Diagnostic science assessments seek to draw inferences about student understanding by eliciting evidence about the mental models that underlie students' reasoning about physical systems. Measurement techniques for analyzing data from such assessments embody one of two contrasting assessment programs: learning progressions and facet-based assessments. The research presented here provides a systematic comparison of these two approaches, which is of great practical value to assessment programs that seek to employ small clusters of related items for the purpose of measuring depth of understanding. Specifically, models were compared on model-data fit, diagnostic reliability, diagnostic certainty, and predictive accuracy. In addition, the effects of test length were evaluated for both models in order to inform the number of items required to obtain adequately reliable diagnoses of understanding. Lastly, changes in student understanding over time were studied with a longitudinal model in order to provide educators and curriculum developers with a sense of how students advance in understanding over the course of instruction.

Working memory (WM), which includes short-term memory and cognitive control, has been found to be closely related to a wide range of high-level cognitive abilities and academic achievement. Prior studies showed children with attention-deficit/hyperactivity disorder improved their WM and fluid intelligence through computerized cognitive training (CCT) in a clinical setting. This research examined whether regular middle-school students would significantly improve their WM through CCT on WM; and if so, whether increase in WM would lead to improved fluid intelligence and science achievement. Two randomized pretest-posttest control-group experimental studies were conducted to answer these questions. Results showed CCT effectively improved regular students' WM in a school setting, with more increase in short-term memory than in cognitive control. No significant improvement was observed in fluid intelligence and science achievement immediately following training. Given the increasingly complex learning environment in schools, using CCT to improve students' cognition and academic learning has important implications for both practitioners and researchers in education.