Modeling Mathematical Teaching Knowledge Relationships for Different Teaching Practice Using Bayesian Networks

• In Event: Marriott Roundtable Session 2
  In Roundtable Session: Modeling and Developing Usable Knowledge of Mathematics Teaching

Abstract

We report on a study in which 224 teachers responded to an authentic classroom video clip on teaching fractions as partitioning from the Classroom Video Analysis-Modified (CVA-M; Authors 2012) instrument. We identified Common Core (Council of Chief State School Officers & National Governors Assocation Center for Best Practices, 2010)-aligned mathematical and pedagogical knowledge in teachers’ written responses. Conceptualizing knowledge as the usable knowledge proximal to the knowledge teachers activate in similar situations in the classroom based on their own teaching practices, we created models of usable knowledge structures for different teaching practice groups using Bayesian Networks (BN). The results capture how the conditional dependencies, the ways in which the knowledge is related, differ across groups.

Authors

• James E. Smith, University of Arizona

• Nicole B. Kersting, The University of Arizona

• Beau Vezino, Northern Arizona University

• Mei-Kuang Chen, The University of Arizona

• James W. Stigler, University of California - Los Angeles