The IRDL Summer Research Workshop covers all of the stages of designing an effective library science research project with a social science focus: research ethics, developing effective research questions and objectives, operationalizing research, method selection (qualitative and quantitative), sampling, and logistical considerations. It also provides detailed instruction on how to collect and analyze both qualitative and quantitative data.

Illustrative examples and personal consultation will be provided throughout the workshop to exemplify principles that are covered. The workshop is comprised of lecture, containing numerous illustrative examples of concepts discussed, discussion, and group work with consultation from the instructors. Small group work will provide Scholars the opportunity to put into practice what they have learned and get feedback on their ideas from peers and course instructors. Two instructors will be available throughout the training, increasing the amount of time devoted to personalized instruction.

Course Objectives

At the end of this course, participants will be able to:

  • Construct an effective research question
  • Choose an appropriate research design for a library science study
  • Explain the conceptual logic behind various data collection approaches and describe the rationale for selection of specific methods
  • Identify appropriate sampling strategies for research projects
  • Use and apply common qualitative data collection methods
  • Assess and apply different qualitative data analysis options
  • Design and implement a survey
  • Understand survey data management
  • Explain various analytic options for surveys

An abbreviated list of course topics:

  • Basic types of research design
  • Qualitative data collection (Techniques and how to choose them based on the research question)
  • Reliability and validity
  • Sampling
  • In-depth interviews
  • Focus groups
  • Writing an analysis plan
  • Themes and codes
  • Creating a codebook
  • Research designs for survey research
  • Univariate analysis
  • Bivariate analysis
  • Mixed methods
  • Inferential statistics