Sampling participants’ experience in laboratory experiments: complementary challenges for more complete data collection

Sampling participants’ experience in laboratory experiments: complementary challenges for more complete data collectionSpeelman and McGann’s (2013) examination of the uncritical way in which the mean is often used in psychological research raises questions both about the average’s reliability and its validity. In the present paper, we argue that interrogating the validity of the mean involves, amongst other things, a better understanding of the person’s experiences, the meaning of their actions, at the time that the behavior of interest is carried out. Recently emerging approaches within Psychology and Cognitive Science have argued strongly that experience should play a more central role in our examination of behavioral data, but the relationship between experience and behavior remains very poorly understood. We outline some of the history of the science on this fraught relationship, as well as arguing that contemporary methods for studying experience fall into one of two categories. “Wide” approaches tend to incorporate naturalistic behavior settings, but sacrifice accuracy and reliability in behavioral measurement. “Narrow” approaches maintain controlled measurement of behavior, but involve too specific a sampling of experience, which obscures crucial temporal characteristics. We therefore argue for a novel, mid-range sampling technique, that extends Hurlburt’s descriptive experience sampling, and adapts it for the controlled setting of the laboratory. This controlled descriptive experience sampling may be an appropriate tool to help calibrate both the mean and the meaning of an experimental situation with one another.Ye