Learning Progressions
in Science Conference

June 24-26, 2009
Iowa City, IA

Conference Proceedings

Thursday, June 25th, 2009
Defining Plenary Session
MoDeLS: Defining a Learning Progression for Scientific Modeling
  • Christina Schwarz, Michigan State University
  • Brian Reiser, Northwestern University
  • David Fortus, Weizmann Institute of Science
  • Yael Shwartz, Weizmann Institute of Science
  • Andres Acher, Northwestern University
  • Betsy Davis, University of Michigan
  • Lisa Kenyon, Wright State University
  • Barbara Hug, University of Illinois
Towards a Model for the Development of an Empirically Tested Learning Progression
  • Shawn Y. Stevens, University of Michigan
  • Namsoo Shin, University of Michigan
  • Joseph S. Krajcik, University of Michigan
Learning a Secondary Discourse: Shifts from Force-Dynamic to Model-Based Reasoning in Understanding Water in Socio-Ecological Systems
  • Kristin L. Gunckel, University of Arizona
  • Beth A. Covitt, University of Montana
  • Charles W. Anderson, Michigan State University
Teaching Experiments and the Carbon Cycle Learning Progression
  • Lindsey Mohan, Michigan State University
  • Charles W. Anderson, Michigan State University
Using Plenary Session
Using a Learning Progression to Inform Scientific Argumentation in Talk and Writing
  • Leema Kuhn Berland, University of Texas at Austin
  • Katherine L. McNeill, Boston College
Learning Progressions as a Tool for Curriculum Development: Lessons from the Inquiry Project
  • Marianne Wiser, Clark University
  • Carol L. Smith, University of Massachusetts at Boston
  • Sue Doubler, TERC
  • Jodi Asbell-Clarke, TERC
Toward Learning Progressions as Teacher Development Tools
  • Erin Marie Furtak, University of Colorado at Boulder
Strand-Specific Breakout Sessions
Defining Strand
Learning Progressions in Science Education: Two Approaches for Development
  • Ivan Salinas, University of Arizona
Understanding Learning Progression in Student Conceptualization of Atomic Structure by Variation Theory for Learning
  • Eun Jung Park, Northwestern University
  • Greg Light, Northwestern University
  • Su Swarat, Northwestern University
  • Denise Drane, Northwestern University
Progression Through Aspects of Variation: An Alternative Approach to Construct Learning Progressions
  • Su Swarat, Northwestern University
  • Greg Light, Northwestern University
  • Denise Drane, Northwestern University
  • Eun Jung Park, Northwestern University
Tracing a Prospective Learning Progression for Magnetism with Implications at the Nanoscale
  • David Sederberg, Purdue University
  • Lynn A. Bryan, Purdue University
Using Strand
The Juncture of Supply and Demand for Information: How and When Can Learning Progressions Meet the Information Demands of Curriculum Developers?
  • Seth Corrigan, Lawrence Hall of Science at the University of California Berkeley
  • Suzanna Loper, Lawrence Hall of Science at the University of California Berkeley
  • Jacqueline Barber, Lawrence Hall of Science at the University of California Berkeley
  • Nathaniel Brown, Indiana University
  • Jonna Kulikowich, The Pennsylvania State University
A Learning Progression Approach to Teacher Professional Development in Astronomy
  • Julia D. Plummer, Arcadia University
  • Cynthia Slagle, Colonial School District
Learning Progressions to Support Coherence Curricula in Instructional Material, Instruction, and Assessment Design
  • Namsoo Shin, University of Michigan
  • Shawn Y. Stevens, University of Michigan
  • Harry Short, University of Michigan
  • Joseph Krajcik, University of Michigan
Learning Progressions as Vision Tools for Advancing Teachers' Pedagogical Performance
  • Jessica Thompson, University of Washington
  • Melissa Braaten, University of Washington
  • Mark Windschitl, University of Washington
Assessing Strand
Designing Learning Progressions with the BEAR Assessment System
  • Karen Draney, University of California, Berkeley
Development and Validation of Assessments for a Learning Progression on Carbon Cycling in Socio-Ecological Systems
  • Hui Jin, Michigan State University
  • Jinnie Choi, University of California, Berkeley
  • Charles W. Anderson, Michigan State University
Modeling/Interpreting Strand
The Psychometric Modeling of Ordered Multiple-Choice Item Responses for Diagnostic Assessment with a Learning Progression
  • Derek C. Briggs, University of Colorado
  • Alicia C. Alonzo, University of Iowa
