One of the main goals of statistics is to use data to provide evidence in support of an argument. This article will discuss some popular forms of writing assessments currently in use, to demonstrate the differences between the methods for structuring the students' learning to support their arguments with evidence. We share a model, which was originally created to assess students in introductory statistics and has been adapted for the second course in statistics, which takes a unique approach toward assessing the students' understanding of statistical concepts through writing. In this model, students are expected to answer prompts that required them to (1) take a stance on an argument, (2) defend their position with facts given in the prompt, (3) discern the implications that those facts implied, and (4) give a proper conclusion to their argument. We provide examples of a few of the writing assignment prompts used in the course, their intended assessment purpose, and common answers that students gave to these assignments. Supplementary materials for this article are available online.
As the demand for skilled data scientists has grown, university level statistics and data science courses have become more rigorous in training students to understand and utilize the tools that their future careers will likely require. However, the mechanisms to assess students' use of these tools while they are learning to use them are not well defined. As such, a framework to assess statistical computing actions was created. Using task-based interviews of students who completed a second course in statistics, the framework was used to determine the ways in which students utilize statistical computing tools, specifically R, while going through problem solving phases. Patterns that emerged are discussed.
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