@article{VladovaUllrichSloaneetal.2023,
  author    = {Vladova, Gergana and Ullrich, Andr{\´e} and Sloane, Mona and Renz, Andr{\´e} and Tsui, Eric},
  title     = {Editorial: new teaching and learning worlds},
  series = {Frontiers in education},
  volume    = {8},
  journal   = {Frontiers in education},
  publisher = {Frontiers Media},
  address   = {Lausanne},
  issn      = {2504-284X},
  doi       = {10.3389/feduc.2023.1175498},
  pages     = {1 -- 3},
  year      = {2023},
  language  = {en}
}
@misc{UllrichVladovaEigelshovenetal.2022,
  author    = {Ullrich, Andr{\´e} and Vladova, Gergana and Eigelshoven, Felix and Renz, Andr{\´e}},
  title     = {Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe},
  number    = {160},
  issn      = {1867-5808},
  doi       = {10.25932/publishup-58907},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-589077},
  pages     = {18},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@article{UllrichVladovaEigelshovenetal.2022,
  author    = {Ullrich, Andr{\´e} and Vladova, Gergana and Eigelshoven, Felix and Renz, Andr{\´e}},
  title     = {Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions},
  series = {Discover artificial intelligence},
  volume    = {2},
  journal   = {Discover artificial intelligence},
  publisher = {Springer},
  address   = {Cham},
  issn      = {2731-0809},
  doi       = {10.1007/s44163-022-00031-7},
  pages     = {18},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@article{RenzVladova2021,
  author    = {Renz, Andr{\´e} and Vladova, Gergana},
  title     = {Reinvigorating the discourse on Human-Centered artificial intelligence in educational technologies},
  series = {Technology Innovation Management Review},
  journal   = {Technology Innovation Management Review},
  number    = {11},
  publisher = {Talent First Network},
  address   = {Ottawa},
  issn      = {1927-0321},
  doi       = {doi: 10.22215/timreview/1438},
  pages     = {5 -- 16},
  year      = {2021},
  abstract  = {The increasing relevance of artificial intelligence (AI) applications in various domains has led to high expectations of benefits, ranging from precision, efficiency, and optimization to the completion of routine or time-consuming tasks. Particularly in the field of education, AI applications promise immense innovation potential. A central focus in this field is on analyzing and evaluating learner characteristics to derive learning profiles and create individualized learning environments. The development and implementation of such AI-driven approaches are related to learners' data, and thus involves several privacies, ethics, and morality challenges. In this paper, we introduce the concept of human-centered AI, and consider how an AI system can be developed in line with human values without posing risks to humanity. Because the education market is in the early stages of incorporating AI into educational tools, we believe that this is the right time to raise awareness about the use of principles that foster human-centered values and help in building responsible, ethical, and value-oriented AI.},
  language  = {en}
}
@techreport{GagrčinSchaetzRakowskietal.2021,
  author    = {Gagrčin, Emilija and Schaetz, Nadja and Rakowski, Niklas and Toth, Roland and Renz, Andr{\´e} and Vladova, Gergana and Emmer, Martin},
  title     = {We and AI},
  publisher = {Weizenbaum Institute for the Networked Society - the German Internet},
  address   = {Berlin},
  doi       = {10.34669/wi/1},
  pages     = {70},
  year      = {2021},
  language  = {en}
}