Educational interventions are often evaluated and compared on the basis of their impacts on test scores. Decades of research have produced two empirical regularities: interventions in later grades tend to have smaller effects than the same interventions in earlier grades, and the test score impacts of early educational interventions almost universally “fade out” over time. This paper explores whether these empirical regularities are an artifact of the common practice of rescaling test scores in terms of a student’s position in a widening distribution of knowledge. If a standard deviation in test scores in later grades translates into a larger difference in knowledge, an intervention’s effect on normalized test scores may fall even as its effect on knowledge does not. We evaluate this hypothesis by fitting a model of education production to correlations in test scores across grades and with college-going using both administrative and survey data. Our results imply that the variance in knowledge does indeed rise as children progress through school, but not enough for test score normalization to fully explain these empirical regularities.
As many states are slated to soon use scores derived from classroom observation instruments in high-stakes decisions, developers must cultivate methods for improving the functioning of these instruments. We show how multidimensional, multilevel item response theory models can yield information critical for improving the performance of observational instruments.
We extend this line of research by investigating teacher career and background characteristics, personal resources, and school and district resources that predict an array of instructional practices identified on a mathematics-specific observational instrument, MQI, and a general instrument, CLASS. To understand these relationships, we use correlation and regression analyses. For a subset of teachers for whom we have data from multiple school years, we exploit within-teacher, cross-year variation to examine the relationship between class composition and instructional quality that is not confounded with the sorting of "better" students to "better" teachers. We conclude that multiple teacher- and school-level characteristics--rather than a single factor--are related to teachers' classroom practices.
While research has generated substantial information regarding the characteristics of effective mathematics teachers and classrooms, scholars have rarely tested multiple aspects of teachers or teaching within a single study. Without testing multiple variables simultaneously, it is difficult to identify specific aspects of mathematics teachers and teaching that may be particularly impactful on student learning, and to understand the degree to which these characteristics are related to one another. This plenary draws on data from a three-year study measuring multiple components of teacher and teaching quality to investigate these issues.