John M. Aiken
John M. Aiken
University of Oslo
Verified email at - Homepage
Cited by
Cited by
Understanding student computational thinking with computational modeling
JM Aiken, MD Caballero, SS Douglas, JB Burk, EM Scanlon, BD Thoms, ...
AIP Conference Proceedings 1513 (1), 46-49, 2013
Exploring physics students’ engagement with online instructional videos in an introductory mechanics course
SY Lin, JM Aiken, DT Seaton, SS Douglas, EF Greco, BD Thoms, ...
Physical Review Physics Education Research 13 (2), 020138, 2017
Alternative model for administration and analysis of research-based assessments
BR Wilcox, BM Zwickl, RD Hobbs, JM Aiken, NM Welch, HJ Lewandowski
Physical Review Physics Education Research 12 (1), 010139, 2016
The initial state of students taking an introductory physics mooc
JM Aiken, SY Lin, SS Douglas, EF Greco, BD Thoms, MF Schatz, ...
arXiv preprint arXiv:1307.2533, 2013
Integrating numerical computation into the modeling instruction curriculum
MD Caballero, JB Burk, JM Aiken, BD Thoms, SS Douglas, EM Scanlon, ...
The Physics Teacher 52 (1), 38-42, 2014
Do-it-yourself whiteboard-style physics video lectures
SS Douglas, JM Aiken, E Greco, M Schatz, SY Lin
The Physics Teacher 55 (1), 22-24, 2017
Student use of a single lecture video in a flipped introductory mechanics course
JM Aiken, SY Lin, SS Douglas, EF Greco, BD Thoms, MD Caballero, ...
arXiv preprint arXiv:1407.2620, 2014
Modeling student pathways in a physics bachelor’s degree program
JM Aiken, R Henderson, MD Caballero
Physical Review Physics Education Research 15 (1), 010128, 2019
Peer evaluation of video lab reports in an introductory physics MOOC
SY Lin, SS Douglas, JM Aiken, CL Liu, EF Greco, BD Thoms, ...
arXiv preprint arXiv:1407.4714, 2014
A Python Library for Teaching Computation to Seismology Students
JM Aiken, C Aiken, F Cotton
Seismological Research Letters, 2018
Identifying features predictive of faculty integrating computation into physics courses
NT Young, G Allen, JM Aiken, R Henderson, MD Caballero
Physical Review Physics Education Research 15 (1), 010114, 2019
Predicting the proximity to macroscopic failure using local strain populations from dynamic in situ X-ray tomography triaxial compression experiments on rocks
J McBeck, JM Aiken, Y Ben-Zion, F Renard
Earth and Planetary Science Letters 543, 116344, 2020
Peer evaluation of video lab reports in a blended introductory physics course
SS Douglas, SY Lin, JM Aiken, BD Thoms, EF Greco, MD Caballero, ...
arXiv preprint arXiv:1407.3248, 2014
Transforming high school physics with modeling and computation
JM Aiken
arXiv preprint arXiv:1310.3725, 2013
Examining the relationship between student performance and video interactions
R Solli, JM Aiken, R Henderson, MD Caballero
Physics Education Research Conference Proceedings 2018, 2018
Peer assessment of student-produced mechanics lab report videos
SS Douglas, JM Aiken, SY Lin, EF Greco, E Alicea-Mu˝oz, MF Schatz
Isolating the factors that govern fracture development in rocks throughout dynamic in situ X‐ray tomography experiments
J McBeck, N Kandula, JM Aiken, B Cordonnier, F Renard
Geophysical Research Letters 46 (20), 11127-11135, 2019
Two-phase study examining perspectives and use of quantitative methods in physics education research
AV Knaub, JM Aiken, L Ding
Physical Review Physics Education Research 15 (2), 020102, 2019
Predicting time to graduation at a large enrollment American university
JM Aiken, R De Bin, M Hjorth-Jensen, MD Caballero
arXiv preprint arXiv:2005.05104, 2020
Predicting the proximity to system-scale rupture using fracture networks
J McBeck, J Aiken, J Mathiesen, Y Ben-Zion, F Renard
EGU General Assembly Conference Abstracts, 3316, 2020
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