Digital Technologies and the Automation of Education — Key Questions and Concerns
Open accessAbstract
Education — as with most areas of contemporary life — is becoming steadily infused with small acts of technology-based automation. These automations are intrinsic to the software, apps, systems, platforms and digital devices that pervade contemporary education. Viewed on a case-by-case basis, each of these different automations might appear to be of minor importance, and can quickly fade into the background of any school, university or other educational setting. For example, the novelty of a school’s facial recognition ‘visitor management system’ soon passes once one becomes accustomed to not having to ‘sign in’ at the front-desk. The same goes for the initial relief of not having to grade a newly submitted stack of fifty student essays, or not having to walk around to check what a class of students are actually doing on their laptops. These are all tasks that can quickly become unquestioned aspects of what we expect digital technology to be doing in educational contexts.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
There is growing concern that teachers must engage in additional tasks "behind the scenes" to ensure that AI tools are able to function in complex classroom settings.
“In contrast to the idea that AI tools relieve teachers of repetitive and onerous work, there is growing concern that teachers must engage in additional tasks “behind the scenes” (e.g. curating and filtering content, monitoring student–AI interactions, providing technical support) to ensure that AI tools are able to function in complex classroom settings (95).”
From The impact of generative artificial intelligence on socioeconomic inequalities and policy making (2024) · cites this paper as [95]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Why has Critique Run out of Steam? From Matters of Fact to Matters of Concern
Latour, B. (2004) · Critical Inquiry · doi:10.1086/421123 · Cited by 5,595 · see citing works
Code/Space: Software and Everyday Life
Kitchin, R., & Dodge, M. (2011) · doi:10.7551/mitpress/9780262042482.001.0001 · Cited by 964 · see citing works
What is Education For? On Good Education, Teacher Judgement, and Educational Professionalism
Biesta, G. (2015) · European Journal of Education · doi:10.1111/ejed.12109 · Cited by 900 · see citing works
Bainbridge, L. (1982) · IFAC Proceedings Volumes · doi:10.1016/s1474-6670(17)62897-0 · Cited by 321 · see citing works
Bainbridge, L. (1983) · Analysis, Design and Evaluation of Man–Machine Systems · doi:10.1016/b978-0-08-029348-6.50026-9 · Cited by 219 · see citing works
Andrejevic, M. (2019) · doi:10.4324/9780429242595 · Cited by 217 · see citing works
Learning Like a State: Statecraft in the Digital Age
Fourcade, M., & Gordon, J. (2020) · Journal of Law and Political Economy · doi:10.5070/lp61150258 · Cited by 158 · see citing works
Bridle, J. (2019) · C.H.Beck eBooks · doi:10.17104/9783406741784 · Cited by 118 · see citing works
Pasquale, F. (2020) · doi:10.4159/9780674250062 · Cited by 101 · see citing works
Anticipating education: governing habits, memories and policy-futures
Webb, P. T., Sellar, S., & Gulson, K. Ν. (2019) · Learning Media and Technology · doi:10.1080/17439884.2020.1686015 · Cited by 68 · see citing works
Improving the radiologist-CAD interaction: designing for appropriate trust
Jorritsma, W., Cnossen, F., & van Ooijen, P. M. A. (2015) · Clinical Radiology · doi:10.1016/j.crad.2014.09.017 · Cited by 61 · see citing works
The attachments of ‘autonomous’ vehicles
Tennant, C., & Stilgoe, J. (2021) · Social Studies of Science · doi:10.1177/03063127211038752 · Cited by 47 · see citing works
Selker, T. (2008) · Communications of the ACM · doi:10.1145/1409360.1409366 · Cited by 40 · see citing works
Relational architectures and wearable space: Smart schools and the politics of ubiquitous sensation
de Freitas, E., Rousell, D., & Jäger, N. (2019) · Research in Education · doi:10.1177/0034523719883667 · Cited by 26 · see citing works
Rieder, B. (2020) · Routledge eBooks · doi:10.5117/9789462986190 · Cited by 26 · see citing works
Heads in the Clouds: Measuring the Implications of Universities Migrating to Public CloudsPreprint
Fiebig, T., Gürses, S. F., Gañán, C., et al. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.09462 · Cited by 15 · see citing works
Biesta, G. (2015) · doi:10.4324/9781315634319-7 · Cited by 3 · see citing works
Friction and the aesthetics of the smooth
Rasch, M. (2020) · Data Archiving and Networked Services (DANS) · Cited by 2 · see citing works
Rieder, B. (2020) · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 3
- Kitchin, R., & Dodge, M. (2011). Code/space. Cambridge, MA: MIT Press.
- Sparrow, R. (2021) Slaves to the algorithms: algocracy and Republican liberty. Keynote presentation to (Unintended) Information in Human-Machine Interaction symposium, 21-23rd April. Hagen: FernUniversität.
- Zuboff, S. (1988). In the age of smart machines. New York: Basic Books. · DOI
Cited by
Sorted by citations
The impact of generative artificial intelligence on socioeconomic inequalities and policy making
Capraro, V., Lentsch, A., Acemoglu, D., Akgun, S., Akhmedova, A., Bilancini, E., Bonnefon, J.-F., Brañas-Garza, P., Butera, L., Douglas, K. M., et al. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae191 · Cited by 371 · see citing works
Self-citationBozkurt, A., Xiao, J., Lambert, S., Pazurek, A., Crompton, H., Koseoglu, S., Farrow, R., Bond, M., Nerantzi, C., Honeychurch, S., et al. (2023) · Zenodo · doi:10.5281/zenodo.7636568 · Cited by 350 · see citing works
- Authors
- Selwyn, N., Hillman, T., Bergviken Rensfeldt, A., & Perrotta, C.
- Affiliations
- Monash University (AU)
- University of Gothenburg (SE)
- Venue
- Postdigital Science and Education
- Published
- 2021-10-29
- Volume
- 5
- Issue
- 1
- Pages
- 15-24
- ISSN
- 2524-485X (ISSN-L)
- 2524-4868
- OpenAlex
- W3208740840
- Cited by
- 134
- References
- 19
- Citations by year
- 2026: 36 · 2025: 31 · 2024: 27 · 2023: 24 · 2022: 16
- FWCI
- 15.14
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Postdigital Science and Education (publishedVersion, cc-by)
- Monash University Research Portal (Monash University) (publishedVersion, cc-by)
- Funders
- University of Gothenburg
- Topics
- Physical Sciences › Computer Science › Information Systems › Digital Education and Society
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Political Science and International Relations › Global Educational Policies and Reforms
- Keywords
- educational automation, digital technologies in education, educational technology, postdigital education, classroom monitoring, automated grading, visitor management system, technology adoption in schools
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
