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Understanding academics' adoption of learning technologies: A systematic review
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“Technology diffusion in universities is a complicated process, which often faces multifaceted challenges rooted in both organizational and cultural aspects of HEIs [30,31].”
From AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities (2024) · cites this paper as [31]
In the citing paper
“Using the technology acceptance framework to design faculty development primarily predicts adoption intention [6, 7] rather than use and performance outcomes needed in actual educational practice [1].”
In the citing paper
“Faculty members' views on the adoption and use of AI in teaching practices, as well as their interest in professional development regarding AI for teaching and learning, have been relatively underexplored (Liu et al., 2020).”
From Artificial intelligence in higher education: exploring faculty use, self-efficacy, distinct profiles, and professional development needs (2024) · cites this paper as Liu et al., 2020
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Metadata
- Authors
- Liu, Q., Geertshuis, S., & Grainger, R.
- Affiliations
- University of Auckland (NZ)
- University of Otago (NZ)
- Corresponding author
- Liu, Qian
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2020-07
- Volume
- 151
- Pages
- 103857
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W3008352202
- Cited by
- 279
- References
- 178
- Citations by year
- 2026: 22 · 2025: 42 · 2024: 63 · 2023: 42 · 2022: 48 · 2021: 39 · 2020: 23
- FWCI
- 5.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers & Education (publishedVersion)
- Otago University Research Archive (University of Otago) (submittedVersion)
- Funders
- University of Auckland
- Topics
- Physical Sciences › Computer Science › Information Systems › Educational Technology and E-Learning
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Education › Digital Transformation of Higher Education
- Keywords
- learning technology adoption, university faculty, higher education, technology adoption factors, adoption strategies, faculty technology use, educational technology implementation
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.
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