Cited by 198Artificial Intelligence in EducationEthics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

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 access
McGrath, Cormac, Cerratto Pargman, Teresa, Juth, Niklas, Palmgren, Per J.·2023·Computers and Education: Artificial Intelligence

Abstract

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.

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Crossref · 10.1016/j.caeai.2023.100139

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Citations

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Show all 50 references

Research works printed but not linked: 4

  1. Cerratto Pargman, 2023, New vistas on responsible learning analytics: A data feminist perspective, Journal of Learning Analytics, 1
  2. 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
  3. Tronto, 1998, An ethic of care. Generations, Journal of the American Society on Aging, 22, 15
  4. Williamson, 2022, A review of learning analytics dashboard research in higher education: Implications for justice, equite, diversity, and inclusion, 260

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Items 101–198 of 198

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
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
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

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