGG, G., & KOCH, J. (2009) · Academy of Management Review · doi:10.5465/amr.2009.44885978 · Cited by 884
Artificial intelligence literacy in higher and adult education: A scoping literature review
Laupichler, M. C., Aster, A., Schirch, J., & Raupach, T. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100101 · Cited by 658
Chounta, I., Bardone, E., Raudsep, A., & Pedaste, M. (2021) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-021-00243-5 · Cited by 622
Discourses of artificial intelligence in higher education: a critical literature review
Bearman, M., Ryan, J., & Ajjawi, R. (2023) · Higher Education · doi:10.1007/s10734-022-00937-2 · Cited by 545
Research works printed but not linked: 4
- Cerratto Pargman, 2023, New vistas on responsible learning analytics: A data feminist perspective, Journal of Learning Analytics, 1
- Tomczak, 2014, The need to report effect size estimates revisited. An overview of some recommended measures of effect size, Trends in Sport Sciences, 1, 19
- Tronto, 1998, An ethic of care. Generations, Journal of the American Society on Aging, 22, 15
- Williamson, 2022, A review of learning analytics dashboard research in higher education: Implications for justice, equite, diversity, and inclusion, 260
Cited by
Sorted by citations
Items 101–198 of 198
Embracing Generative AI in Education: A Global View on AI Anxiety Through Digital Literacy
Kristandl, G. (2025) · Springer eBooks · doi:10.1007/978-3-031-97999-6_5 · Cited by 3
Warrier, A. M., Agarwal, A., Savelka, J., Bogart, C., & Burte, H. (2025) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie63693.2025.11328591 · Cited by 3
Hallal, K., Hamdan, R., & Tlais, S. (2026) · Journal of Chemical Education · doi:10.1021/acs.jchemed.5c00693 · Cited by 3
MRAYYAN, M. T., & Alomari, A. K. (2026) · Human Behavior and Emerging Technologies · doi:10.1155/hbe2/9885653 · Cited by 3
del Litoral., C. E., de la Cruz, J. P. C., García, A. E. P., del Caribe, U. A., Cárdenas, J. E. C., del Caribe, U. A., Gómez, L. M. P., & del Caribe, U. A. (2024) · Ad-gnosis · doi:10.21803/adgnosis.13.13.667 · Cited by 6
Zhao, T., Zhu, J., Jian, Z., Zhou, X., Yang, S., & Zhang, P. (2024) · Education Sciences · doi:10.3390/educsci14121412 · Cited by 3
Arunima, S. N., & Akhter, M. (2025) · Review of Artificial Intelligence in Education · doi:10.37497/rev.artif.intell.educ.v6ii.53 · Cited by 3
Artificial Intelligence in Malaysian Education: An Evaluation of Opportunities and Pathways
Murad, D. F., Hassan, R. B., Naseer, T. A., Inn, A., Wijanarko, B. D., & Fernando, E. (2025) · International Conference on Data Science and Its Applications (ICoDSA) · doi:10.1109/icodsa67155.2025.11157027 · Cited by 2
Fernandes, R. M., Nagata, V. D. M. N., Filho, W. L., Rampasso, I. S., Ávila, L. V., da Silva, J. M. N., Anholon, R., & Martins, V. W. B. (2025) · International Journal of Educational Management · doi:10.1108/ijem-08-2024-0441 · Cited by 3
The double edge of communicative AI: continuity and disruption in higher education
Breiter, A., & Lopez, P. (2026) · i-com · doi:10.1515/icom-2026-0007 · Cited by 4
Aljumah, A. I., Nuseir, M. T., Hameed, W. U., AlShawabkeh, A., & Fararah, F. S. (2026) · Discover Sustainability · doi:10.1007/s43621-026-03367-7 · Cited by 2
Pitchaipandi, P., & Chinnasamy, B. (2024) · Proceedings on Engineering Sciences · doi:10.24874/pes06.02.013 · Cited by 2
Dushchenko, O. S. (2024) · Educological discourse · doi:10.28925/2312-5829/2024.3.1 · Cited by 12
