Research Methods Course Focusing on Program Evaluation

CIRI Blog

Published: May 17, 2022 by Jennifer Sweeney

I’m excited to share a reflection on my section of INFO 285, Applied Research Methods: Evaluating Programs and Services with you all here.  I developed and started teaching this course at SJSU in 2018. Teaching this course has been one of the most fulfilling aspects of my work life so far.

Bear with me for a little background. In the late 1990’s I transitioned from career academic reference librarian to “library analyst” at UC Davis, a contract position charged with evaluating library operations.  This was a new position: there was no handbook, no manual, no list of duties beyond some general notions of conducting surveys, collecting other kinds of data, analyzing, and reporting out to campus administration.  “You pretty much get to invent this job” said my supervisor.  Well, I loved every minute of it.  In the years since, I’ve been a library evaluation and planning consultant doing strategic planning, organizational development, and grant program evaluation.  This course was designed to address some of the skills needed in this applied research niche.

I have several goals in the course:

  • To provide a solid foundation of social science research methodology
  • To connect evaluation concepts to LIS research in a focused and practical way
  • To introduce practical tools like logic models to provide the framework for evaluation research.

 

Course modules begin with an overview of social science research, then focus in on evaluation, and then deeper into evaluation in LIS.  Throughout the term, we read and discuss selected chapters of Earl Babbie’s Practice of Social Research for grounding in basic research concepts, and connect these concepts to LIS research literature.  Modules on data collection introduce typical activities such as experiments and quasi-experiments, surveys and interviews.  In addition to a qualitative coding exercise, a two-week statistics “boot camp” provides practice with descriptive statistics and hypothesis testing using Excel.  (I adapted a middle-school level statistics curriculum to help make the material more approachable for the math-averse. Dragons are involved.)

I use actual LSTA grant programs as the substrate for key learning experiences.  Students take on the role of program evaluator and use grant documents to construct a logic model, develop variable concepts and operational definitions, analyze actual survey data (already collected), and write a final narrative summary for funders and other stakeholders. 

It’s a challenging course, for certain. Students seem to appreciate the mix of practical with theoretical. It is a surface-level introduction to a lot of research vocabulary rather than a deep dive into a specific area, which I think gives students the ability to understand more of the literature.  Some students have been inspired to continue into a doctoral program as a result of the course, which is nice to hear! 

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