Weitere Ankündigungen und Neuigkeiten zur Arbeit dieser Juniorprofessur finden Sie hier.
Panel discussion about Experience Sampling Method studies
Two new research projects funded!
Assistant Professor Dr. Julia Moeller participates in two research projects about methods of data analysis both of which have recently been funded with 50 000 Canadian Dollars each (converted to approximately jeweils 33 847 €, totalling 67 694 €).
The projects are funded to equal parts by the Jacobs Foundation and CIFAR. Each project team includes method experts funded by either foundation.
We thank both foundations for this support and are looking forward to exciting research in both projects!
- Project 1: Using astronomical simulation techniques to assess temporal network methods for studying individual differences in learning (Adriene Beltz, University of Michigan, Jacobs Foundation Research Fellow, Renée Hložek, University of Toronto, CIFAR Azrieli Global Scholar, Gravity & the Extreme Universe Program, Julia Moeller, University of Leipzig, Jacobs Foundation Research Fellow, Kou Murayama, University of Tübingen, Jacobs Foundation Research Fellow, Allyson Mackey, University of Pennsylvania, Jacobs Foundation Research Fellow and CIFAR Azrieli Global Scholar, Child & Brain Development Program)
- Project 2: Leveraging the full potential of longitudinal data analysis: Cross-disciplinary workshop series (Kou Murayama, University of Tübingen, Jacobs Foundation Research Fellow, Catherine Lebel, University of Calgary, Jacobs Foundation Research Fellow, Julia Moeller, University of Leipzig, Jacobs Foundation Research Fellow, Drew Bailey, University of California, Irvine, Jacobs Foundation Research Fellow, Adeel Razi, Monash University, CIFAR Azrieli Global Scholar, Brain, Mind & Consciousness Program, Baobao Zhang, Syracuse University, CIFAR Azrieli Global Scholar, Innovation, Equity & the Future of Prosperity Program)
The ManyMoments project goes online!
The website of the ManyMoments project has been launched. The project aims to contribute to improving replicability and generalizability of research with the experience sampling method and other methods of intensive longitudinal data collection.
Intensiven longitudinal studies typically survey or observe participants with multiple repeated surveys or measurements. The ManyMoments project uses and promotes open science practices to improve the research using intensive longitudinal data. Please read more about the ManyMoments projects here.