ABSTRACT

Cheating on tests is a pervasive concern across many, varied contexts. Those contexts span a range that includes elementary school achievement testing programs to postsecondary training and professional credentialing programs that offer specialized certifications or licenses to practice in a given field. Viewing cheating as a technical concern actually liberates attention to cheating from becoming mired in comparative, cultural, contextual, or relativist morality debates. Qualitative and quantitative methods for detecting test cheating can produce trustworthy and powerful evidence that a test score lacks validity. The chapter describes the datasets comprise real test data from one credentialing testing program and one K-12 student achievement testing program in the US. It provides detailed information on the two datasets. The two datasets are the credentialing dataset, and the K-12 education dataset. The chapter also presents an overview of the key concepts discussed in this book.