A new entry in the testing lexicon is through-course summative assessment, a system consisting of components administered periodically during the academic year. As defined in the Race to the Top program, these assessments are intended to yield a yearly summative score for accountability purposes. They must provide for both individual and group proficiency estimates and allow for the measurement of growth. They must accommodate students who vary in their patterns of curricular exposure. Because they are meant to provide actionable information to teachers they must be instructionally sensitive, so item-operating characteristics can be expected to change relative to one another as a function of patterns of curricular exposure. This paper discusses methodology one can draw upon to tackle this ambitious collection of inferences. We consider a modeling framework that consists of an item response theory component and a population component, as in the National Assessment of Educational Progress, and show how performance and growth could be expressed in terms of expected performance on a market basket of tasks. We discuss conditions under which modeling simplifications might be possible and discuss studies that would be needed to fit models, estimate parameters, and evaluate data requirements.