Research

Computer Science Education

My research has four main threads: academic integrity, collaboration, student success, and tools and OER for CS Education.

Academic Integrity

Academic integrity is usually discussed in terms of stopping or deterring cheating. We are instead interested in positive ways to promote academic integrity, through course policies, classroom interactions, and building a sense of community. I have had multiple discussions with students in courses on the practices that would help foster an atmosphere of honesty; we have tested a few examples including flexible collaboration policies and relaxed late penalites.

Citations

Nathan Brunelle and John R. Hott. 2020. Ask Me Anything: Assessing Academic Dishonesty. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education (SIGCSE '20). Association for Computing Machinery, New York, NY, USA, 1375. https://doi.org/10.1145/3328778.3372658

Nathan Brunelle and John R. Hott. 2020. Fix the Course, Not the Student: Positive Approaches to Cultivating Academic Integrity (Birds of a Feather Session). In Proceedings of the 51st ACM Technical Symposium on Computer Science Education (SIGCSE '20). Association for Computing Machinery, New York, NY, USA, 1402. https://doi.org/10.1145/3328778.3372535

Collaboration

How do students collaborate? How can we foster healthy collaboration while maintaining academic integrity? We are looking to uncover how students collaborate if given freedom to choose and change their collaborators throughout the semester. We anticipate that this flexibility will help reduce cheating by promoting a sense of community. Our initial results, published in the 2021 SIGCSE Technical Symposium suggests that encouraging students to work in groups of 4-5 produces the best learning outcomes.

Citations

Xinyue Lin, James Connors, Chang Lim, and John R. Hott. 2021. How Do Students Collaborate? Analyzing Group Choice in a Collaborative Learning Environment. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (SIGCSE '21). Association for Computing Machinery, New York, NY, USA, 212–218. https://doi.org/10.1145/3408877.3432389

Student Success

Citations

Ryan Lenfant, Alice Wanner, John R. Hott, and Raymond Pettit. 2023. Project-Based and Assignment-Based Courses: A Study of Piazza Engagement and Gender in Online Courses. In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1 (ITiCSE 2023). Association for Computing Machinery, New York, NY, USA, 138–144. https://doi.org/10.1145/3587102.3588833

John R. Hott, Nada Basit, Ziyao Gao, Ella Truslow, and Nour Goulmamine. 2023. Providing a Choice of Time Trackers on Online Assessments. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2023). Association for Computing Machinery, New York, NY, USA, 715–721. https://doi.org/10.1145/3545945.3569776

Ella Truslow, Nour Goulmamine, John R. Hott, and Nada Basit. 2022. Analyzing Student Experience of Time Trackers on Assessments. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2 (SIGCSE 2022). Association for Computing Machinery, New York, NY, USA, 1113. https://doi.org/10.1145/3478432.3499121

Angela A. Siegel, Mark Zarb, Bedour Alshaigy, Jeremiah Blanchard, Tom Crick, Richard Glassey, John R. Hott, Celine Latulipe, Charles Riedesel, Mali Senapathi, Simon, and David Williams. 2022. Teaching through a Global Pandemic: Educational Landscapes Before, During and After COVID-19. In Proceedings of the 2021 Working Group Reports on Innovation and Technology in Computer Science Education (ITiCSE-WGR '21). Association for Computing Machinery, New York, NY, USA, 1–25. https://doi.org/10.1145/3502870.3506565

Angela A. Siegel, Mark Zarb, Bedour Alshaigy, Jeremiah Blanchard, Tom Crick, Richard Glassey, John R. Hott, Celine Latulipe, Charles Riedesel, Mali Senapathi, Simon, and David Williams. 2021. Educational Landscapes During and After COVID-19. In Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 2 (ITiCSE '21). Association for Computing Machinery, New York, NY, USA, 597–598. https://doi.org/10.1145/3456565.3461439

Adrian Thinnyun, Ryan Lenfant, Raymond Pettit, and John R. Hott. 2021. Gender and Engagement in CS Courses on Piazza. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (SIGCSE '21). Association for Computing Machinery, New York, NY, USA, 438–444. https://doi.org/10.1145/3408877.3432395

Tools and OER for CS Education

Citations

Emma Choi, Lisa Meng, and John Hott. 2021. Open Source Software Practices in CS2. In Proceedings of the 21st Koli Calling International Conference on Computing Education Research (Koli Calling '21). Association for Computing Machinery, New York, NY, USA, Article 18, 1–5. https://doi.org/10.1145/3488042.3488047

Jeremiah Blanchard, John R. Hott, Vincent Berry, Rebecca Carroll, Bob Edmison, Richard Glassey, Oscar Karnalim, Brian Plancher, and Seán Russell. 2022. Stop Reinventing the Wheel! Promoting Community Software in Computing Education. In Proceedings of the 2022 Working Group Reports on Innovation and Technology in Computer Science Education (ITiCSE-WGR '22). Association for Computing Machinery, New York, NY, USA, 261–292. https://doi.org/10.1145/3571785.3574129

Jeremiah Blanchard, John R. Hott, Vincent Berry, Rebecca Carroll, Bob Edmison, Richard Glassey, Oscar Karnalim, Brian Plancher, and Seán Russell. 2022. Leveraging Community Software in CS Education to Avoid Reinventing the Wheel. In Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education Vol. 2 (ITiCSE '22). Association for Computing Machinery, New York, NY, USA, 580–581. https://doi.org/10.1145/3502717.3532169