A Framework for the Responsible Integration of Generative AI Tools in Learning
Ko, S., & Chan, S. C. H. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3373-1017-6.ch006 · Cited by 2
Генеративный искусственный интеллект: интеграция в вузах России и мира
Kobelev, S. V., & Леонидович, О. П. (2025) · Vocational education and labour market · doi:10.52944/port.2025.62.3.009 · Cited by 2
Exploring Artificial Intelligence Anxiety Among Basic School Teachers in Ghana
Arthur, F., Boateng, E., Opoku, E., Gyedu, F. O., Asare-Bediako, S., Quayson, E., Salifu, I., Attom, E. R., & Nortey, S. A. (2026) · SAGE Open · doi:10.1177/21582440251410713 · Cited by 4
Isak, M. A., & Isak, A. A. (2025) · Research Square · doi:10.21203/rs.3.rs-7292768/v1 · Cited by 2
Evaluating the impact of using ChatGPT on EFL students’ argumentative skills
Mai, H. T. (2026) · Discover Education · doi:10.1007/s44217-026-01153-1 · Cited by 2
ASL Educators' Perspectives on AI for Enhancing Student Learning in American Sign Language Education
Hassan, S., Nourian, L., de Lacerda Pataca, C., M Olson, M., D'aurio, T., Agarwal, K., Asad, S. M. N., Tigwell, G. W., & Huenerfauth, M. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791928 · Cited by 1
Garro-Mena, L. (2024) · REDU Revista de Docencia Universitaria · doi:10.4995/redu.2024.21989 · Cited by 2
Integración de la inteligencia artificial en la enseñanza universitaria
Gaibor, D. S. P., Jiménez, J. F. M., Granja, C. D. A., & Jiménez, J. A. V. (2024) · Revista Chone Ciencia y Tecnología · doi:10.56124/cct.v2i2.005 · Cited by 1
ERKILIÇ, E., & Çifçi, İ. (2025) · Journal of Multidisciplinary Academic Tourism · doi:10.31822/jomat.2025-10-1-111 · Cited by 1
A Systematic Review of Leadership Curriculum at the U.S. Air Force Academy from 1955 to 1980
Ramig, T. (2024) · Journal of Character and Leadership Development · doi:10.58315/jcld.v11.307 · Cited by 1
Annamalai, S., Ramnath, R., Antony, S., & Devi, S. B. (2025) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3373-2262-9.ch017 · Cited by 1
Xia, L. A., & Beech, H. (2025) · Journal of China Computer-Assisted Language Learning · doi:10.1515/jccall-2024-0031 · Cited by 3
Lascano, D. M. V., Zambrano, T. L. C., Collahuazo, E. X. M., & Ocaña, Y. E. C. (2025) · Data & Metadata · doi:10.56294/dm20251017 · Cited by 2
Mbewe, G., Chamba, P., Duwa, V., Kibombwe, G. M., Dzaoneni, A., & Chigwenembe, P. (2025) · Journal of Global Research in Education and Social Science · doi:10.56557/jogress/2025/v19i39526 · Cited by 4
Large Language Models in Graduate Information Science Education: Benefits and Challenges
Xiang, S., Deng, H., Liu, J., & Wu, J. (2025) · International Conference on Computer Science and Technologies in Education (CSTE) · doi:10.1109/cste64638.2025.11092151 · Cited by 1
Spor Bilimleri Öğrencilerinin Yapay Zekâ Tutumları ile Spor Farkındalığı Düzeylerinin İncelenmesi
İNAN, H. (2025) · Journal of Global Sport and Education Research · doi:10.55142/jogser.1715410 · Cited by 2
Faculty Perceptions of AI Use in Higher Education: A Case Study
Jacob, H. R., Cozad, D., & Castle, K. (2025) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-80592-228-520251008 · Cited by 1
More Talk Than Touch: Chinese Art Educators and the Overwhelming Discourse of AI in Higher Education
Tadesse, E., Fu, S., & Diankun, J. (2026) · European Journal of Education · doi:10.1111/ejed.70408 · Cited by 1