Modeling Learning Progressions in Epistemic Games with Epistemic Network Analysis: Principles for Data Analysis and Generation
  • André A. Rupp, University of Maryland
  • Younyoung Choi, University of Maryland
  • Matthew Gushta, University of Maryland
  • Robert Mislevy, University of Maryland
  • Mary Carolyn Thies, University of Maryland
  • Elizabeth Bagley, University of Wisconsin at Madison
  • Padraig Nash, University of Wisconsin at Madison
  • David Hatfield, University of Wisconsin at Madison
  • Gina Svarovsky, University of Wisconsin at Madison
  • David W. Shaffer, University of Wisconsin at Madison
Keynote Address
Reflections on Learning Progressions
  • Richard J. Shavelson, Stanford University
Graduate Student Poster Session
The Iterative Development of a Learning Progression Assessment Tool
  • Lea Bullard, University of Michigan
  • Amelia Wenk Gotwals, Michigan State University
  • Nancy Butler Songer, University of Michigan
Utilizing an Assessment Design Framework to Map Research Questions and Develop High Quality Assessments (Poster)
  • Andrew J. Galpern, University of California, Berkeley
Investigating the Relationship Between Scientific Modeling and Content Knowledge
  • Hayat Hokayem, Michigan State University
  • Jing Chen, Michigan State University
Using Learning Progressions to Develop and Implement an Inquiry Model for Force and Motion at K-5 Level (Poster)
  • Diane Johnson, Lewis County Schools
  • Martin Brock, Eastern Kentucky University
Developing a Calibrated Progress Variable for the Particle Nature of Matter (Poster)
  • Joi Merritt, University of Michigan, Ann Arbor
  • Joe Krajcik, University of Michigan, Ann Arbor
Learning Progressions of Ecological Concepts Developed Through Earth Education Informal Learning Experiences
  • Elisabeth Roberts, University of Arizona
  • Bruce Johnson, University of Arizona
Learning Progressions in Science Education: Two Approaches for Development (Poster)
  • Ivan Salinas, University of Arizona
Defining Learning Progressions for Scientific Inquiry (Poster)
  • Tiffany-Rose Sikorski, University of Maryland, College Park
  • Victoria Winters, San Diego State University/University of California, San Diego
  • David Hammer, University of Maryland, College Park
Progression Through Aspects of Variation: An Alternative Approach to Construct Learning Progressions
  • Su Swarat, Northwestern University
  • Greg Light, Northwestern University
  • Denise Drane, Northwestern University
  • Eun Jung Park, Northwestern University
Modeling the Learning Progression of Students' Data Representation and Scientific Explanations: A Multilevel Modeling Approach
  • Shinping Tsai, University of Washington
  • Min Li, University of Washington
  • Maria Araceli Ruiz-Primo, University of Colorado Denver
Coordinated Progress in Conceptual Understanding and Representational Competence (Poster)
  • Leah Walker, University of California, Berkeley
  • Mark Wilson, University of California, Berkeley
  • Robert Schwartz, University of California, Berkeley
  • David Torres Irribarra, University of California, Berkeley
Friday, June 26th, 2009
Assessing & Modeling Plenary Session
Assessing Students' Progressing Abilities to Construct Scientific Explanations
  • Amelia Wenk Gotwals, Michigan State University
  • Nancy Butler Songer, University of Michigan
  • Lea Bullard, University of Michigan
Assessing Students' Evolving Understandings about Matter
  • David W. Carraher, TERC
  • Carol L. Smith, University of Massachusetts at Boston
  • Marianne Wiser, Clark University
  • Analúcia D. Schliemann, Tufts University
  • Gabrielle Cayton-Hodges, Tufts University
The Structured Constructs Model (SCM): A Family of Statistical Models Related to Learning Progressions
  • Mark Wilson, University of California, Berkeley
A Bayes Net Approach to Modeling Learning Progressions and Task Performances
  • Patti West, Cisco
  • Daisy Wise Rutstein, University of Maryland
  • Robert J. Mislevy, University of Maryland
  • Junhui Liu, University of Maryland
  • Roy Levy, Arizona State University
  • Kristen E. DiCerbo, Cisco Learning Institute
  • Aaron Crawford, Arizona State University
  • Younyoung Choi, University of Maryland
  • John T. Behrens, Cisco

The LeaPS conference is supported by the National Science Foundation under grant # DRL 0824432. Any opinions, findings, and conclusions or recommendations expressed are those of the conference organizers and/or participants and do not necessarily reflect the views of the National Science Foundation.

Copyright © 2009