John R. Hott and Jeremiah Blanchard. 2022. Toward a Collaborative Open Source CS-focused Assessment Framework (Birds of a Feather Session). In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2 (SIGCSE 2022). Association for Computing Machinery, New York, NY, USA, 1194. https://doi.org/10.1145/3478432.3499199

John R. Hott, Derrick Stone, Nada Basit, and Daniel Graham. 2022. Meme Magic: Project in Sprints. ACM EngageCSEdu, Online. https://doi.org/10.1145/3519933

John R. Hott, Nada Basit, Raymond Pettit, and Derrick Stone. 2020. CS2 Graphical Photo Library Project. NCWIT EngageCSEdu, Online. https://www.engage-csedu.org/find-resources/cs2-graphical-photo-library-project

Briana Morrison, Michelle Craig, Mark Gondree, Rita Garcia, Chris Mayfield, Helen Hu, Tzu-Yi Chen, Mikey Goldweber, and John R. Hott. March 2021. EngageCSEdu: A Collection of Engaging Assignments. Sister session of the 52nd ACM Technical Symposium on Computing Science Education (SIGCSE), Online.

Evolving Networks

Network analysis, especially social network analytics, has become widespread due to the growing amount of linked data available. Many researchers have started to consider evolving networks, i.e. Time-Varying Graphs (TVGs), to begin to understand how these networks change over time. In this dissertation, we expand on current practice in three directions: we define a new concept of “node-identity class” to describe different “lenses” over an evolving network, we develop sampling methods to produce representative static graphs over a network as it evolves, and we utilize social network metrics to produce distributions characterizing the dynamics of the network’s evolution. By combining these different techniques, we uncover a change effect in metric value due to network activity across sampling methods and window sizes, and produce a differential measure D(G) that helps signal possibly significant network evolution. We evaluate these techniques on synthetically-generated datasets with prescribed dynamics to show their effectiveness at capturing and depicting those events. We then apply our techniques to analyze three real-world applications: the Nauvoo Marriage Project, consisting of an evolving Mormon marital network in mid-1800s Nauvoo, IL; the Social Networks and Archival Context Project’s historical social-document network; and an ArXiv co-authorship network. In each case, we were able to depict the network’s dynamics, highlight periods of network activity for further investigation, and guide domain-specific researchers to new insights. For the Nauvoo Marriage Project, through a comparison of the network across identity lenses, our metrics depicted an increased centrality under the patriarchal lens compared with that of the matriarchal lens. Indeed, the rapidity with which the patriarchal centrality “rebounds” suggests a desire of the Nauvoo community to form a strong patriarchal system.

Read more in my Dissertation

Digital Humanities and Computer Science Applications

Visualizations and Network Analysis of early Mormonism, with Kathleen Flake

Publications and Presentations

Samples and Research Code

Visualizations and Network Analysis with SNAC

Social Networks and Archival Context Project visualizations and analysis through the Institute for Advanced Technology in the Humanities and UVA Library.

Publications

Hott, J. R. March 2020. Using Temporal Network Analysis to Uncover Bias in Collections. code4lib, Pittsburgh, PA.
https://2020.code4lib.org/talks/Using-Temporal-Network-Analysis-to-Uncover-Bias-in-Collections

Hott, J. R., Martin, W. N., and Flake, K. 2018. Visualization of Complex Familial and Social Structures. Electronic Imaging, Burlingame, CA.

Hott, J. R., Martin, W. N., and Flake, K. 2016. Visualizing Dynamics of Complex Familial Structures (Poster). IEEE Information Visualization, Baltimore, MD.

Hott, J. R., Martin, W. N., and Flake, K. 2016. Identity Lenses in Analyzing Evolving Social Structures. Digital Humanities, Krakow, Poland.

Hott, J. R., Martin, W. N., and Flake, K. 2015. Visualizing and Analyzing Identity Classes in Evolving Social Structures. Chicago Colloquium on Digital Humanities and Computer Science, University of Chicago. Chicago, IL.

Hott, J. R., Martin, W. N., and Flake, K. 2015. Evolving Family Structures: Representation and Visualization. Family History Technology Workshop, Brigham Young University. Provo, UT.

Hott, J. R., Martin, W.N., et al. 2014. Evolving Social Structures: Networks with People as the Edges. Digital Humanities Forum, University of Kansas. Lawrence, KS. Best paper award.

Hott, J. R., Brunelle, N., Myers, J., Rassen, J. and shelat, a. 2012. KD-Tree Algorithm for Propensity Score Matching With Three or More Treatment Groups. Technical Report Series. Division of Pharmacoepidemiology And Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School. Boston, MA.

Noonan, R. E. and Hott, J. R. 2007. A course in software development. In Proceedings of the 38th SIGCSE Technical Symposium on Computer Science Education (Covington, Kentucky, USA, March 07 - 11, 2007). SIGCSE ‘07. ACM Press, New York, NY, 135-139.

Project Archive

k-point Matching using kd-trees and Voronoi diagrams

A Comparison of bug-finding tools

Interesting Course Projects