Sequential Observational Methods

Roger Bakeman and Augusto Gnisci

Observational methods are about measurement. Like most of the assessment methods described in other chapters in this section, they provide ways to extract scores from behavior. Thus observational methods, in common with assessment methods generally, are defined by procedures that when applied to events produce scores. Such scores are usually refined and reduced and then, often in combination with scores from other sources (thus becoming multimethod), are subjected to the sorts of statistical analyses described in the next section of this volume.

This volume urges readers to take a multi-method perspective. This chapter is much narrower. Here, a particular approach to measurement is presented, systematic observation of behavior, with a particular emphasis on capturing sequential aspects of the observed behavior. This is hardly the only approach to measurement, nor do the methods we emphasize here even exhaust the domain of observational methods understood broadly. Our intent in writing this chapter was to describe a particular approach, revealing its promises and pitfalls with sufficient specificity so that investigators could judge when it might prove useful. Thus we hope to contribute to a multimethod perspective, not so much directly, but indirectly. We think that sequential observational methods often capture aspects of behavior that other approaches do not and thus have much to contribute when used in combination with other approaches as investigators develop their own unique multimethod strategies.

If observational refers to methods for measuring behavior, what distinguishes them from other measurement approaches such as self-assessment questionnaires, peer ratings, standardized tests, physiological recording, and the like? For what kinds of circumstances and what sorts of research questions are they recommended? What kinds of researchers have found them useful? In an attempt to address these questions, we consider five topics in turn. First, we discuss defining characteristics of observational methods generally along with their advantages and disadvantages; second, ways of recording observational data; third, methods of representing observational data for computer analysis; fourth, the reliability of observational data; and finally, data reduction and analytic approaches that let us answer the questions that motivated our research in the first place. Throughout, concrete examples are used to illustrate specific points.

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