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Showing results 1-7 of 7

2020
1 Aiken, John Mark.
Understanding University Student Pathways Towards Graduation with Machine Learning and Institutional Data. : Det matematisk naturvitenskapelige fakultet 2020 152 p.
UiO Untitled
 
2019
2 Aiken, John Mark; Henderson, Rachel; Caballero, Marcos Daniel.
Modeling student pathways in a physics bachelor's degree program. Physical Review Physics Education Research 2019 ;Volume 15.(1) p. 1-17
UiO Untitled
 
3 Knaub, Alexis V; Aiken, John Mark; Ding, Lin.
Two-phase study examining perspectives and use of quantitative methods in physics education research. Physical Review Physics Education Research 2019 ;Volume 15.(2)
UiO Untitled
 
4 McBeck, Jessica Ann; Kandula, Neelima; Aiken, John Mark; Cordonnier, Benoit; Renard, Francois.
Isolating the factors that govern fracture development in rocks throughout dynamic in situ X-ray tomography experiments. Geophysical Research Letters 2019 ;Volume 46.(20) p. 11127-11135
UiO Untitled
 
5 Young, Nicholas; Allen, Grant; Aiken, John Mark; Henderson, Rachel; Caballero, Marcos Daniel.
Identifying features predictive of faculty integrating computation into physics courses. Physical Review Physics Education Research 2019 ;Volume 15.(1)
UiO Untitled
 
2018
6 Aiken, John Mark; Aiken, Chastity; Cotton, Fabrice.
A python library for teaching computation to seismology students. Seismological Research Letters 2018 ;Volume 89.(3) p. 1165-1171
UiO Untitled
 
2017
7 Lin, Shih-Yin; Aiken, John Mark; Seaton, Daniel T; Douglas, Scott; Greco, Edwin F; Thoms, Brian D; Schatz, Michael F.
Exploring physics students' engagement with online instructional videos in an introductory mechanics course. Physical Review Physics Education Research 2017 ;Volume 13.(2)
UiO Untitled