@incollection{GrumKotarskiAmbrosetal.2021,
  author    = {Grum, Marcus and Kotarski, David and Ambros, Maximilian and Biru, Tibebu and Krallmann, Hermann and Gronau, Norbert},
  title     = {Managing knowledge of intelligent systems},
  series = {Business modeling and software design : 11th International Symposium, BMSD 2021, Sofia, Bulgaria, July 5-7, 2021, Proceedings},
  volume    = {422},
  booktitle = {Business modeling and software design : 11th International Symposium, BMSD 2021, Sofia, Bulgaria, July 5-7, 2021, Proceedings},
  editor    = {Shishkov, Boris},
  publisher = {Springer International Publishing},
  address   = {Cham},
  isbn      = {978-3-030-79975-5},
  doi       = {10.1007/978-3-030-79976-2_5},
  pages     = {78 -- 96},
  year      = {2021},
  abstract  = {Since more and more business tasks are enabled by Artificial Intelligence (AI)-based techniques, the number of knowledge-intensive tasks increase as trivial tasks can be automated and non-trivial tasks demand human-machine interactions. With this, challenges regarding the management of knowledge workers and machines rise [9]. Furthermore, knowledge workers experience time pressure, which can lead to a decrease in output quality. Artificial Intelligence-based systems (AIS) have the potential to assist human workers in knowledge-intensive work. By providing a domain-specific language, contextual and situational awareness as well as their process embedding can be specified, which enables the management of human and AIS to ease knowledge transfer in a way that process time, cost and quality are improved significantly. This contribution outlines a framework to designing these systems and accounts for their implementation.},
  language  = {en}
}
@incollection{LangemeyerGronauSchmidWalzetal.2021,
  author    = {Langemeyer, Ines and Gronau, Norbert and Schmid-Walz, Sabrina and Kotarski, David and Reimann, Daniela and Teichmann, Malte},
  title     = {From employee to expert},
  series = {2021 Crossing Boundaries Muttenz/Basel and Bern : 4th International VET Conference Crossing Boundaries 8 to 9 April 2021, online, Muttenz and Bern, Switzerland},
  booktitle = {2021 Crossing Boundaries Muttenz/Basel and Bern : 4th International VET Conference Crossing Boundaries 8 to 9 April 2021, online, Muttenz and Bern, Switzerland},
  doi       = {10.5281/zenodo.4590196},
  pages     = {226 -- 231},
  year      = {2021},
  abstract  = {In the context of the collaborative project Ageing-appropriate, process-oriented and interactive further training in SME (API-KMU), innovative solutions for the challenges of demographic change and digitalisation are being developed for SMEs. To this end, an approach to age-appropriate training will be designed with the help of AR technology. In times of the corona pandemic, a special research design is necessary for the initial survey of the current state in the companies, which will be systematically elaborated in this paper. The results of the previous methodological considerations illustrate the necessity of a mix of methods to generate a deeper insight into the work processes. Video-based retrospective interviews seem to be a suitable instrument to adequately capture the employees' interpretative perspectives on their work activities. In conclusion, the paper identifies specific challenges, such as creating acceptance among employees, open questions, e.g., how a transfer or generalization of the results can succeed, and hypotheses that will have to be tested in the further course of the research process.},
  language  = {en}
}
@inproceedings{TeichmannUllrichKotarskietal.2021,
  author    = {Teichmann, Malte and Ullrich, Andr{\´e} and Kotarski, David and Gronau, Norbert},
  title     = {Facing the demographic change},
  series = {SSRN eLibrary / Social Science Research Network},
  booktitle = {SSRN eLibrary / Social Science Research Network},
  publisher = {Social Science Electronic Publ.},
  address   = {[Erscheinungsort nicht ermittelbar]},
  issn      = {1556-5068},
  doi       = {10.2139/ssrn.3858716},
  pages     = {6},
  year      = {2021},
  abstract  = {Digitization and demographic change are enormous challenges for companies. Learning factories as innovative learning places can help prepare older employees for the digital change but must be designed and configured based on their specific learning requirements. To date, however, there are no particular recommendations to ensure effective age-appropriate training of bluecollar workers in learning factories. Therefore, based on a literature review, design characteristics and attributes of learning factories and learning requirements of older employees are presented. Furthermore, didactical recommendations for realizing age-appropriate learning designs in learning factories and a conceptualized scenario are outlined by synthesizing the findings.},
  language  = {en}
}