The past two decades of research on how students develop their science understandings as they make sense of phenomena that occur in the natural world has culminated in a movement to redefine science educational standards. The so-called Next Generation Science Standards (or NGSS) codify this new definition into a set of distinct performance expectations, which outline how students might reveal to what extent they have sufficient understanding of disciplinary core ideas (DCIs), science practices (SEPs), and crosscutting concepts (CCCs). The latter of these three dimensions is unique both in being the most recent to the field and in being the least supported by prior science education research. More crucially, as a policy document, the NGSS alone does not provide the supports teachers need to bring reforms to their classrooms, particularly not summative assessments. This dissertation addresses both of these gaps using a combination of quantitative and qualitative techniques. First, I analyze differential categorization of problems that require respondents to engage with their CCC understandings via confirmatory factor analysis inference. Second, I use a set of Rasch models to measure preliminary learning progressions for CCCs evident in student activity within a computer-assisted assessment experience. Third, I analyze student artifacts, think-aloud interviews, and post-task reflective interviews via activity theory to adapt the progression into a task model in which students explain and predict aspects of Earth systems. The culmination of these three endeavors not only sets forth a methodology for researching CCCs in a way that is more integrative to the other dimensions of the NGSS, but also provides a framework for developing assessments that are aligned to the goals of these new standards.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-h5d3-5j83 |
| Date | January 2019 |
| Creators | Weiser, Gary |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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