Signal, error, or bias? exploring the uses of scores from observation systems

Scores from observational measures of teaching have recently been put to many uses within school systems, including communicating a standard of practice and providing teacher feedback, identifying teachers for professional development, monitoring system equity, and making employment decisions. In each of these uses, observation scores are interpreted as representing some aspect of the enacted instruction or teachers’ capacity to enact instruction, as seen through the observation systems lens for understanding teaching quality. The quality of these interpretations, or the extent to which observation scores are composed of a signal that accurately reflects the interpretation, has important implications for the overall validity of uses of observation systems. Starting from an explicit conceptualization of instruction, this paper combines generalizability theory and hierarchical linear modelling approaches to decompose observation scores to explore the extent to which scores from observation systems are composed of signal, error, and bias across four different uses (i.e., teacher feedback, professional development, monitoring system equity, and employment decisions) of scores. We show that the quality of observation scores may depend more on what scores are interpreted as representing (i.e., the proposed use) than on the specific observation rubric being used. Further, we show that rater errors and biases are a major threat to any attempt to interpret observation scores as capturing the observation system’s understanding of teaching quality. We discuss implications for using scores from observation systems.