By the ASPIRE Research Team. This paper outlines development of the Modeling Energy Flows Learning Progression and key indicators for each level of the learning progression. This learning progression is designed to directly support three-dimensional science learning by integrating the crosscutting concept of energy in systems and the science practice of modeling at each level.
By Benjamin Shear. When contextual features of test-taking environments differentially affect item responding for different test-takers and these features vary across test administrations, they may cause differential item functioning (DIF) that varies across test administrations. Because many common DIF detection methods ignore potential DIF variance, this paper proposes the use of random coefficient hierarchical logistic regression (RC-HLR) models to test for both uniform DIF and DIF variance simultaneously.
By Derek C. Briggs and Erin Marie Furtak. Learning progressions have great potential as an organizing framework for classroom instruction and assessment. However, successful implementation of this framework hinges upon developing a curriculum-embedded system of student assessment. In this chapter, an approach to meeting this challenge is illustrated in the context of a learning progression in science that crosses the disciplinary boundaries of physics, chemistry and biology in a high school setting.
By Derek C. Briggs and Jessica L. Alzen. Observation protocol scores are commonly used as status measures to support inferences about teacher practices. When multiple observations are collected for the same teacher over the course of a year, some portion of a teacher’s score on each occasion may be attributable to the rater, lesson and time of year of the observation.