TY  - JOUR
A1  - Vladova, Gergana
A1  - Ullrich, André
A1  - Sloane, Mona
A1  - Renz, André
A1  - Tsui, Eric
T1  - Editorial: new teaching and learning worlds
BT  - potentials and limitations of digitalization for innovative and sustainable research and practice in education and training
JF  - Frontiers in education
KW  - creativity
KW  - design thinking
KW  - digital education
KW  - 21st century skills
KW  - open education
KW  - virtual education
Y1  - 2023
U6  - https://doi.org/10.3389/feduc.2023.1175498
SN  - 2504-284X
VL  - 8
SP  - 1
EP  - 3
PB  - Frontiers Media
CY  - Lausanne
ER  - 
TY  - GEN
A1  - Ullrich, André
A1  - Vladova, Gergana
A1  - Eigelshoven, Felix
A1  - Renz, André
T1  - Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions
BT  - a bibliometrics analysis and recommendation for future research
T2  - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe
N2  - 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 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.
T3  - Zweitveröffentlichungen der Universität Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe - 160 
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-589077
SN  - 1867-5808
IS  - 160
ER  - 
TY  - JOUR
A1  - Ullrich, André
A1  - Vladova, Gergana
A1  - Eigelshoven, Felix
A1  - Renz, André
T1  - Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions
BT  - a bibliometrics analysis and recommendation for future research
JF  - Discover artificial intelligence
N2  - 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 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.
Y1  - 2022
U6  - https://doi.org/10.1007/s44163-022-00031-7
SN  - 2731-0809
VL  - 2
PB  - Springer
CY  - Cham
ER  -