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Session Type: Symposium
Learning progressions (LPs) are descriptions of how students’ understandings in a domain develop over time, and are prominent in the new science standards. Research on LPs invariably involves the design of valid assessments to provide useful evidence of student thinking and learning, however the process is complicated and fraught with challenges, particularly in the context of LPs. This symposium aims to tackle some of the tricky, nuanced, and unique problems in working with assessment and student data in relation to LPs. A panel of experts will discuss open and candidly with the audience the obstacles they face working with assessment data in relation to LPs, and how they have attempted to address and move through these challenges in their work.
Navigating the Challenges of Open-Ended Response Scores - Ann E. Rivet, Teachers College, Columbia University
Assessing Students' Level of Understanding the Core Idea of Matter Using Ordered Multiple-Choice Items - Knut Hartmut Neumann, Leibniz Institute for Science and Mathematics Education
Validating Assessments for a Genetics Learning Progression - Jinnie Choi, Pearson; Ravit Golan Duncan, Rutgers University; Moraima Castro-Faix, Rutgers University; Veronica Cavera, American Water Works Association
What We've Learned About Learning Progressions, Items, and Scoring Guides From Using Item Response Models - Karen L. Draney, University of California - Berkeley; Jennifer H. Doherty, University of Washington; Charles W. Anderson, Michigan State University; Jinho Kim, University of California - Berkeley
Machine Learning Analysis of Student Responses to Carbon: Transformations in Matter and Energy (Carbon TIME) Learning Progression Items - James Lamar Gambrell, ACT, Inc.; Jay Thomas, ACT, Inc.; Richard Meisner, ACT, Inc.; Brad Bolender, ACT, Inc.