欧洲冠军联赛_欧冠冠军足彩￥app在线投注

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  1. Universit?t
  2. Fakult?ten
  3. Philosophisch-Sozialwissenschaftliche Fakult?t
  4. F?cher & Arbeitsgruppen
  5. Learning Analytics and Educational Data Mining
  6. Team
  7. Dr. Elisabeth Bauer

Dr. Elisabeth Bauer

Akademische R?tin auf Zeit
Learning Analytics and Educational Data Mining
Telefon: +49 (0) 821 598 4349
E-Mail:
Raum: 7018 (BCM)
Sprechzeiten: nach Vereinbarung
Adresse: Alter Postweg 101 (Büro Center Messe), 86159 Augsburg

Lebenslauf

Elisabeth Bauer graduated from LMU Munich with a Bachelor's degree in Educational Sciences (major) and Psychology (minor) and a Master's degree in Psychology in the Learning Sciences. From 2017 to 2023, she worked as a research associate at the Chair of Education and Educational Psychology at LMU Munich; during this time, she completed her PhD, working on the BMBF project FAMULUS on facilitating diagnostic reasoning and argumentation in medical and teacher education using simulations and AI-based automatic adaptive feedback (2017-2020); from 2019 to 2021, her research was funded through a fellowship position in the REASON international doctoral program of the Elite Network of Bavaria; from 2022 to 2023, she was a postdoctoral researcher at the Chair of Education and Educational Psychology at LMU Munich. In 2023 to 2024, she was a postdoctoral researcher at the Technical University of Munich, Chair of Educational Psychology, where she contributed to the COSIMA research group funded by the German Research Foundation (DFG). Since 2024 she is an Assistant Professor (Akademische R?tin auf Zeit) at the University of Augsburg, Chair of Learning Analytics & Educational Data Mining, and a Fellow at the CIDER College for Interdisciplinary Educational Research, funded by the Leibniz Education Research Network (LERN) and the Jacobs Foundation.

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Forschungsschwerpunkte

  • Adaptive learning technologies
  • Simulation-based learning
  • Learning analytics
  • AI in education
  • Reasoning and argumentation?

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Lehrveranstaltungen

(Angewandte Filter: Semester: aktuelles | Dozenten: Elisabeth Bauer | Vorlesungsarten: alle)
Name Semester Typ
Tutorium: Mixed Methods Wintersemester 2024/25 Tutorium
Tutorium: Measurement and assessment methods Wintersemester 2024/25 Tutorium
Psychologie II für Lehramtsstudierende - Bedingungen von Lehr-Lernprozessen Wintersemester 2024/25 Vorlesung
Learning by Design: Simulationen für das Lehramtsstudium Wintersemester 2024/25 Seminar
Measurement and assessment methods Wintersemester 2024/25 Seminar
Mixed Methods Wintersemester 2024/25 Seminar

