Matches in SemOpenAlex for { <https://semopenalex.org/work/W2958075928> ?p ?o ?g. }
Showing items 1 to 74 of
74
with 100 items per page.
- W2958075928 endingPage "2809" @default.
- W2958075928 startingPage "2794" @default.
- W2958075928 abstract "Digital data are transforming higher education (HE) to be more student-focused and metrics-centred. In the UK, capturing detailed data about students has become a government priority, with an emphasis on using student data to measure, compare and assess university performance. The purpose of this paper is to examine the governmental and commercial drivers of current large-scale technological efforts to collect and analyse student data in UK HE. The result is an expanding data infrastructure which includes large-scale and longitudinal datasets, learning analytics services, student apps, data dashboards and digital learning platforms powered by artificial intelligence (AI). Education data scientists have built positive pedagogic cases for student data analysis, learning analytics and AI. The politicization and commercialization of the wider HE data infrastructure is translating them into performance metrics in an increasingly market-driven sector, raising the need for policy frameworks for ethical, pedagogically valuable uses of student data in HE. Practitioner Notes What is already known about this topic Learning analytics, education data science and artificial intelligence are opening up new ways of collecting and analysing student data in higher education. UK government policies emphasize the use of student data for improvements to teaching and learning. What this paper adds A conceptual framework from “infrastructure studies” demonstrates how political objectives and commercial aims are fused to HE data systems, with data infrastructure becoming a key tool of government reform. A critical infrastructure analysis shows that student data processing technologies are being developed and deployed to measure university performance through student data. Implications for practice and/or policy Educators and managers in universities need to prepare robust institutional frameworks to govern their use of student data. Learning analytics practitioners, data scientists, learning scientists and social science researchers need to collaborate with the policy community and education technology developers on new policy frameworks to challenge narrow uses of student data as performance metrics." @default.
- W2958075928 created "2019-07-23" @default.
- W2958075928 creator A5086450084 @default.
- W2958075928 date "2019-07-09" @default.
- W2958075928 modified "2023-10-12" @default.
- W2958075928 title "Policy networks, performance metrics and platform markets: Charting the expanding data infrastructure of higher education" @default.
- W2958075928 cites W1624797311 @default.
- W2958075928 cites W1870458811 @default.
- W2958075928 cites W2087750029 @default.
- W2958075928 cites W2206322733 @default.
- W2958075928 cites W2501145764 @default.
- W2958075928 cites W2507201434 @default.
- W2958075928 cites W2588841625 @default.
- W2958075928 cites W2611176525 @default.
- W2958075928 cites W2736170603 @default.
- W2958075928 cites W2770182351 @default.
- W2958075928 cites W2883412093 @default.
- W2958075928 cites W2892120767 @default.
- W2958075928 cites W2899947470 @default.
- W2958075928 cites W2900728025 @default.
- W2958075928 cites W2902258885 @default.
- W2958075928 cites W2909679658 @default.
- W2958075928 cites W2937100135 @default.
- W2958075928 cites W2942268010 @default.
- W2958075928 cites W2962776606 @default.
- W2958075928 cites W2964815814 @default.
- W2958075928 cites W2968914873 @default.
- W2958075928 cites W4234686611 @default.
- W2958075928 cites W4236635370 @default.
- W2958075928 cites W4243459145 @default.
- W2958075928 cites W4245299350 @default.
- W2958075928 cites W4252045650 @default.
- W2958075928 cites W584790758 @default.
- W2958075928 doi "https://doi.org/10.1111/bjet.12849" @default.
- W2958075928 hasPublicationYear "2019" @default.
- W2958075928 type Work @default.
- W2958075928 sameAs 2958075928 @default.
- W2958075928 citedByCount "62" @default.
- W2958075928 countsByYear W29580759282019 @default.
- W2958075928 countsByYear W29580759282020 @default.
- W2958075928 countsByYear W29580759282021 @default.
- W2958075928 countsByYear W29580759282022 @default.
- W2958075928 countsByYear W29580759282023 @default.
- W2958075928 crossrefType "journal-article" @default.
- W2958075928 hasAuthorship W2958075928A5086450084 @default.
- W2958075928 hasBestOaLocation W29580759282 @default.
- W2958075928 hasConcept C144133560 @default.
- W2958075928 hasConcept C2522767166 @default.
- W2958075928 hasConcept C41008148 @default.
- W2958075928 hasConceptScore W2958075928C144133560 @default.
- W2958075928 hasConceptScore W2958075928C2522767166 @default.
- W2958075928 hasConceptScore W2958075928C41008148 @default.
- W2958075928 hasIssue "6" @default.
- W2958075928 hasLocation W29580759281 @default.
- W2958075928 hasLocation W29580759282 @default.
- W2958075928 hasOpenAccess W2958075928 @default.
- W2958075928 hasPrimaryLocation W29580759281 @default.
- W2958075928 hasRelatedWork W1996408511 @default.
- W2958075928 hasRelatedWork W2093578348 @default.
- W2958075928 hasRelatedWork W2350741829 @default.
- W2958075928 hasRelatedWork W2358668433 @default.
- W2958075928 hasRelatedWork W2376932109 @default.
- W2958075928 hasRelatedWork W2382290278 @default.
- W2958075928 hasRelatedWork W2390279801 @default.
- W2958075928 hasRelatedWork W2748952813 @default.
- W2958075928 hasRelatedWork W2766271392 @default.
- W2958075928 hasRelatedWork W2899084033 @default.
- W2958075928 hasVolume "50" @default.
- W2958075928 isParatext "false" @default.
- W2958075928 isRetracted "false" @default.
- W2958075928 magId "2958075928" @default.
- W2958075928 workType "article" @default.