Prediction assessments: Using video-based predictions to assess prospective teachers' knowledge of students' mathematical thinking

Anderson Norton, Andrea McCloskey, Rick A. Hudson

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

In order to evaluate the effectiveness of an experimental elementary mathematics field experience course, we have designed a new assessment instrument. These video-based prediction assessments engage prospective teachers in a video analysis of a child solving mathematical tasks. The prospective teachers build a model of that child's mathematics and then use that model to predict how the child will respond to a subsequent task. In this paper, we share data concerning the evolution and effectiveness of the instrument. Results from implementation indicate moderate to high degrees of inter-rater reliability in using the rubric to assess prospective teachers' models and predictions. They also indicate strong correlation between participation in the experimental course and prospective teachers' performances on the video-based prediction assessments. Such findings suggest that prediction assessments effectively evaluate the pedagogical content knowledge that we are seeking to foster among the prospective teachers.

Original languageEnglish (US)
Pages (from-to)305-325
Number of pages21
JournalJournal of Mathematics Teacher Education
Volume14
Issue number4
DOIs
StatePublished - Aug 1 2011

All Science Journal Classification (ASJC) codes

  • Education
  • Mathematics(all)

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