Learning Progression Analytics, Uncertainty, Research Methods
Prof. Dr. Marcus Kubsch
Physics Education Research
My work focuses on three main areas: Learning Progression Analytics, uncertainty & research methods.
Learning Progression Analytics
Learning Progression Analytics is a developing area of work where we use artificial intelligence techniques such as machine learning and natural language processing to build the basis for scaling personalized learning for all learners.
Uncertainty is everywhere is science and developing an adequate understanding of it is challenging. In this area we work on better understanding how people can learn about uncertainty effectively.
Learning about physics and science more generally is complex. Doing research about this is also complex and demands the deliberate, careful use of research methods. I’m particularly interested in overcoming the devide between qualitative and quantitative methods using using methodologies inspired by distributed cognition and network epistemologies such as computational grounded theory (CTG).More information will follow soon.
- dahlem school of education
- marcus kubsch
- physics education
- physics teacher
- teacher training