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Umeå universitet
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Huvudmenyn dold.
Personalbild Marcus Kubsch

Marcus Kubsch

Jag vill förstå hur människor lär sig fysik och hur de kan stödjas. Jag intresserar mig särskilt för hur lärande navigerar osäkerhet och för hur AI förändrar forskning, undervisning och lärande.

Kontakt

E-post
marcus.kubsch@umu.se
Telefon
090-786 75 31

Verksam som

Anknytning
Universitetslektor vid Institutionen för naturvetenskapernas och matematikens didaktik
Plats
Naturvetarhuset, huskropp A, plan 5, Johan Bures väg 16 Umeå universitet, 901 87 Umeå
Investigating the analytical robustness of the social and behavioural sciences
Nature, Nature Publishing Group 2026, Vol. 652, (8108) : 135-142
Aczel, Balazs; Szaszi, Barnabas; Clelland, Harry T.; et al.
Self-regulated learning in the digitally enhanced science classroom: toward an early warning system
Educational psychology review, Springer 2025, Vol. 37, (2)
Kubsch, Marcus; Strauß, Sebastian; Grimm, Adrian; et al.
Adaptive, but equitable?: Exploring the impact of machine learning-based adaptive support on educational debts in undergraduate chemistry
Science Education, John Wiley & Sons 2025, Vol. 110, (3) : 928-946
Martin, Paul P.; Kubsch, Marcus; Yik, Brandon J.; et al.
What affects the continued learning about energy?: Evidence from a 4-year longitudinal study
Journal of Research in Science Teaching, John Wiley & Sons 2024, Vol. 61, (5) : 975-997
Kubsch, Marcus
Bias, bias everywhere: a response to Li et al. and Zhai and Nehm
Journal of Research in Science Teaching, John Wiley & Sons 2023, Vol. 60, (10) : 2395-2399
Krist, Christina; Kubsch, Marcus
The interplay between students' motivational profiles and science learning
Journal of Research in Science Teaching, Wiley 2023, Vol. 60, (1) : 3-25
Kubsch, Marcus; Fortus, David; Neumann, Knut; et al.
Distributing epistemic functions and tasks — A framework for augmenting human analytic power with machine learning in science education research
Journal of Research in Science Teaching, Wiley 2023, Vol. 60, (2) : 423-447
Kubsch, Marcus; Krist, Christina; Rosenberg, Joshua M.
Integrating artificial intelligence-based methods into qualitative research in physics education research: a case for computational grounded theory
Physical Review Physics Education Research, American Physical Society 2023, Vol. 19, (2)
Tschisgale, Paul; Wulff, Peter; Kubsch, Marcus
Accretion disk dynamics: alpha-viscosity in self-similar self-gravitating models
Astronomy and Astrophysics, EDP Sciences 2016, Vol. 588
Kubsch, Marcus; Illenseer, Tobias F.; Duschl, Wolfgang J.
Visa publikationer i DiVA