Operating from multiple literature bases in cognitive psychology, mathematics education, and theoretical and applied psychometrics, Schilling, Hill and their colleagues provide a systemic approach to studying the validity of scores of mathematical knowledge for teaching. This system encompasses an array of task formats and methodologies. The undertaking is both comprehensive and scientific as they propose three different types of validation-related assumptions and inferences (i.e., elemental, structural, and, ecological) for seven different categories of teachers' mathematical knowledge. Schilling and his colleagues emphasize the importance of considering issues related to academic development in their generalizations and conclusions summary, and it is clear in their specification and test of hierarchical linear models (HLM; Hill, Rowan, & Ball, 2005) that development issues are important in their agenda as they calculate IRT-based knowledge gain scores as outcomes. There may be additional theoretical considerations, other variables, and task development and scoring issues that may inform programs of research on the development of mathematical knowledge in teaching and its effectiveness. The author offers suggestions to complement comprehensive programs of research that may shed light on developmental trajectories.