While research has consistently shown the positive effects of having a teacher of the same race on various student outcomes, the literature has not examined how racial match affects the everyday interactions within classrooms. This research article by Dan Battey, Luis A. Leyva, Immanuel Williams, Victoria A. Belizario, Rachel Greco, and Roshni Shah addresses this underexplored area by documenting relational interactions in classrooms to find one mechanism that could be producing racialized effects on learning. Using a dataset from a study of twenty-five mathematics classrooms across predominantly white and black US middle schools, they examine the quality of relational interactions when teachers and students are racially matched and mismatched, as well as the effects on student achievement in mathematics. Their analysis shows how various dimensions of relational interactions significantly predict increases and decreases in achievement due to racial match.

Summary Many students find understanding confidence intervals difficult, especially because of the amalgamation of concepts such as confidence levels, standard error, point estimates and sample sizes. An R Shiny application was created to assist the learning process of confidence intervals using graphics and data from the US National Basketball Association.

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Understanding summary statistics and graphical techniques are building blocks to comprehending concepts beyond basic statistics. Its known that motivated students perform better in school. Using examples that students find engaging allows them to understand the concepts at a deeper level.

This paper provides introductory statistics instructors with the capacity to use engaging National Basketball Association (NBA) data within a web application to either strengthen students' understanding or introduce the concept of variance and one-way analysis of variance. Using engaging data within the classroom provides context to data that students deem applicable to their lives. This paper not only provides a lesson plan for teaching these concepts but also provides a web application and the engaging NBA dataset if the instructor decides to use the app or the data in another context. The NBA data selected to focus on the debate "Who is the greatest NBA player of all time?". By using context students are familiar with and interested in, we can get them interested in and further engaged in statistics.