This article contributes to the larger narrative around what makes a mathematics professional development (PD) successful and in what ways. We share a research-based PD model that was implemented in elementary schools in an urban school district for 3 years. The model uses a pseudo lesson study approach and emphasizes standards-based instruction. We found that teachers made gains in knowledge and instruction quality. However, whereas some students saw gains on standardized assessments, this was the case only for students who were not members of historically minoritized groups (Black/Latino), countering our assumptions that the PD would lead to equitable achievement results. We conclude with a discussion of how a colorblind approach to PD may account for the inequitable results.
Although the demand for statisticians is growing across many different fields and sectors and more and more students are graduating with degrees in statistics, employers express difficulties in hiring. Indeed, there seems to be a lack of continuity during the transition to the workplace for statisticians. To study this phenomenon, we interviewed junior statisticians who recently experienced the transition as well as mentors who supervised it. A cross-case analysis allowed for an in-depth description of the development of statistical practices in academic settings and at the workplace. Based on our findings and from the perspectives of the participants, we formulate recommendations to promote different practices that are especially challenging to facilitate the transition between education and profession for future statisticians.
Because context plays a critical part in data collection, analysis, and interpretation, we offer an icebreaker activity during which students explore data with an unknown context. We previously developed this activity for small, in-person, introductory statistics courses (White et al., 2018), and we adapted the instructions and materials for online instruction. Surprisingly, we observed more robust conversations of critical concepts during the online implementation. We report how students engaged in the activity, by creating graphs of their own and identifying features of data representations that help them reveal the context. Finally, we discuss how concepts introduced in the icebreaker activity can be developed in later classes.
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