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Open Access Publications from the University of California


Using Lexical Analysis Software to Assess Student Writing in Statistics

Meaningful assessments that reveal student thinking are vital to the success of addressing the GAISE recommendation: use assessments to improve and evaluate student learning. Constructed-response questions, also known as open-response or short answer questions, in which students must write an answer in their own words, have been shown to better reveal students' understanding than multiple-choice questions, but they are much more time consuming to grade for classroom use or code for research purposes. This paper describes and illustrates the use of two different software packages to analyze open-response data collected from undergraduate students’ writing. The analysis and results produced by the two packages are contrasted with each other and with the results obtained from hand coding of the same data sets. The article concludes with a discussion of the advantages and limitations of the analysis options for statistics education research.

Technology Innovations

R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics

Nolan and Temple Lang argue that “the ability to express statistical computations is an es- sential skill.” A key related capacity is the ability to conduct and present data analysis in a way that another person can understand and replicate. The copy-and-paste workflow that is an artifact of antiquated user-interface design makes reproducibility of statistical analysis more difficult, especially as data become increasingly complex and statistical methods become increasingly sophisticated. R Markdown is a new technology that makes creating fully-reproducible statistical analysis simple and painless. It provides a solution suitable not only for cutting edge research, but also for use in an introductory statistics course. We present experiential and statistical evidence that R Markdown can be used effectively in introductory statistics courses, and discuss its role in the rapidly-changing world of statistical computation.