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Goller, M., Caruso, C., &; Harteis, C. (2021). Digitalisation in Agriculture: Knowledge and Learning Requirements of German Dairy Farmers. International Journal for Research in Vocational Education and Training, 8(2), 208–223.https://doi.org/10.13152/IJRVET.8.2.4. 
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Berisha-Gawlowski,https://doi.org/10.1007/978-3-030-55878-9_6__Angelina, Caruso, C., &; Harteis, C. (2021). The Concept of a Digital Twin and Its Potential for Learning Organizations. In D. Ifenthaler, S. Hofhues, M. Egloffstein, &; C. Helbig (Eds.), Digital Transformation of Learning Organizations   (pp. 95–114). Springer.https://doi.org/10.1007/978-3-030-55878-9_6 
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Schneider, S. B. (2021). Conventional and Machine Learning Approaches for Network and Service Coordination.
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Müller, O., Caron, M., Döring, M., Heuwinkel, T., &; Baumeister, J. (n.d.). PIVOT: A Parsimonious End-to-End Learning Framework for Valuing Player Actions in Handball using Tracking Data. 8th Workshop on Machine Learning and Data Mining for Sports Analytics (ECML PKDD 2021). European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML PKDD 2021), Online.
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Bruns, J., Gasteiger, H., &; Strahl, C. (2021). Conceptualising and measuring domain-specific content knowledge of early childhood educators: A systematic review. Review of Education, 9(2), 500–538.https://doi.org/10.1002/rev3.3255 
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Schneider, S. B., Manzoor, A., Qarawlus, H., Schellenberg, R., Karl, H., Khalili, R., &; Hecker, A. (2020). Self-Driving Network and Service Coordination Using Deep Reinforcement Learning. In IEEE International Conference on Network and Service Management (CNSM). IEEE.
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Kersting, J., &; Bäumer, F. S. (2020). SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, 119--123.
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Kersting, J., &; Geierhos, M. (2020). Aspect Phrase Extraction in Sentiment Analysis with Deep Learning. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020) (pp. 391--400). Setúbal, Portugal: SCITEPRESS.
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Harteis, C., Goller, M., &; Caruso, C. (2020). Conceptual Change in the Face of Digitalization. Frontiers in Education, 5(1).https://doi.org/10.3389/feduc.2020.00001 
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Caruso, C., Adammek, C., Bonanati, S., &; Wiescholek, S. (2020). Motivierende Lernzugänge als Ausgangspunkt der Professionalisierung angehender Lehrer_innen. Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion, 3(1), 18–33.https://doi.org/10.4119/hlz-2540 
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Hahn, C. A. (2020). Informationskompetenz durch E-Learning? Durch Lernvideos nach Literatur suchen. die hochschullehre, 6.
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Seiler, M., Pohl, J., Bossek, J., Kerschke, P., &; Trautmann, H. (2020). Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. Parallel Problem Solving from Nature (PPSN XVI), 48–64.https://doi.org/10.1007/978-3-030-58112-1_4 
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Szopinski, D. (2019). Squaring the circle: Business model teaching in large classroom settings. Journal of Business Models, 7(3), 90–100.
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Schumacher, J., &; Rezat, S. (n.d.). A Hypothetical Learning Trajectory for the Learning of the Rules for Manipulating Integers. In U. T. Jankvist, M. Van den Heuvel-Panhuizen, &; M. Veldhuis (Eds.), Proceedings of the Eleventh Congress of the European Society for Research in Mathematics Education (CERM, February 6 – 10, 2019). Utrecht, the Netherlands: Freudenthal Group &; Freudenthal Institute, Utrecht University and ERME.
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Redder, A., Ramaswamy, A., &; Quevedo, D. (2019). Deep reinforcement learning for scheduling in large-scale networked control systems. In Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems. Chicago, USA.
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Schlichtig, M., Opel, S. A., Budde, L., &; Schulte, C. (2019). Understanding Artificial Intelligence – A Project for the Development of Comprehensive Teaching Material. In E. Jasut &; S. Pozdniakov (Eds.), ISSEP 2019 - 12th International conference on informatics in schools: Situation, evaluation and perspectives, Local Proceedings (Vol. 12, pp. 65–73).
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Casalicchio, G., Bossek, J., Lang, M., Kirchhoff, D., Kerschke, P., Hofner, B., Seibold, H., Vanschoren, J., &; Bischl, B. (2019). OpenML: An R Package to Connect to the Machine Learning Platform OpenML. Computational Statistics, 34(3), 977–991.https://doi.org/10.1007/s00180-017-0742-2 
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Harteis, C., &; Fischer, C. (2018). Wissensmanagement unter Bedingungen von Arbeit 4.0. In G. W. Maier, G. Engels, &; E. Steffen (Eds.), Handbuch Gestaltung digitaler und vernetzter Arbeitswelten (pp. 1--18). Berlin, Heidelberg: Springer.
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Fischer, C., Goller, M., Brinkmann, L., &; Harteis, C. (2018). Digitalisation of Work: Between Affordances and Constraints for Learning at Work. In D. Ifenthaler (Ed.), Digital Workplace Learning (pp. 227--249). Cham: Springer.
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