A Study on AI-Related Anxiety among Pre-Service Teachers
Hündür, T., Yazıcı, J., & Taş, E. (2026) · Journal of Computer and Education Research · doi:10.18009/jcer.1742147 · Cited by 1
From colleagues to conferences: Where public administration instructors learn about AI
Thomas, M. B., & Larson, S. (2026) · Teaching Public Administration · doi:10.1177/01447394261462108 · Cited by 1
الروبي, ح. أ. (2023) · دراسات فى التعلیم الجامعى · doi:10.21608/deu.2023.235556.1026 · Cited by 1
How Artificial Intelligence (AI) Can Support Developing Curriculums in Education and for Research
Safaeimanesh, F., Güden, N., & Safaeimanesh, S. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-0884-4.ch002 · Cited by 1
Redefining Teaching in the Era of Generative Artificial Intelligence
Joshi, R., Pandey, K., & Kumari, S. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-7255-5.ch003 · Cited by 1
Aydoğmuş, H. Y., & Aydoğmuş, U. (2025) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-7949-3.ch006 · Cited by 1
Artificial Intelligence Tools for Question Generation
Kılıçkaya, F., & Liontas, J. I. (2024) · The TESOL Encyclopedia of English Language Teaching · doi:10.1002/9781118784235.eelt1042 · Cited by 1
Jandrić, P., Manchester, H., Ross, J., Hayes, S., Macgilchrist, F., Green, B., Gómez, D. L., Shankar, K., & Lupton, D. A. (2025) · Postdigital Science and Education · doi:10.1007/s42438-024-00534-9 · Cited by 1
Teaching in the Age of AI: Exploring Faculty Perceptions and Practices
Nelson, K., Marshall, D. T., Manning, K. Q., & Hong, H. B. (2026) · AI in Education · doi:10.31219/osf.io/nqb84_v1 · Cited by 2
AI in Universities: The Good, the Bot, and the Ugly TruthsPreprint
Adewusi, M. A., Ainebyoona, C., Odekeye, O. T., & Ngoma, M. (2025) · Research Square · doi:10.21203/rs.3.rs-6883202/v1 · Cited by 4
A Systematic Review of Ethical Integration of Generative AI in Higher Education
Yarboi, P. Y., Adu-Manu, K. S., Amponsah, S., Oheneba-Sakyi, Y., & Barimah, A. (2026) · Education Sciences · doi:10.3390/educsci16071016 · Cited by 1
Ayanda, A. O. (2026) · International Journal of Applied Resilience and Sustainability · doi:10.70593/deepsci.0203003
“These technologies use machine learning, predictive analytics, and learner modeling to adjust instructional content according to each student’s needs [45-46].”
Adoptions of AI in Education: A Systematic Literature ReviewPreprint
Arya, S. (2024) · Research Square · doi:10.21203/rs.3.rs-3978368/v1
Strategies and Considerations of Implementing AI in Higher Education
Harthy, K. A., & Hasani, S. A. A. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-2145-4.ch011
Coleman, A., & Beta, K. (2024) · Contributions to management science · doi:10.1007/978-3-031-58704-7_12 · Cited by 1
Peixer, C. G., Nass, F. A., Hirt, F. N., de Moura, G. S., Trainoti, J. D. A. S., Schroeder, K., Wagner, L. A., Becker, L. C., Rodrigues, N. C., & Busnello, V. E. I. (2025) · doi:10.29327/5474955
Cano, C. A. G., Castillo, V. S., & Zapata, E. M. J. (2025) · REVISTA COLOMBIANA DE TECNOLOGIAS DE AVANZADA · doi:10.24054/rcta.v2i46.3743 · Cited by 4
Universidad Politécnica Salesiana, V. D. I., Inga, E., Arias, S. T. C., & Universidad Politécnica Salesiana, V. A. (2025) · doi:10.17163/abyaups.127.10
Ellington, L. M. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5102-5.ch012
Insights into Faculty's use of Generative Artificial Intelligence systems in Engineering Classrooms.
