Scientist

Katharina Fleig

Katharina Fleig

Portrait of Katharina Fleig

Katharina Fleig has been working as a research assistant and doctoral candidate at the IWM in the Multiple Representations lab since August 2020. In her dissertation project “The effects of AI-supported feedback in the context of adaptive learning systems”, she investigates the automatic diagnosis of learning as well as the adaptive reactions of the system based on it affect its acceptance. Her focus is on the question of how automatically generated feedback influences cognitive and metacognitive learning processes.

Main research topics:

  • Development of linguistic models for the automatic semantic analysis of open-ended text responses
  • Empirical investigation of the effects of adaptive feedback on learning outcomes and learning processe

Katharina Fleig

Schleichstr. 6

72072 Tübingen

Room 6.534

+49 7071 979-333k.fleig@iwm-tuebingen.de

Lab membership

Project

Projects with a current term and projects that have taken place in the last 5 years are shown.

Publications

 

Articles (peer-reviewed) | Research data

Articles (peer-reviewed)

  • Hoch, E., Fleig, K., & Scheiter, K. (2023). Can monitoring prompts help to reduce a confidence bias when learning with multimedia? Zeitschrift für Entwicklungspsychologie und Pädagogische Psychologie, 55(2-3), 77-90. https://doi.org/10.1026/0049-8637/a000279

    Open Access

Research data

To overview

Presentations und Conferences

Talks

  • Hoch, E., Fleig, K., & Scheiter, K. (2023, August 22–26). Monitoring in multimedia learning: Does monitoring one's learning process affect learning? 20th Biennial Conference of the European Association for Research on Learning and Instruction (EARLI). Thessaloniki, Greece. [Talk]
  • Fleig, K., Padó, U., Hoch, E., Lachner, A., & Scheiter, K. (2022, März 9-11). Evidenzbasierte Entwicklung eines KI-Systems. 9. Jahrestagung der Gesellschaft für Empirische Bildungsforschung (GEBF). Bamberg (virtuelle Konferenz). [Talk]
  • Hoch, E., Fleig, K., & Scheiter, K. (2022, August 29-31). Explicit monitoring increases learning time but not performance. European Association for Research on Learning and Instruction (EARLI). Special Interest Group (SIG) 2. Kiel. [Talk]

Poster presentations

To overview
  • Fleig, K., Hoch, E., Lachner, A., & Scheiter, K. (2024, April 11). The effects of AI-generated feedback in the context of adaptive learning systems. Closing Conference of the Human-Agent Interaction Network: Interactions with Language-Based AI. Leibniz-Institut für Wissensmedien, Tübingen. [Poster presentation]
  • Fleig, K., Hoch, E., Lachner, A., Padó, U., & Scheiter, K. (2022, März 30). Implementierung einer automatischen Auswertung offener Antwortformate. Jahrestagung Leibniz-Forschungsverbund Bildungspotenziale (LERN) (virtuelle Konferenz). Frankfurt am Main. [Poster Presentation]
  • Fleig, K., Hoch, E., Lachner, A., Padó, U., & Scheiter, K. (2022, April 27-29). NLP-based learner assessment for feedback generation. Retreat of the LEAD (Learning, Educational Achievement, and Life Course Development) Graduate School & Research Network. Untermarchtal. [Poster Presentation]
  • Fleig, K., Hoch, E., Lachner, A., Padó, U., & Scheiter, K. (2022, October 19-21). NLP-based learner assessment for feedback generation. Retreat of the LEAD (Learning, Educational Achievement, and Life Course Development) Graduate School & Research Network. Tübingen. [Poster Presentation]

Other conference contributions

To overview
  • Fleig, K., Padó, U., Hoch, E., Lachner, A., & Scheiter, K. (2022, August 29-31). Evidence-based implementation of automatic response assessment. European Association for Research on Learning and Instruction (EARLI). Special Interest Group (SIG) 2. Kiel. [Round Table]

CV