Observation Oriented Modeling: Preparing Students for Research in the 21st century1:

Abstract Observation Oriented Modeling is an alternative to traditional methods of data conceptualization and analysis that challenges researchers to develop integrated, explanatory models of patterns of observations. The focus of research is thus shifted away from aggregate statistics, such as means, variances, and correlations, and is instead directed toward assessing the accuracy of judgments based on the observations in hand. In this paper a number of example data sets will be used to demonstrate how Observation Oriented Modeling can be taught to undergraduate and graduate students. While the examples are drawn from psychology, the method of contrasting Observation Oriented Modeling with traditional methods of research design and statistical analysis can easily be adapted to examples from other sciences.