Hassani, A., Daher, T. A., Trainin, G., & Wheeler, J. M. (2025) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--56806
Iswanti, U. D., Suryanto, T. L. M., Ridwandono, D., Faroqi, A., & Chuttur, M. Y. (2025) · INTENSIF Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi · doi:10.29407/intensif.v9i2.24993 · Cited by 1
A Mixed-Methods Study of The Impact of ChatGPT on EFL Students’ Argumentative Writing PerformancePreprint
Hiền, M. T. (2025) · Research Square · doi:10.21203/rs.3.rs-7112215/v1
Lee, S.-S., Kim, J., Yu, S., & Li, N. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-05891-9 · Cited by 3
Revisión bibliométrica sobre la adopción de inteligencia artificial en la educación superior
Jiménez, M. U., López-Mallama, O. M., & Espinosa, A. A. (2025) · Revista Guillermo de Ockham · doi:10.21500/22563202.7780
Student and Teacher Perceptions on AI Integration in Indian Higher Education
Sekar, R. R. R., Parab, G. A., Bheemesh, B., Krithi, G., & Srinivas, T. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-7912-8.ch006
Morales, M., Rosales, M., Linares, B., Hernández-Rizzardini, R., & Amado-Salvatierra, H. R. (2025) · IEEE Digital Education and MOOCS Conference (DEMOcon) · doi:10.1109/democon65705.2025.11282754
AI-Enhanced Professional Development for Language Teachers
SAYIN, İ., & Coşkun, D. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-2927-7.ch002
Jay, A., Koh, Y., & Hoppe, E. J. (2026) · The Journal of Arts Management Law and Society · doi:10.1080/10632921.2026.2621379
Yetik, S. S. (2024) · DergiPark (Istanbul University)
Prototype of Gamification Teaching Materials to Foster AI Literacy for Children
Sakakura, T., 西田, 義., Sakamoto, S., & Kitagawa, T. (2025) · IEEE International Conference on Engineering Education (ICEED) · doi:10.1109/iceed66794.2025.11400000
Jeya, S. F., & Saravanakumar, A. (2026) · Innovare Journal of Education · doi:10.22159/ijoe.2026v14i2.58362
Iturralde, D. D. O. (2026) · Etic net Revista científica electrónica de Educación y Comunicación en la Sociedad del Conocimiento · doi:10.30827/eticanet.v26i1.31168 · Cited by 2
Exploring AI's Role in Startup Success: A Framework for Future Entrepreneurs
Dey, S. K., & Sharma, D. (2026) · BENTHAM SCIENCE PUBLISHERS eBooks · doi:10.2174/9798898812973126010013
Velarde-Camaqui, D., Peláez‐Sánchez, I. C., & Guerrero, H. M. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1730207 · Cited by 1
Generative AI’s impact on the assessment practices of university faculty
Kearney, S., & Wheeler, B. D. (2026) · To improve the academy · doi:10.3998/tia.7246
Gabelaia, I. (2026) · Sustainability · doi:10.3390/su18104884 · Cited by 1
Ngcobo, L., & Ncube, T. (2026) · Journal of Education and Learning Technology · doi:10.38159/jelt.2026743
Razzaq, S., McCarthy, P. M., & El-Soussi, A. (2026) · Discover Sustainability · doi:10.1007/s43621-026-03464-7
Oh, N., Jiang, Q., Ko, E., Taylor, C. R., & Kim, K. H. (2026) · Journal of Global Fashion Marketing · doi:10.1080/20932685.2026.2682791
From Tool to Teammate? Negotiating Accountability and Disclosure in Academic Generative AI Use
Vassallo, D. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29773-0_10
Faculty Response to Generative AI: Attitudes, Change in Practice and Policy Towards Students’ Use
Meishar‐Tal, H., Seifert, T., & Shonfeld, M. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29770-9_3
Manojkumar, R. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-2811-7.ch004
Mbaga, J., Dulle, F., & Mahenge, M. (2026) · MUST Journal of Research and Development. · doi:10.62277/mjrd2026v7i20010
Analyzing ChatGPT user experiences: a sentiment analysis and thematic cluster analytics approach
Teng, S., & HAMZAH, A. B. (2026) · Quality and User Experience · doi:10.1007/s41233-026-00079-8
Al-Garni, Z. (2026) · Journal of Computer Assisted Learning · doi:10.1002/jcal.70291
Teacher readiness and adaptive quality assurance for human-centered AI in higher education
Mandhari, B. R. S. A. A., Mar, T. T., Hercz, M., & PABINGWIT, A. T. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-026-01757-4 · Cited by 1
Digitalization, AI, and the Changing Social Contract of the Professoriate
Kayyali, M. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-8525-9.ch010
