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Although the paradigm wars between quantitative and qualitative research methods and the associated epistemologies may have settled down in recent years within the mathematics education research community, the high value placed on quantitative methods and randomized control trials remain as the gold standard at the policy-making level (USDOE, 2008). Although diverse methods are valued in the mathematics education community, if mathematics educators hope to influence policy to cultivate more equitable education systems, then we must engage in rigorous quantitative research. However, quantitative research is limited in what it can measure by the quantitative tools that exist. In mathematics education, it seems as though the development of quantitative tools and studying their associated validity and reliability evidence has lagged behind the important constructs that rich qualitative research has uncovered. The purpose of this study is to describe quantitative instruments related to mathematics teacher behavior and affect in order to better understand what currently exists in the field, what validity and reliability evidence has been published for such instruments, and what constructs each measure. 1. How many and what types of instruments of mathematics teacher behavior and affect exist? 2. What types of validity and reliability evidence are published for these instruments? 3. What constructs do these instruments measure? 4. To what extent have issues of equity been the focus of the instruments found? 

Proof and argumentation are essential components of learning mathematics, and technology can mediate students’ abilities to learn. This systematic literature review synthesizes empirical literature which examines technology as a support for proof and argumentation across all content domains. The themes of this review are revealed through analyzing articles related to Geometry and mathematical content domains different from Geometry. Within the Geometry literature, five subthemes are discussed: (1) empirical and theoretical interplay in dynamic geometry environments (DGEs), (2) justifying constructions using DGEs, (3) comparing technological and non-technological environments, (4) student processing in a DGE, and (5) intelligent tutor systems. Within the articles related to content different from Geometry, two subthemes are discussed: technological supports for number systems/algebra and technological supports for calculus/real analysis. The technological supports for proof revealed in this review could aid future research and practice in developing new strategies to mediate students’ understandings of proof.