Biblio

Export 211 results:
2000
Kennedy, C. (2000). What Influences Student Learning in an Online Course? (No. BEAR Research Note). University of California, Berkeley.
2001
Xie, Y. (2001). Dimensionality, Dependence, or Both?: An Application of the Item Bundle Model to Multidimensional Data. Position Paper; Policy, Organization, Measurement, & Evaluation; Graduate School of Education; University of California, Berkeley.
2002
Xie, Y. (2002). An Application of a Special Two-Class Item Response Model Using Markov Chain Monte Carlo Method. Position Paper; Policy, Organization, Measurement, & Evaluation; Graduate School of Education; University of California, Berkeley.
Kennedy, C. (2002, November). Formative Evaluation of an Online Teaching Strategy: Using Mixed Methods to Learn From the Student Experience. Presented at the American Evaluation Association 2002 Conference, Washington, D.C.
 (873.21 KB)
Claesgens, J., Scalise, K., Draney, K., Wilson, M., & Stacy, A.. (2002). Perspective of a Chemist: A Framework to Promote Conceptual Understanding of Chemistry. Presented at the

Annual Meeting of the American Educational Research Association, New Orleans, LA.

.
2003
Wilson, M. (2003). On Choosing a Model for Measuring. Methods of Psychological Research.
Briggs, D. C., & Wilson, M.. (2003). An introduction to multidimensional measurement using Rasch models. Journal of Applied Measurement, 4, 87–100.
Kennedy, C. (2003). A Primer on Design Matrices (No. BEAR Research Note). University of California, Berkeley.
 (53.24 KB)
Kennedy, C. (2003, April). Promoting Success in Online College Courses: Understanding Interactions Between Course Structure and Learner Readiness. Presented at the Annual Meeting of the American Educational Research Association, New Orleans, LA.
Wilson, M., & Scalise, K.. (2003, June). Research on learning: Implications for assessment in higher education. Presented at the American Association for Higher Education Assessment Conference, Seattle, WA.
2004
Kennedy, C. (2004, March). The BEAR Assessment System. Presented at the No Child Left Behind Technology Summit, St. Louis, MO.
Briggs, D. C. (2004). Causal Inference and the Heckman Model. Journal of Educational and Behavioral Statistics, 29, 397-420. doi:10.3102/10769986029004397
Briggs, D. C. (2004). Evaluating SAT coaching: gains, effects and self-selection. Rethinking the SAT: The Future of Standardized Testing in University Admissions, 217–233.
Kennedy, C. (2004, April). An example of a task template from the Full Option Science System (FOSS). Presented at the Annual Meeting of the American Educational Research Association, San Diego, CA.
Wilson, M., & Xie, Y.. (2004). The Imperial vs Metric Study. University of California, Berkeley.
 (756.77 KB)
Scalise, K., Claesgens, J., Krystyniak, R., Mebane, S., Wilson, M., & Stacy, A.. (2004). Perspectives of Chemists: Tracking conceptual understanding of student learning in chemistry at the secondary and university levels. Enhancing the Visibility and Credibility of Educational Research, American Educational Research Association Annual Meeting, San Diego, CA.
Wilson, M., & Draney, K.. (2004). Some Links Between Large-Scale and Classroom Assessments: The Case of the BEAR Assessment System. Yearbook of the National Society for the Study of Education, 103, 132–154.
Kennedy, C. (2004, April). Technology Underlying task templates in the PADI design system: The scoring engine. Presented at the Annual Meeting of the American Educational Research Association, San Diego, CA.

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