Ryan Bockmon
Assistant Teaching Professor at the Roux Institute at Northeastern University.
Bockmon teaches machine learning, data science, data mining, computer vision and introductory computing.
His research interests include computer science education, augmented reality, mixed reality, experimental design,
and instrument validation. Bockmon completed his PhD in Computer Science from the University of Nebraska – Lincoln
and his bachelor’s also in Computer Science from Montana State University.
When not teaching, he enjoys hiking, fishing, woodworking, gardening, and painting.
Contact
email: r.bockmon@northeastern.edu
Publications
- C. Harper, R. Bockmon and S. Cooper. 2023. Investigating Themes of Student-Generated Analogies. Proceedings of the ACM Conference on Global Computing Education Vol 1 (CompEd 23)
- A. Jain, R. Bockmon, C. Bourke and S. Cooper. 2023. Validating a Language-Independent CS1 LEarning Outcomes Assessment. Proceedings of the ACM Conference on Global Computing Education Vol 1 (CompEd 23)
- R. Bockmon and C. Bourke. 2023. Validation of the Placement Skill Inventory: A CS0/CS1 Placement Exam. Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. (SIGCSE 23)
- R. Bockmon and S. Cooper. 2022. What's Your Placebo? The dangers of participation bias. Communication of the ACM
- B. Gopal, R. Bockmon, S. Cooper and J Olmanson. 2022. The impact of POGIL-like learning on student understanding of software testing and DevOps: A qualitative study. 33rd Annual Workshop of the Psychology of Programming Interest Group (PPIG 2022)
- J. Parkinson, R. Bockmon, Q. Cutts, M. Liut, A. Petersen and S. Sorby. 2021. Practice report: six studies of spatial skills training in introductory computer science. ACM Inroads
- B. Gopal, S. Cooper, and R. Bockmon. 2021. Industry partners’ reflections on undergraduate software engineering students: An exploratory pilot qualitative study. 32st Annual Workshop of the Psychology of Programming Interest Group (PPIG 2021).
- B. Gopal, S. Cooper, J. Olmanson, and R. Bockmon. 2021. Student Difficulties in unit and integration testing: A qualitative study. 32st Annual Workshop of the Psychology of Programming Interest Group (PPIG 2021)
- Y. He, R. Bockmon, M. Modey, and S. Roscoe. 2020. Classification of cancer types based on gene expression dataIEEE International Conference on Bioinformatics and Biomedicine (BIBM)
- R. Bockmon, S. Cooper, J. Zhang, J. Gratch, and M. Dorodchi. 2020. Can Students’ spatial skills predict their programming abilities? Proceedings of ITiCSE
- R. Bockmon, S. Cooper, W. Koperski, J. Gratch, S. Sorby, and M. Dorodchi. 2020. A cs1 spatial skills intervention and the impact on introductory programming abilties. 51st ACM Technical Symposium on Computer Science Education (SIGCSE’20)
- R. Bockmon, S. Cooper, J. Gratch, and M. Dorodchi. 2020. Validating a CS attitudes instrument. 51st ACM Technical Symposium on Computer Science Education (SIGCSE’20)
- R. Bockmon, S. Cooper, J. Gratch, and M. Dorodchi. 2019. (Re)Validating Cognitive Introductory Computing Instruments. Proceedings of the 50th ACM Technical Symposium on Computer Science Education, 552–557.
Teaching
- Introduction to Programming for Data Science: (DS 5010)
- Computer Vision: (CS 6330)
- Data Mining: (CS 6220)
- Algorithms: (CS 5800)
- Stats and Applications: (RAIK 270H)
- Data and Models II: (RAIK 370H)
- Data and Models III: (RAIK 371H)
- CS I: Data Science Focused (CSCE 155:T)
- Joy and Beauty of Data (CSCI 108)
Work Experience
- Assistant Teaching Professor - Roux Institute at Northeastern University: August 2023 - Current
- Postdoc - Data Science, Jeffrey S. Raikes School of Computer Science and Management: August 2017 - May 2022
- Graduate Research Assistant, University of Nebraska - Lincoln: August 2017 - May 2022
- Data Scientist Intern - PhD, Lawrence Livermore National Laboratory: May 2017 - December 2017 and May 2018 - August 2018
- Course Assistant, Montana State University: July 2016 - August 2017
