Clayton State Digital Repository
The Clayton State Digital Repository (CSDR) collects, preserves, and shares scholarly research with its community of users. These contributions demonstrate the value placed on instruction and research as well as illustrate how the University’s mission is met across our campus community. The uploaded documents will be freely accessible online and will include faculty and student scholarship, electronic theses, open access journals, campus documents and publications, and more.
Recent Submissions
Item From Data to Decisions: Building a Culture of Assessment in a Law Library(2025-11-12)Learn how two law librarians are building a sustainable, data-informed assessment program to support strategic planning, outreach, and annual reporting. We'll share practical tools, visualization tips, and strategies for fostering a culture of assessment.Item Does it Count? Measuring the Library's Impact on Student Success(2025-11-13)This presentation will highlight the results of a longitudinal study that examines the relationship of library usage and student success to determine if students who use library services and resources are more successful academically than students who do not use the library. In addition, the quantitative data was paired with demographic data and qualitative data to identify the specific services and resources may have the most impact on students. Results were used to promote library services and resources to target populations and stakeholders, strengthen budget request justifications, and improve library services, resources, and spaces.Item Using count regression models to analyze library usage: A practical overview(2025-11-13)Counts are commonly collected to determine library usage and have some characteristics that violate assumptions of using linear regression models or statistical techniques to investigate relationships between variables. This presentation will provide an overview of count regression models, including what they are, how they differ from linear regression, and how they can be used to analyze library usage data. Criteria for how to compare statistical models to identify the best one to answer the question being investigated will also be presented.Item Multiple-Objective Optimization for Library Journal Portfolios - A Machine Learning Approach(2025-11-13)While cost/use is a traditional analysis tool for evaluating Library Resources, for journals we have a richer data set including local citation rates and local authorship rates. Adding additional variables create a multiple object optimization problem. This presentation explores a machine learning technique, genetic algorithms, to explore solutions to this problem.Item Analyzing the Impact of Library Affordability Programs: A Causal Inference Study(2025-11-12)Despite extensive empirical evidence demonstrating the positive impact of affordability initiatives on student learning outcomes, our library lacked internal analyses of our affordability programs and their effects on students. To bridge this gap, I developed a causal analysis to evaluate the impact of a library partnership with the School of Electrical and Computer Engineering on student grades. This session will explore the study design, data challenges, and results of the analysis.
Communities in Clayton State Digital Repository
Select a community to browse its collections.