HPE 609 Survey Design
Although self-report surveys (also known as questionnaires) are among the most common forms of data collection instruments employed by social and behavioral scientists, including HPE scientists, few researchers are fluent in the basic processes needed to design effective surveys that yield valid, reliable data. This course familiarizes students with the steps and procedures essential to developing, administering, and analyzing data from high-quality surveys. The course focuses primarily on learning and applying “best practices” of survey design, based on the existing empirical evidence. The course will examine research bearing on the following common questions:
• Should I use an existing survey or design my own?
• Should I use open-ended, ranking, or rating items?
• How many response options should I offer?
• Should I label every point in my response scale?
• How should I organize the items on my survey?
• Does the way I administer the survey influence the results?
• How do I use online survey software to collect data from participants?
• What type of response rate should I expect, and how do I calculate it?
• What are the initial data management and analysis steps after data has been collected?
• How do I know if my survey is yielding data that is reliable and valid?
• What are the common statistical techniques used to demonstrate the reliability and validity of the scales used in a survey?
• How do I report the findings of my survey design and development process?
• What survey-related information should I report in the methods section of a scientific paper?
In addition, the course covers a modest number of theories associated with survey design. These theories help inform the design process, particularly in the (numerous) areas where the existing research provides little guidance.