TY  - CHAP
A1  - Grum, Marcus
A1  - Kotarski, David
A1  - Ambros, Maximilian
A1  - Biru, Tibebu
A1  - Krallmann, Hermann
A1  - Gronau, Norbert
ED  - Shishkov, Boris
T1  - Managing knowledge of intelligent systems
BT  - the design of a chatbot using domain-specific knowledge
T2  - Business modeling and software design : 11th International Symposium, BMSD 2021, Sofia, Bulgaria, July 5–7, 2021, Proceedings
N2  - 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.
KW  - domain-specific language
KW  - morphologic box
KW  - explainability
Y1  - 2021
SN  - 978-3-030-79975-5
SN  - 978-3-030-79976-2
U6  - https://doi.org/10.1007/978-3-030-79976-2_5
VL  - 422
SP  - 78
EP  - 96
PB  - Springer International Publishing
CY  - Cham
ER  - 
TY  - CHAP
A1  - Langemeyer, Ines
A1  - Gronau, Norbert
A1  - Schmid-Walz, Sabrina
A1  - Kotarski, David
A1  - Reimann, Daniela
A1  - Teichmann, Malte
T1  - From employee to expert
BT  - towards a corona-sensitive approach for data collection
T2  - 2021 Crossing Boundaries Muttenz/Basel and Bern : 4th International VET Conference Crossing Boundaries 8 to 9 April 2021, online, Muttenz and Bern, Switzerland
N2  - 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.
KW  - cross self-confrontation
KW  - recording of workplaces
KW  - corona-sensitive data collection
KW  - age-appropriate vocational training
KW  - augmented reality
Y1  - 2021
U6  - https://doi.org/10.5281/zenodo.4590196
SP  - 226
EP  - 231
ER  - 
TY  - JOUR
A1  - Teichmann, Malte
A1  - Ullrich, André
A1  - Kotarski, David
A1  - Gronau, Norbert
T1  - Facing the demographic change
BT  - recommendations for designing learning factories as age-appropriate teaching-learning environments for older blue-collar workers
JF  - SSRN eLibrary / Social Science Research Network
N2  - 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.
KW  - learning factory
KW  - vocational training
KW  - learning environment
KW  - age-appropriate competence development
KW  - demographic change
Y1  - 2021
U6  - https://doi.org/10.2139/ssrn.3858716
SN  - 1556-5068
PB  - Social Science Electronic Publ.
CY  - [Erscheinungsort nicht ermittelbar]
ER  -