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Abstract

Teacher noticing of student mathematical thinking is increasingly seen as an important construct, but challenges remain in operationalizing and assessing teachers’ analyses of their classrooms. In this chapter, we present a methodology for analyzing teachers’ professional noticing of student mathematical thinking based on its alignment to mathematical learning goals. This process entails first deconstructing a mathematical learning goal into its conceptually important pieces (known as subgoals). Then, researchers can look for references to these subgoals in teachers’ attending, interpreting, and deciding (the three skills of noticing). When teachers reference conceptual subgoals of a learning goal in their noticing, it indicates their attention to students’ reasoning about the important mathematical ideas of a lesson. This method of data analysis can be used across a variety of contexts and allows for greater precision in understanding teacher noticing by focusing on its mathematical content and attention to relevant student thinking. In this theoretical chapter, we describe this research methodology (and the process of deconstructing learning goals and using subgoals), justify its appropriateness as a measure of teacher noticing, and provide examples from our own and others’ work to illuminate its use.

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... Morris et al. (2010) suggest that the best claims should align with the mathematical learning goal, beginning by dissecting learning goals into their component mathematical ideas, called subgoals, and comparing student responses to those subgoals. High-quality evaluation of student thinking will address as many of the conceptually important mathematical ideas (subgoals) as possible, allowing teachers to make judgments about the full range of ideas in the learning goal and to pay attention to gaps in mathematical knowledge (Morris 2006;Morris et al. 2010;Spitzer and Phelps-Gregory 2017). ...
... For our first category of codes, addressing research question one, we coded PTs' claims about student thinking using a coding scheme that categorized PTs' claims based on their level of specificity and alignment to the learning goal (see Table 1 for descriptions and examples of these codes). In alignment with our conceptual framework and following the work of other researchers (Meikle 2014;Morris et al. 2010;Spitzer and Phelps 2017), we consider PTs' claims about subgoals of the learning goal as the highest quality claim, because these claims are both specific about the kinds of student thinking inferred and relevant to the learning goal (as a reminder, see Fig. 1 for the goal and one possible subgoal decomposition). The other three types of claims are either poorly aligned with the learning goal (focusing on irrelevant mathematics or pure procedural knowledge) or too broad to be useful (generic claims about math). ...
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