Paper: Program Description Abstract

Improvements to Assessment of Library-Led Doctoral Class Lead to Insights into Library Programming

Monday, May 6
4:35 PM - 4:50 PM
Room: Columbus AB (East Tower, Ballroom/Gold Level)

Background : Our health sciences library offers a required one-credit, research fundamentals class for first year PhD students. The class covers literature search, citation, data management, publication metrics, visualization, team science and data sharing. Because we are in the unique position of having a captive audience, we are able to conduct assessment deeper than typically possible in library workshops, presenting an opportunity to improve our educational offerings. This paper provides a case study exploring the history and evolution of assessment of a librarian-taught graduate level class and how we have come to improve over time to include both baseline and summative assessments.

Description : During the first two years of our class, we offered a final summative assessment that asked questions addressing topics covered in each of the 8 sessions of our class, as well as a questionnaire to understand attitudes about the class. This year in attempting to get a stronger sense of what was known by students coming into the workshop, we implemented a baseline questionnaire that offers multiple-choice and free text questions to assess what students come in knowing about course topics. The assessment was created in REDCap and administered on the first day of class after reading the syllabus. The experience of seeing what students know has led to improvements in our teaching to address these gaps within the class, as well as adjustments to general library workshops on similar topics.

Conclusion : The new baseline assessment already highlighted gaps in student knowledge entering the class, particularly in literature databases, data sharing, team science, and publication metrics, and these have informed how we have tailored the sessions. Moreover, data gleaned from formative and summative assessments highlight gaps in our teaching, allowing for improvements both in the context of the PhD class and general library workshops for the broader academic community. We expect that when the class is complete, analyzing improvements will highlight areas for improvement in our instruction as well as underscore difficult concepts for students.

Fred Willie Zametkin LaPolla

Research and Data Librarian
NYU Langone Health
New York, New York

Fred LaPolla is a Research and Data Librarian with NYU Health Sciences Library. He has a strong interest in data visualization and teaches workshops in tools including GraphPad Prism, Excel and R Studio. In addition to working with NYU HSL's Data Services Team, Fred is liaison to the departments of General Internal Medicine and Radiology. He earned his MLS at Queens College, CUNY.


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Kevin Read

Lead, Data Discovery and Data Services Librarian
NYU Health Sciences Library
New York, New York

Kevin Read, MLIS, MAS is the Lead of Data Discovery and Data Services Librarian at NYU Langone Health. He leads the NYU Data Catalog project; an initiative to make research datasets created and used by NYU researchers more discoverable. He also leads the Data Catalog Collaboration Project, a multi-site collaboration consisting of eight academic institutions working to improve the discoverability of institutional research data using the NYU Data Catalog model.

Beyond his data discovery efforts, Kevin provides training and research support to faculty, residents, students and staff on topics including: clinical research data management, REDCap, reproducibility, and data sharing.


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Nicole Contaxis

Data Catalog Coordinator
NYU Health Sciences Library
New York, New York

Nicole Contaxis, MLIS, is the NYU Data Catalog Coordinator at the NYU Health Sciences Library. She works alongside researchers to make research data discoverable. Her main responsibilities include planning and conducting outreach events, curating metadata in the catalog, and collaborating with other medical librarians through the Data Catalog Collaboration Project. Her areas of interest include data sharing, data ethics, and community engagement. She received her MLIS degree from UCLA and is currently pursuing an MA in Bioethics at NYU.


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Alisa Surkis

Assistant Director, Research Data and Metrics/Vice Chair for Research
NYU Health Sciences Library
New York, New York

Alisa Surkis, PhD, MLS is the Assistant Director for Research Data and Metrics and the Vice Chair for Research at the NYU Health Sciences Library. She serves as a co-Director for Team Science and leads the Workforce Data Capacity Core within the Biomedical Informatics Program for the NYU Clincical and Translational Science Institute. She is the Data Science Core Director for an NIH BRAIN Initiative funded project on Oxytocin Modulation of Neural Circuit Function and Behavior.


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Improvements to Assessment of Library-Led Doctoral Class Lead to Insights into Library Programming

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