Publikationen

2025 | 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018

2025
Bauer, Elisabeth, Sailer, Michael, Niklas, Frank, Greiff, Samuel, Sarbu‐Rothsching, Sven, Zottmann, Jan M., Kiesewetter, Jan, Stadler, Matthias, Fischer, Martin R., Seidel, Tina, Urhahne, Detlef, Sailer, Maximilian, & Fischer, Frank (2025). AI‐based adaptive feedback in simulations for teacher education: an experimental replication in the field. Journal of Computer Assisted Learning, 41(1), e13123. https://doi.org/10.1111/jcal.13123
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2024
Nickl, Michael, Sommerhoff, Daniel, Radkowitsch, Anika, Huber, Sina A., Bauer, Elisabeth, Ufer, Stefan, Plass, Jan L., & Seidel, Tina (2024). Effects of real-time adaptivity of scaffolding: supporting pre-service mathematics teachers' assessment skills in simulations. Learning and Instruction, 94, 101994. https://doi.org/10.1016/j.learninstruc.2024.101994
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Bauer, Elisabeth, Sailer, Michael, Kiesewetter, Jan, Fischer, Martin R., Gurevych, Iryna, & Fischer, Frank (2024). Facilitating justification, disconfirmation, and transparency in?diagnostic argumentation: effects of automatic adaptive feedback in teacher education. Zeitschrift für P?dagogische Psychologie, 38(1-2), 49-54. https://doi.org/10.1024/1010-0652/a000363
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Bichler, Sarah, Sailer, Michael, Bauer, Elisabeth, Kiesewetter, Jan, H?rtl, Hanna, Fischer, Martin R., & Fischer, Frank (2024). Promoting diagnostic reasoning in teacher education: the role of case format and perceived authenticity. European Journal of Psychology of Education, 39, 3227-3252. https://doi.org/10.1007/s10212-024-00874-x
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Sailer, Michael, Ninaus, Manuel, Huber, Stefan E., Bauer, Elisabeth, & Greiff, Samuel (2024). The end is the beginning is the end: the closed-loop learning analytics framework. Computers in Human Behavior, 158, 108305. https://doi.org/10.1016/j.chb.2024.108305
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Kosel, Christian, Bauer, Elisabeth, & Seidel, Tina (2024). Where experience makes a difference: teachers' judgment accuracy and diagnostic reasoning regarding student learning characteristics. Frontiers in Psychology, 15, 1278472. https://doi.org/10.3389/fpsyg.2024.1278472
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2023
Sailer, Michael, Bauer, Elisabeth, Hofmann, Riikka, Kiesewetter, Jan, Glas, Julia, Gurevych, Iryna, & Fischer, Frank (2023). Adaptive feedback from artificial neural networks facilitates pre-service teachers' diagnostic reasoning in simulation-based learning. Learning and Instruction, 83, 101620. https://doi.org/10.1016/j.learninstruc.2022.101620
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Greisel, Martin, Bauer, Elisabeth, Kuznetsov, Ilia, Berndt, Markus, Dresel, Markus, Fischer, Martin R., Kollar, Ingo, & Fischer, Frank (2023). How to use theory to implement natural language processing for peer-feedback. C. Dams?a, M. Borge, E. Koh, M. Worsley (Eds.), Proceedings of the 16th International Conference on Computer-Supported Collaborative Learning - CSCL 2023, June 10–15, 2023, Montréal, QC, Canada(pp. 237-240). Montréal: International Society of the Learning Sciences (ISLS). https://doi.org/10.22318/cscl2023.108887
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Bauer, Elisabeth, Greisel, Martin, Kuznetsov, Ilia, Berndt, Markus, Kollar, Ingo, Dresel, Markus, Fischer, Martin R., & Fischer, Frank (2023). Using natural language processing to support peer‐feedback in the age of artificial intelligence: a cross‐disciplinary framework and a research agenda. British Journal of Educational Technology, 54(5), 1222-1245. https://doi.org/10.1111/bjet.13336
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2022
Bauer, Elisabeth, Sailer, Michael, Kiesewetter, Jan, Fischer, Martin R., & Fischer, Frank (2022). Diagnostic argumentation in teacher education: making the case for justification, disconfirmation, and transparency. Frontiers in Education, 7, 977631. https://doi.org/10.3389/feduc.2022.977631
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Kiesewetter, Jan, Hege, Inga, Sailer, Michael, Bauer, Elisabeth, Schulz, Claudia, Platz, Manfred, & Adler, Martin (2022). Implementing remote collaboration in a virtual patient platform: usability study. JMIR Medical Education, 8(3), e24306. https://doi.org/10.2196/24306
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Bauer, Elisabeth, Sailer, Michael, Kiesewetter, Jan, Schulz, Claudia, Gurevych, Iryna, Fischer, Martin R., & Fischer, Frank (2022). Learning to diagnose students' behavioral, developmental, and learning disorders in a simulation-based learning environment for pre-service teachers. In Frank Fischer & Ansgar Opitz (Eds.), Learning to diagnose with simulations: examples from teacher education and medical education (pp. 97-107). Cham: Springer. https://doi.org/10.1007/978-3-030-89147-3_8
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Fischer, Frank, Bauer, Elisabeth, Seidel, Tina, Schmidmaier, Ralf, Radkowitsch, Anika, Neuhaus, Birgit J., Hofer, Sarah I., Sommerhoff, Daniel, Ufer, Stefan, Kuhn, Jochen, Küchemann, Stefan, Sailer, Michael, Koenen, Jenna, Gartmeier, Martin, Berberat, Pascal, Frenzel, Anne, Heitzmann, Nicole, Holzberger, Doris, Pfeffer, Jürgen, Lewalter, Doris, Niklas, Frank, Schmidt-Hertha, Bernhard, Gollwitzer, Mario, Vorholzer, Andreas, Chernikova, Olga, Schons, Christian, Pickal, Amadeus J., Bannert, Maria, Michaeli, Tilman, Stadler, Matthias, & Fischer, Martin R. (2022). Representational scaffolding in digital simulations – learning professional practices in higher education. Information and Learning Sciences, 123(11/12), 645-665. https://doi.org/10.1108/ils-06-2022-0076
