Prediction assessments: Using video-based predictions to assess prospective teachers’ knowledge of students’ mathematical thinking
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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.
KeywordsTeacher knowledge Instrument development Video Preservice teacher education Pedagogical content knowledge
The research reported in this paper was supported by a DR-K12 grant from the National Science Foundation (NSF), under grant number DRL-0732143. The authors wish to thank all the members of the IMB research team, as well as Dionne Cross, who collaborated with us in collecting data.
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