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Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions

  • Teaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In thisTeaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In this way, a comparative analysis between AI usage in administration and teaching and learning processes, a systematization of the state of research, an identification of research gaps as well as further research path on AI in higher education institutions are contributed to research.show moreshow less

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Metadaten
Author details:André UllrichORCiDGND, Gergana VladovaORCiDGND, Felix EigelshovenORCiD, André RenzORCiDGND
URN:urn:nbn:de:kobv:517-opus4-589077
DOI:https://doi.org/10.25932/publishup-58907
ISSN:1867-5808
Title of parent work (German):Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe
Subtitle (English):a bibliometrics analysis and recommendation for future research
Publication series (Volume number):Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe (160)
Publication type:Postprint
Language:English
Date of first publication:2022/09/05
Publication year:2022
Publishing institution:Universität Potsdam
Release date:2023/04/20
Issue:160
Number of pages:18
Source:Discover Artificial Intelligence 2 (2022), Art. 16. DOI: https://doi.org/10.1007/s44163-022-00031-7
Organizational units:Wirtschafts- und Sozialwissenschaftliche Fakultät / Wirtschaftswissenschaften
DDC classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
3 Sozialwissenschaften / 37 Bildung und Erziehung / 370 Bildung und Erziehung
3 Sozialwissenschaften / 37 Bildung und Erziehung / 378 Hochschulbildung
Peer review:Referiert
Publishing method:Open Access / Green Open-Access
License (German):License LogoCC-BY - Namensnennung 4.0 International
External remark:Bibliographieeintrag der Originalveröffentlichung
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