Researchers have long endeavored to understand whether teachers’ evaluations of their students’ mathematical ability or performance are accurate or whether their evaluations reveal implicit biases. To disentangle these factors, in a randomized controlled study (N = 390), we examined teachers’ evaluations of 18 mathematical solutions to which gender- and race-specific names had been randomly assigned. Teachers displayed no detectable bias when assessing the correctness of students’ solutions; however, when assessing students’ mathematical ability, biases against Black, Hispanic, and female students were revealed, with biases largest against Black and Hispanic girls. Specifically, non-White teachers’ estimations of students’ mathematical ability favored White students (both boys and girls) over students of color, whereas (primarily female) White teachers’ estimations of students’ mathematical ability favored boys over girls. Results indicate that teachers are not free of bias, and that teachers from marginalized groups may be susceptible to bias that favors stereotype-advantaged groups.

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The purpose of this design based research study was to better understand and build from students’ perceptual experiences of visual representations of the greenhouse effect. Twenty undergraduate students were interviewed as they engaged with an online visualization for the learning of the greenhouse effect. We found that, even though all students agreed that climate change is happening, a majority initially held a misconception about how it works. Upon engaging with the visualization, students made perceptual inferences and formulated causal rules that culminated in an improved description of how climate change works. This trajectory was supported with prompts from the interviewer to make predictions, observe specific interactions in the visualization and revise their causal inferences based on these observations. A case study is presented to illustrate a typical learning trajectory.

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The success of professional development programs has typically been determined based on their impact on teacher learning, without much attention being given to the data sources used. Large-scale studies have generally relied on teachers’ self-reports, whereas small-scale studies have included more direct assessments and observations of teacher learning. The purpose of this study was to compare teachers’ self-reported gains in mathematical knowledge for teaching with those measured by direct assessments. Quantitative analyses of the data collected from 545 teachers who participated in content-focused professional development programs indicated a lack of correlation between teachers’ self-reports and direct assessments of their knowledge gains. Furthermore, different teacher-related factors were associated with the learning reported by these two measures. These findings speak to the need to pay careful attention to the outcome measures used to evaluate teachers’ learning.