Dr. David B Strohmetz

Experimenter effects, or the impact that an experimenter can independently have on a study’s outcome, is an important consideration in social and behavioral research. These effects can occur in two ways. Noninteractional experimenter effects involve study biases that do not directly impact participants’ actual behaviors. Examples include biases in the decisions an experimenter makes, such as choice of study stimuli, types of observations made, and data analysis strategies. Interactional experimenter biases arise through the interactions between the experimenter and the participant. Examples include the experimenter’s biosocial and psychosocial attributes which may affect a participant’s behavior independent of the study variables. Experimenter expectations can also bias a study’s outcome in favor of its hypotheses. The potential for experimenter effects emphasizes the importance of good study design, including the use of properly trained experimenters blind to the study’s hypotheses and transparency in one’s study decisions.

Editors’ Commentary
Designing a course to be engaging can be challenging, especially when the course in question is one that students often dread having to take and traditional sources of inspiration are limited, static, uneven in quality, or cost-prohibitive. In this chapter, authors David Strohmetz, Natalie Ciarocco, and Gary Lewandowski discuss the development of a website devoted to the sharing of openly-licensed and peer-reviewed strategies and demonstrations for teaching research methods and statistics. In doing so they demonstrate how individual faculty can marry the recognized resources and practices of their discipline, such as support from professional societies and peer review, with open licensing to be able to ‘take a little piece
of their world and improve it.’

‘Experimenter artifacts’ and ‘subject artifacts’ are uncontrolled systematic errors that can arise within the experimental situation. Experimenter artifacts can be classified as being noninteractional or interactional. Subject artifacts can result from demand characteristics within the experimental situation and from the motivations of the subjects themselves. While there are strategies for minimizing potential artifacts, experimenters must be mindful of ethical considerations.