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Bauer, Elisabeth, Heitzmann, Nicole, & Fischer, Frank (2022). Simulation-based learning in higher education and professional training: approximations of practice through representational scaffolding. Studies in Educational Evaluation, 75, 101213. https://doi.org/10.1016/j.stueduc.2022.101213
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2021
Bauer, Elisabeth, Sailer, Michael, Kiesewetter, Jan, Fischer, Martin R., & Fischer, Frank (2021). Pre-service teachers' argumentations in the context of assessment. E. de Vries, Y. Hod, J. Ahn (Eds.), Proceedings of the 15th International Conference of the Learning Sciences - ICLS 2021, Bochum, Germany, June 8-11, 2021(pp. 669-672). International Society of the Learning Sciences.
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Fink, Maximilian C., Radkowitsch, Anika, Bauer, Elisabeth, Sailer, Michael, Kiesewetter, Jan, Schmidmaier, Ralf, Siebeck, Matthias, Fischer, Frank, & Fischer, Martin R. (2021). Simulation research and design: a dual-level framework for multi-project research programs. Educational Technology Research and Development, 69(2), 809-841. https://doi.org/10.1007/s11423-020-09876-0
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2020
Bauer, Elisabeth, Fischer, Frank, Kiesewetter, Jan, Williamson Shaffer, David, Fischer, Martin R., Zottmann, Jan M., & Sailer, Michael (2020). Diagnostic activities and diagnostic practices in medical education and teacher education: an interdisciplinary comparison. Frontiers in Psychology, 11, 562665. https://doi.org/10.3389/fpsyg.2020.562665
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Kiesewetter, Jan, Sailer, Michael, Jung, Valentina M., Sch?nberger, Regina, Bauer, Elisabeth, Zottmann, Jan M., Hege, Inga, Zimmermann, Hanna, Fischer, Frank, & Fischer, Martin R. (2020). Learning clinical reasoning: how virtual patient case format and prior knowledge interact. BMC Medical Education, 20(1), 73. https://doi.org/10.1186/s12909-020-1987-y
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Bauer, Elisabeth, Sailer, Michael, Kiesewetter, Jan, Williamson Shaffer, David, Schulz, Claudia, Pfeiffer, Jonas, Gurevych, Iryna, Fischer, Martin R., & Fischer, Frank (2020). Pre-service teachers' diagnostic argumentation: what is the role of conceptual knowledge and cross-domain epistemic activities?. M. Gresalfi, I. S. Horn (Eds.), The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020, June 19-23, 2020, Nashville, Tennessee, USA, volume 4(pp. 2399-2400). International Society of the Learning Sciences.
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2019
Schulz, Claudia, Meyer, Christian M., Kiesewetter, Jan, Sailer, Michael, Bauer, Elisabeth, Fischer, Martin R., Fischer, Frank, & Gurevych, Iryna (2019). Analysis of automatic annotation suggestions for hard discourse-level tasks in expert domains. Anna Korhonen, David Traum, Lluís Màrquez (Eds.), Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, July 28 - August, 2019, Florence, Italy(pp. 2761-2772). Stroudsburg, PA: Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/P19-1265
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Pfeiffer, Jonas, Meyer, Christian M., Schulz, Claudia, Kiesewetter, Jan, Zottmann, Jan, Sailer, Michael, Bauer, Elisabeth, Fischer, Frank, Fischer, Martin R., & Gurevych, Iryna (2019). FAMULUS: interactive annotation and feedback generation for teaching diagnostic reasoning. Sebastian Padó, Ruihong Huang (Eds.), Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations, November 3–7, 2019, Hong Kong, China(pp. 73-78). Stroudsburg, PA: Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/D19-3013
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Bauer, Elisabeth, Sailer, Michael, Kiesewetter, Jan, Schulz, Claudia, Pfeiffer, Jonas, Gurevych, Iryna, Fischer, Martin R., & Fischer, Frank (2019). Using ENA to analyze pre-service teachers' diagnostic argumentations: a conceptual framework and initial applications. Brendan Eagan, Morten Misfeldt, Amanda Siebert-Evenstone (Eds.), Advances in quantitative ethnography: First International Conference, ICQE 2019, Madison, WI, USA, October 20–22, 2019, Proceedings(pp. 14-25). Cham: Springer. https://doi.org/10.1007/978-3-030-33232-7_2
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2018
Schulz, Claudia, Sailer, Michael, Kiesewetter, Jan, Bauer, Elisabeth, Fischer, Frank, Fischer, Martin R., & Gurevych, Iryna (2018). Automatic recommendations for data coding: a use case from medical and teacher education. Wilco Hazeleger, Adri?nne Mendrik, Ben van Werkhoven, Rob van Nieuwpoort, Raül Sirvent Pardell (Eds.), 2018 IEEE 14th International Conference on e-Science (e-Science), 29 October - 1 November 2018, Amsterdam, Netherlands(pp. 364-365). Piscataway, NJ: IEEE. https://doi.org/10.1109/escience.2018.00100
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Schulz, Claudia, Meyer, Christian M., Sailer, Michael, Kiesewetter, Jan, Bauer, Elisabeth, Fischer, Frank, Fischer, Martin R., & Gurevych, Iryna (2018). Challenges in the automatic analysis of students' diagnostic reasoning. preprint. https://doi.org/10.48550/arXiv.1811.10550
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欧洲冠军联赛_欧冠冠军足彩￥app在线投注