Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/1170
Title: Understanding the Relationships Within and Between Constructs of a Learning Progression: Combining Multidimensional Item Response Modeling and Latent Class Analysis
Authors: Choi, Jinnie
Duncan, Ravit Golan
Issue Date: Jun-2014
Publisher: Boulder, CO: International Society of the Learning Sciences
Citation: Choi, J. & Duncan, R. G. (2014). Understanding the Relationships Within and Between Constructs of a Learning Progression: Combining Multidimensional Item Response Modeling and Latent Class Analysis. In Joseph L. Polman, Eleni A. Kyza, D. Kevin O'Neill, Iris Tabak, William R. Penuel, A. Susan Jurow, Kevin O'Connor, Tiffany Lee, and Laura D'Amico (Eds.). Learning and Becoming in Practice: The International Conference of the Learning Sciences (ICLS) 2014. Volume 1. Colorado, CO: International Society of the Learning Sciences, pp. 607-614.
Abstract: Learning progressions are hypothetical models of student learning in a domain over extended periods of time. In many cases these progressions describe multiple `big ideas' or constructs. Relationships between these constructs, i.e., how development along one might affect the other, are difficult to ascertain. Such relationships can be described from the perspectives of either item characteristics or student abilities. Existing methods of analyses focus predominantly on the `item-side' of the equation and much less research addresses construct relationships from the `student-side'. In this study, we supplemented a Multidimensional Item Response Modeling approach with a Latent Class Analysis to more fully explore both within and between-construct relationships. We analyzed student written responses (n=317) to 31 ordered-multiple-choice items targeted at five constructs in a genetics learning progression. We present our finding with the goal of comparing and contrasting the types of inferences that can be made with both measurement approaches.
URI: https://doi.dx.org/10.22318/icls2014.607
https://repository.isls.org//handle/1/1170
Appears in Collections:ICLS2014

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