Postdocs
Dr. Simona Daguati studied mathematics at ETH Zurich and obtained her Master of Science ETH in 2017. She also completed the teaching diploma program in mathematics and became a certified teacher for advanced placement schools (EDK) in 2019. From 2018 to 2022, she worked on her dissertation project, in which she investigated the role of working memory for mathematical problem solving in advanced school mathematics. Among other things, she focused on students who do not (fully) translate their potential in terms of general reasoning abilities into mathematics achievement (under-achievers). In addition to various cognitive variables, in her dissertation project she also considered the mathematical self-concept of her study participants as well as their interest in mathematics.
In parallel to her dissertation project, Dr. Simona Daguati was part of the project team for a longitudinal study on mathematics learning at various advanced placement schools in Switzerland (TraM study). The research goals of the TraM study were, on the one hand, the systematic evaluation of cognitively activating teaching materials for the topics of mathematical functions as well as differential calculus. On the other hand, the TraM study aimed to investigate the learning transfer from mathematical functions to differential calculus and the learning transfer from mathematical functions to kinematics.
As part of the Future Learning Initiative at ETH Zurich, Dr. Simona Daguati and other team members developed several preparatory learning activities for learning linear algebra.
In a follow-up study to her dissertation project, Dr. Simona Daguati would like to investigate whether and to what extent various influencing factors affected the study participants' choice of their study field. In particular, she would like to investigate the question why students who have good prerequisites for studying a STEM subject may decide not to do so.
Dr. Peter Edelsbrunner graduated from Psychology in 2012 at the University of Graz, Austria, focusing on Differential Psychology and Research Methods. Since 2012 he has been working on his doctoral thesis project about scientific thinking in childhood. His research interests include the interplay of content knowledge development and the understanding of experimentation and science in childhood. Peter applies mixture modeling for yielding detailed depictions of knowledge development in childhood. He also combines qualitative and quantitative research methods. In a current project, he examines practices in the application and interpretation of multivariate methods such as Rasch modeling in research on learning and instruction. In June 2017 Peter became a Postdoc.
Research interests
- Mixture modeling in educational and developmental research
- Scientific thinking throughout the lifespan
- Complexity in concept learning
- Statistical and psychometric practices in educational and developmental research
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Dr. Sonja Peteranderl finished her Master of Science in Psychology at the University of Zurich in 2015. In 2019, she obtained the doctoral degree at ETH Zurich (topic: Experimentation Skills in Primary School Children). Her doctoral thesis investigated the ability to conduct empirical experiments in primary school age. She developed an effective Experimentation Skills Training as well as a valid and reliable Experimentation Skills Test that assesses multiple aspects of scientific reasoning. Another important part of her working life comprises sports. She is currently completing her DAS (Diploma of Advanced Studies) in sports psychology at the University of Bern and gives sports classes at the Academic Sports Association Zurich (ASVZ).
Her research interests are cognitive and motoric learning and development, mental training, and the beneficial impact of exercising on mental health and cognition.
Dr. Christian Thurn
Dr. Christian Thurn studied psychology at the University of Konstanz/Germany and the Università degli Studi di Padova/Italy and obtained a Master of Science in 2017. In his dissertation project at ETH Zurich from 2017 to 2021, he investigated the interplay of prior knowledge, learning opportunities, and intelligence in conceptual physics learning.
His research aims at a better understanding of the mental processes of conceptual learning. Central questions in his work concern the role of prior knowledge, intelligence, and their interaction, as well as the statistical modeling of conceptual learning. To address these questions he utilizes classroom studies, concept tests, reaction-time experiments, and concept mapping. These methods allow the investigation of conceptual learning from different perspectives, such as network analytic modeling.
In addition, he is interested in (mis-)conceptions of frequentist statistics, gender issues in STEM subjects, and statistical state-of-the-art methods.
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Dr. Adrian Zwyssig studied chemistry at ETH Zurich and completed his Master of Science in 2016. From 2018 to 2023, as part of his doctoral dissertation at ETH Zurich, he conducted research in the field of chemical education with the aim of diagnosing and promoting the understanding of chemical bonding among high school students and at the interface between high school and university.
He investigated the understanding of chemical bonding in several studies both at the high school level and before the start of a natural science program. In collaboration with the MINT Learning Center at ETH Zurich, he developed a teaching unit that focuses more on comparing and contrasting the different types of bonding. A quasi-experimental study showed the advantages of this method compared to conventional teaching methods in high schools.
In addition, he developed a preparatory course for newly enrolled ETH students in 2020 to deepen their understanding of chemical bonding before the start of their studies. Since then, he has been conducting the courses on behalf of the ETH Youth Academy with an increasing number of participants. In addition to his research work, he also teaches chemistry at the high school level.
His research interests include cognitively activating learning and teaching methods, didactic questions, as well as the understanding of concepts, mental models, and (mis)conceptions of learners in the field of chemistry.