Ren, J., Shi-ping, D., & Xia, J. (2026) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2026.2708156
Artificial Intelligence in Education: Motivational Focus of University Students
Sigacheva, N. A., & Sigachev, M. Y. (2026) · Open Education · doi:10.21686/6/1818-4243-2026-3-97-96
ALShidi, S. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-24810-7_35
Beyond Replacement: How AI Reconfigures Academic Roles
Ghorbani, A., & Blankesteijn, M. (2026) · Foresight and STI Governance · doi:10.17323/fstig.2026.34197
Faculty Training and Professional Development for AI
Pathak, D. N., Rajan, A., Ranjan, R., Retna Mony, R., Rai, S. K., David, B., & Bhoopathy, V. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5586-3.ch009
Future-Focused Leadership for AI and Next Generation Educational Technologies
Manojkumar, R., Srinivas, T. A. S., Inala, K. P., Sharma, N., Sreenivasulu, G., & Yuvaraj, T. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-7411-6.ch004
Fute, A. Z., Amihere, A., & Kangwa, D. (2026) · Open Learning The Journal of Open Distance and e-Learning · doi:10.1080/02680513.2026.2722975
Kosztyó, P., Burkovics, M., & Jenei, P. (2026) · Journal of Physics Conference Series · doi:10.1088/1742-6596/3280/1/012028
Dabiri, A., & Behzadan, A. H. (2026) · AI · doi:10.3390/ai7090363
Chen, Y., & Zare, S. (2026) · AI and Ethics · doi:10.1007/s43681-026-01363-1
Sztuczna inteligencja w warsztacie edukatora-popularyzatora. Propozycja dydaktyczna
Gałuszka, J. (2026) · Archeion · doi:10.4467/26581264arc.26.005.23512
Santos, L. R. A., de Souza, A. D., & Batista, B. G. (2026) · International Conference on Information, Intelligence, Systems & Applications (IISA) · doi:10.1109/iisa71656.2026.11705513
Risk-Dominant Decision Modeling in AI Adoption: Evidence from Indonesian Elementary Teachers
Sasongko, M. V., Sasmoko, Yossy, E. H., & Hermanus, D. R. (2026) · International Conference on ICT for Smart Society (ICISS) · doi:10.1109/iciss71466.2026.11715045
Alkashgari, R. H., Alhayani, A. A., Nasser, A. A., Sheikh, K. H., Sultan, I. E., & Badawy, Y. A. (2026) · MedEdPublish · doi:10.12688/mep.21859.1
Teachers' Use of Artificial Intelligence Tools in Professional Practice
Daniusevičiūtė-Brazaitė, L., Pučėtaitė, R., Gudišauskienė, K., Gaiziuniene, L., Burbaite, R., Gadeikytė, A., & Gudoniene, D. (2026) · 2026 IEEE Digital Education and MOOCS Conference (DEMOcon) · doi:10.1109/democon70840.2026.11708120
Higher education transformation through artificial intelligence: an empirical study in Saudi Arabia
GHUNAIM, H., & Masoud, M. (2026) · Cogent Education · doi:10.1080/2331186x.2026.2722498
Greinke, L., Lange, L., & Richter, J. (2026) · World sustainability series · doi:10.1007/978-3-032-34574-5_26
Teaching in the Age of AI: Perspectives From Public Affairs Faculty
Thomas, M. B., Larson, S., & Sampson, M. (2026) · Journal of Public Affairs Education · doi:10.1177/15236803261495764
The use of artificial intelligence by academic teachers in Poland
Zielińska, M., & Czopek, J. (2026) · Journal of Modern Science · doi:10.13166/jms/241337
Metadata
- Authors
- McGrath, C., Cerratto Pargman, T., Juth, N., & Palmgren, P. J.
- Affiliations
- Stockholm University (SE)
- Uppsala University (SE)
- Karolinska Institutet (SE)
- Corresponding author
- McGrath, Cormac
- Venue
- Computers and Education: Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2023
- Volume
- 4
- Pages
- 100139
- ISSN
- 2666-920X (ISSN-L)
- OpenAlex
- W4367048490
- Semantic Scholar
- abbd9b701038e2951540158928025808e8b32a3c
- Cited by
- 195
- References
- 50
- Citations by year
- 2026: 51 · 2025: 80 · 2024: 55 · 2023: 9
- FWCI
- 45.68
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computers and Education Artificial Intelligence (publishedVersion, cc-by-nc-nd)
- Uppsala University Publications (Uppsala University) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Marianne and Marcus Wallenberg Foundation
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- artificial intelligence in higher education, university faculty perceptions, university responsibility, artificial intelligence adoption, equity, AI knowledge, teacher attitudes toward AI, first-generation college students, students with learning disabilities
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review