Research studies
The list below includes our research studies that are relevant to computer-based testing tools.
Computer-based testing and scheduling
C. Zilles, R. T. Deloatch, J. Bailey, B. B. Khattar, W. Fagen, C. Heeren, D. Mussulman, and M. West, Computerized testing: A vision and initial experiences, in Proceedings of the 122nd American Society for Engineering Education Annual Conference and Exposition (ASEE 2015), 26.387.1-26.387.13, 2015.
C. Zilles, M. West, and D. Mussulman, Student behavior in selecting an exam time in a computer-based testing facility, in Proceedings of the 123rd American Society for Engineering Education Annual Conference and Exposition (ASEE 2016), Paper ID #16655, 2016.
M. West and C. Zilles, Modeling student scheduling preferences in a computer-based testing facility, in Proceedings of the Third ACM Conference on Learning at Scale (L@S 2016), 309-312, 2016.
J. Bailey, M. West, and C. Zilles, Measuring revealed student scheduling preferences using constrained discrete choice models, in Proceedings of the 124th American Society for Engineering Education Annual Conference and Exposition (ASEE 2017), Paper ID #19940, 2017.
C. Zilles, M. West, D. Mussulman, and C. Sacris, Student and instructor experiences with a computer-based testing facility, in Proceedings of the 10th International Conference on Education and New Learning Technologies (EDULEARN18), 4441-4450, 2018.
C. Zilles, M. West, D. Mussulman, and T. Bretl, Making testing less trying: Lessons learned from operating a computer-based testing facility, in Proceedings of the 2018 Frontiers in Education Conference (FIE 2018), 2018.
T. Nip, E. Gunter, G. Herman, J. Morphew, M. West, Using a Computer-based Testing Facility to Improve Student Learning in a Programming Languages and Compilers Course, in Proceedings of ACM SIG on Computer Science Education (SIGCSE’18), 568-573, 2018.
C. Zilles, M. West, G. Herman, and T. Bretl, Every university should have a computer-based testing facility, in Proceedings of the 11th International Conference on Computer Supported Education (CSEDU 2019), 2019.
A. Verma, T. Bretl, M. West, and C. Zilles, A quantitative analysis of when students choose to grade questions on computerized exams with multiple attempts, in Proceedings of the Seventh ACM Conference on Learning at Scale (L@S 2020), 2020.
S. Poulsen, C. J. Anderson, and M. West, The relationship between course scheduling and student performance, in Proceedings of 4th Educational Data Mining in Computer Science Education Workshop (CSEDM 2020), 2020.
Mastery approach: repeated attempts with instant feedback
M. West, G. L. Herman, and C. Zilles, PrairieLearn: Mastery-based online problem solving with adaptive scoring and recommendations driven by machine learning, in Proceedings of the 122nd American Society for Engineering Education Annual Conference and Exposition (ASEE 2015), 26.1238.1-26.1238.14, 2015.
M. Silva and M. West, Algorithmic grading strategies for computerized drawing assessments, in Proceedings of the 124th American Society for Engineering Education Annual Conference and Exposition (ASEE 2017), Paper ID #19927, 2017.
N. Nytko, M. West, and M. Silva, A simple and efficient markup tool to generate drawing-based online assessments, in Proceedings of the 2020 American Society for Engineering Education Virtual Annual Conference (ASEE 2020), 2020.
P. Sud, M. West, and C. Zilles, Reducing difficulty variance in randomized assessments, in Proceedings of the 126th American Society for Engineering Education Annual Conference and Exposition (ASEE 2019), Paper ID #25513, 2019.
B. Chen, M. West, and C. Zilles, Predicting the difficulty of automatic item generators on exams from their difficulty on homeworks, in Proceedings of the Sixth Annual ACM Conference on Learning at Scale (L@S 2019), 2019.
Frequent testing and low-stake assessments
J. W. Morphew, M. Silva, G. Herman, and M. West, Frequent mastery testing with second‐chance exams leads to enhanced student learning in undergraduate engineering, Applied Cognitive Psychology 34(1), 168-181, 2020.
G. L. Herman, Z. Cai, T. Bretl, C. Zilles, and M. West, Comparison of grade replacement and weighted averages for second-chance exams, in Proceedings of the 2020 ACM Conference on International Computing Education Research (ICER 2020), 2020.
W. L. Chang, M. West, C. Zilles, D. Mussulman, and C. Sacris, Computerized exam reviews: In-person and individualized feedback to students after a computerized exam, in Proceedings of the 2020 American Society for Engineering Education Virtual Annual Conference (ASEE 2020), 2020.
Creating robust and randomized assessments to reduce cheating
B. Chen, M. West, and C. Zilles, Do performance trends suggest wide-spread collaborative cheating on asynchronous exams?, in Proceedings of the Fourth ACM Conference on Learning at Scale (L@S 2017), 2017.
B. Chen, M. West, and C. Zilles, How much randomization is needed to deter collaborative cheating on asynchronous exams?, in Proceedings of the Fifth Annual ACM Conference on Learning at Scale (L@S 2018), 62, 2018.
B. Chen, M. West, and C. Zilles, Analyzing the decline of student scores over time in self‐scheduled asynchronous exams, Journal of Engineering Education 108(4), 574-594, 2019.
B. Chen, S. Azad, M. Fowler, M. West, and C. Zilles, Learning to cheat: Quantifying changes in score advantage of unproctored assessments over time, in Proceedings of the Seventh ACM Conference on Learning at Scale (L@S 2020), 2020.
M. Silva, M. West, and C. Zilles, Measuring the score advantage on asynchronous exams in an undergraduate CS course, in Proceedings of the 51st ACM Technical Symposium on Computer Science Education (SIGCSE 2020), 2020.
Autograding of open-ended question
B. Chen, S. Azad, R. Haldar, M. West, and C. Zilles, A validated scoring rubric for Explain-in-Plain-English questions, in Proceedings of the 51st ACM Technical Symposium on Computer Science Education (SIGCSE 2020), 2020.
M. Fowler, B. Chen, S. Azad, M. West, and C. Zilles, Autograding "Explain in Plain English" questions using NLP, in Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (SIGCSE 2021), 2021.