My research involves information retrieval, human-computer interaction, interactive information retrieval, and search as learning. I am interested in better understanding and supporting user learning during search. My research investigates the ways cognitive complexity and knowledge type affect learning. I am also interested in how users subdivide learning objectives throughout a search session.
Ph.D. Student, Information Science, University of North Carolina at Chapel Hill,
anticipated completion date: 2022
Ph.D. Advisors: Dr. Jaime Arguello and Dr. Rob Capra
B.A., University of California, Santa Cruz, 2007
Urgo, K., Arguello, J., & Capra, R. (Forthcoming) “The Effects of Learning Objectives on Searchers’ Perceptions and Behaviors.” Proceedings of the 6th ACM SIGIR International Conference on the Theory of Information Retrieval. 2020.
Urgo, Kelsey. “Anderson and Krathwohl’s Two-Dimensional Taxonomy Applied to Supporting and Predicting Learning During Search.” Proceedings of the 2020 Conference on Human Information Interaction and Retrieval. ACM, 2020. doi:10.1145/3343413.3377947
Urgo, Kelsey, Jaime Arguello, and Rob Capra. “Anderson and Krathwohl’s Two-Dimensional Taxonomy Applied to Task Creation and Learning Assessment.” Proceedings of the 5th ACM SIGIR International Conference on the Theory of Information Retrieval. 2019. doi:10.1145/3341981.3344226
Krishnamurthy, A., et al. “xDCI, a Data Science Cyberinfrastructure for Interdisciplinary Research.” 2017 IEEE High Performance Extreme Computing Conference (HPEC), 2017, pp. 1–7. IEEE Xplore, doi:10.1109/HPEC.2017.8091022.
Presentations & Posters
Urgo, Kelsey (Forthcoming). “Anderson and Krathwohl’s Two-Dimensional Taxonomy Applied to Supporting and Predicting Learning During Search.” Doctoral consortium proposal to be presented at the Conference on Human Information Interaction and Retrieval in Vancouver, British Columbia, Canada.
Urgo, Kelsey (2019). “Anderson and Krathwohl’s Two-Dimensional Taxonomy Applied to Task Creation and Learning Assessment.” Paper presented at the International Conference on the Theory of Information Retrieval in Santa Clara, California.
Urgo, Kelsey (2009). “Effects of Video Modeling on Peer Advocacy by Child with Autism.” Poster session at the Association for Behavior Analysis International Annual Convention in Phoenix, Arizona.
Association for Computing Machinery’s Special Interest Group on Information Retrieval (SIGIR)
Research Assistant, Interactive Information Systems Lab, University of North Carolina at Chapel Hill, 2018 – Present
Research assistant in the Interactive Information Systems Lab working for Dr. Jaime Arguello and Dr. Rob Capra.
Developer for Digital Scholarship, Wake Forest University, September 2017 – August 2018
Webmaster, Renaissance Computing Institute, University of North Carolina, Chapel Hill, November 2016 – August 2017
Digital Producer, Alloy Design + Development, June 2016 – October 2016
Communications Web Assistant, Southern Arkansas University, August 2015 – May 2016
Graduate Assistant, Southern Arkansas University, September 2014 – July 2015
- Graduate coursework topics include regression models, linear algebra, text mining, data mining and machine learning.
- Statistics applied in research include regression models, ANOVA models, multilevel models, principal component analysis (PCA), and exploratory factor analysis.
- Intermediate knowledge of R statistical language.
Courses taken in machine learning, data mining, linear algebra, statistics, topology, abstract algebra, and text mining.