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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.
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