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Bichler Sarah

Sarah Bichler, PhD Learning Sciences

International Doctoral School "Scientific Reasoning and Argumentation"

Further Information

Current affiliation

  • Graduate School of Education United States, University of California, Berkeley

PhD Thesis 

  • Topic: The role of executive functions and Inquiry Based Learning for Scientific Reasoning and Argumentation

Coming up with a good research question, testable hypotheses, appropriate research designs, and considering statistical assumptions to apply statistical methods correctly is complex and the foundation on which scientific knowledge is generated. I am interested in how we best support learners to understand scientific concepts so that they become successful problem solvers who are able to apply their knowledge and engage in scientific practices. 

In one of my studies, we ask: Are learners supported with worked examples better in applying their knowledge about research methods and statistics to specific problems than learners who problem-solve? In two studies we investigate this question further by including learning process data and analyse learners’ self-explanations. We ask: Are self-explanations a mediator of the worked example effect? Another study is set in the context of inquiry-based learning about Global Climate Change. Here learners use scientific methods to understand natural phenomena and we investigate how a modeling video and a generation activity support learning from dynamic visualizations.

Overarching my interest in how scientific reasoning and argumentation can be fostered, is my interest to learn about the underlying cognitive processes of learning. We investigate executive functions (working memory capacity and shifting ability) and fluid intelligence. Understanding how individual learner differences on these cognitive learning prerequisites matter for the effectiveness of instructional support helps us to understand why support is effective and to design effective support.

  • Supervisory team: Prof. Dr. Frank Fischer (LMU), Prof. Dr. Birgit Neuhaus (LMU), Prof. Dr. Marcia Linn (University of Berkeley)
  • Graduation year: 2019

Incubator Stay

Publications

Peer Reviewed Journals

  • Bichler, S., Schwaighofer, M., Stadler, M., Bühner, M., Greiff, S., & Fischer, F. (manuscript in revision). How Working Memory Capacity and Shifting Matter for Learning with Worked Examples – A Replication Study. Journal of Educational Psychology.
  • Bichler, S., Stadler, M., Bühner, M., Greiff, S., & Fischer, F. (manuscript in preparation). Jointly investigating moderating and mediating factors in the context of worked examples (working title).
  • Bichler, S., & Fischer, F. (manuscript in preparation). The three-constituent model of instructionally supported learning: Moderating and mediating factors in the context of worked examples. A replication study (working title).

Conference Proceedings

  • Bichler, S., Richards, S., Hasenbein, L., Linn, M. C., & Fischer, F. (2019). Understanding Climate Change Through Collaborative Versus Individual Inquiry with Constructive or Example-Based Scaffolds. In K. Lund, G. P. Niccolai, E. Lavoué, C. Hmelo-Silver, G. Gweon, & M. Baker (Ed.), 13th International Conference on Computer Supported Collaborative Learning (CSCL) (Vol 2, pp. 668–671). Lyon, France.

Paper and Poster Presentations

  • Bichler, S., Stadler, M., Greiff, S., Bühner, M., & Fischer, F. (2019). Worked Examples and Problem-Solving: What is the Role of Self-Explanations. Paper presented at the paEpsy-Tagung: Variation: Noise or Norm?, Leipzig, Germany.
  • Bichler, S., Bachhuber, A. M., Goyal, H., Achtner, M., & Stadler, M. (2019). Complex Reasoning in Science: How do reasoning skills on domain-general and domain-specific tasks relate and predict science learning? Poster presented at the paEpsy-Tagung: Variation: Noise or Norm?, Leipzig, Germany.
  • Bichler, S., Richards, S., Hasenbein, L., Linn, M. C., & Fischer, F. (2019). Understanding Climate Change Through Constructive and Example-Based Scaffolds. Paper presented at the 18th Biennial Conference of the European Association for Research on Learning and Instruction (EARLI), Aachen, Germany.
  • Bichler, S., Stadler, M., Bühner, M., Greiff, S., & Fischer, F. (2019). Does Learner’s Shifting Ability Moderate the Worked Example Effect on Scientific Reasoning? A Replication Study. Poster presented at the American Educational Research Association (AERA) 2019 Annual Meeting: Leveraging Education Research in a Post-Truth Era: Multimodal Narratives to Democratize Evidence, Toronto, Canada.
  • Bichler, S., Richards, S., Hasenbein, L., Linn, M. C., & Fischer, F. (2019). Fostering the use of evidence from models in science learning: constructive and example-based scaffolding. Paper presented at REASON 3rd Interdisciplinary Winter School: Bridging the research-practice gap: Advancing evidence-based argumentation, Munich, Germany.
  • Bichler, S., Bühner, M., Greiff, S., & Fischer, F. (2018). Learning to Apply Statistics Knowledge: A Replication Study on the Role of Cognitive Functions. In C. Osterhaus (Chair), Reasoning with and about evidence: Contributions from developmental and educational psychology. Symposium conducted at the German Psychological Society (DGPs) Congress, Frankfurt, Germany.
  • Bichler, S., & Fischer, F. (2018). Learning with Worked Examples – Why Cognitive Prerequisites Matter. Poster presented at EARLI SIG 6/7 Meeting: Instructional Design and Technology for 21st Century Learning: Challenges, Solutions, and Future Directions, Bonn, Germany.
  • Bichler, S., Neuhaus, B., Linn, M. C., & Fischer, F. (2018). Explanations as Learning Mechanism in Learning to Apply Knowledge in Reasoning and Argumentation – A Process Analysis. Poster presented at REASON 2nd Interdisciplinary Spring School: Advances in measuring scientific reasoning and argumentation, Munich, Germany.
  • Bichler, S., Bühner, M., Greiff, S., & Fischer, F. (2018). Executive functions as moderators of the worked example effect on statistical reasoning – A replication study. Poster presented at INHERE 2018: Learning through inquiry in higher education – current research and future challenges, Munich, Germany.

Memberships

  • American Educational Research Association (AERA)
  • European Association for Research on Learning and Instruction (EARLI)
  • Deutsche Gesellschaft für Psychologie [German Psychological Association] (DGPs)