Research Interests

My research involves information retrieval, human-computer interaction, human-centered AI, interactive information retrieval, and search as learning. I am interested in better understanding and supporting user learning during search. My research investigates measuring learning during search, how users subdivide learning objectives throughout a search session, and developing tools that support learning during search. I am particularly interested in how generative AI tools are used in the search as learning context. I explore ways in which generative AI tools can be used to support complex learning tasks, goal-setting, and self-regulated learning in the search as learning process.

Education

Ph.D., Information Science, University of North Carolina at Chapel Hill,
August 2023
Dissertation title: “Investigating the Influence of Subgoals on Learning During Search.” 2023, doi: 10.17615/2yzf-1s98
Ph.D. Advisor: Dr. Jaime Arguello

B.A., University of California, Santa Cruz, 2007

Publications

Urgo, Kelsey, and Jaime Arguello. “The Effects of Goal-setting on Learning Outcomes and Self-Regulated Learning Processes.” In Proceedings of the 2024 Conference on Human Information Interaction and Retrieval (CHIIR ’24). 2024, doi: 10.1145/3627508.3638348.

Urgo, Kelsey, and Jaime Arguello. “Goal-Setting in Support of Learning During Search: An Exploration of Learning Outcomes and Searcher Perceptions.” Information Processing & Management, vol. 60, no. 2, p. 103158, Mar. 2023, doi: 10.1016/j.ipm.2022.103158.

Urgo, Kelsey, and Jaime Arguello. “Capturing Self-Regulated Learning During Search.” 3rd International Workshop on Investigating Learning during Web Search co-located at SIGIR hybrid conference. 2022. kelseyurgo.com/wp-content/uploads/2023/05/UrgoIWILDS2022.pdf

Smith, Catherine, Kelsey Urgo, Jaime Arguello, and Robert Capra. “Learner, Assignment, and Domain: Contextualizing Search for Comprehension.” In ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR ’22). 2022. doi: 10.1145/3498366.3505819

Urgo, Kelsey, and Jaime Arguello. “Understanding the “Pathway” Towards a Searcher’s Learning Objective.” ACM Transactions on Information Systems (TOIS) 40.4 (2022): 1-42. doi: 10.1145/3495222

Urgo, Kelsey, and Jaime Arguello. “Learning assessments in search-as-learning: A survey of prior work and opportunities for future research.” Information Processing & Management 59.2 (2022): 102821. doi: 10.1016/j.ipm.2021.102821

Urgo, Kelsey, Jaime Arguello, and Robert Capra. “The Effects of Learning Objectives on Searchers’ Perceptions and Behaviors.” Proceedings of the 2020 ACM SIGIR on International Conference on Theory of Information Retrieval. 2020. doi: 10.1145/3409256.3409815

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. 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 (2024). “Exploring the Influence of Subgoals on Learning During Search.” Research presented at the Symposium on Information Interaction and Learning hybrid event virtual and in Chapel Hill, North Carolina.

Urgo, Kelsey (2024). “Search as Learning: Supporting Human Learning in Search Environments” Research presented at the University of San Francisco Computer Science Faculty Speaker Series in San Francisco, California.

Urgo, Kelsey (2024). “The Effects of Goal-setting on Learning Outcomes and Self-Regulated Learning Processes.” Paper presented at the Conference on Human Information Interaction and Retrieval (CHIIR ’24) in Sheffield, England.

Urgo, Kelsey (2022). “Capturing Self-Regulated Learning During Search.” Paper presented at the 3rd International Workshop on Investigating Learning during Web Search co-located at SIGIR hybrid conference (hybrid virtual).

Cole, A., & Urgo, K. (2021). Multi-method experience sampling in information behaviour research. In Proceedings of the Annual Conference of CAIS/Actes du congrès annuel de l’ACSI. doi: https://doi.org/10.29173/cais1187

Urgo, Kelsey (2020). “The Effects of Learning Objectives on Searchers’ Perceptions and Behaviors.” Paper presented at the International Conference on the Theory of Information Retrieval in Stavanger, Norway (virtual).

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.

Professional Memberships

Association for Computing Machinery’s Special Interest Group on Information Retrieval (SIGIR)

Research Experience

Assistant Professor, University of San Francisco, 2023 – present

Assistant professor conducting mixed-methods research in human-computer interaction and information retrieval investigating complex human learning in search environments and generative AI tools

• Quantitative and qualitative research methods (mixed-methods)
• Develop novel features and auxiliary tools aimed at enhancing human learning during search
• Implement and innovate on research methodology from across disciplines (e.g., learning sciences, cognitive science)
• Conduct in-person lab and Amazon Mechanical Turk-based studies

Research Assistant, Interactive Information Systems Lab, University of North Carolina at Chapel Hill, 2018 – 2023

Research assistant in the Interactive Information Systems Lab working with Dr. Jaime Arguello and Dr. Rob Capra.

• Quantitative and qualitative research methods (mixed-methods)
• Identify meaningful research questions from gaps in existing work and literature
• Research study design methods
• Conduct in-person lab and Amazon Mechanical Turk-based studies
• Excellent knowledge and demonstrated use of R statistical language and RStudio software for data analysis
• Multiple publications

Work Experience

Freelance Technical Designer and Writer, Renaissance Computing Institute, University of North Carolina, Chapel Hill, 2017 – 2023

Web Developer for Digital Scholarship, Wake Forest University, 2017 – 2018

Web Developer, Renaissance Computing Institute, University of North Carolina, Chapel Hill, 2016 – 2017

Communications Assistant Web Developer, Southern Arkansas University, 2015 – 2016

Graduate Assistant Web Developer, Southern Arkansas University, 2014 – 2015

Key Skills