I.  Course/Instructor Information:

• Course Title: Understanding Educational Testing
• Semester/Year: Fall 2024
• Class meeting times: Tuesdays & Thursdays, 2:15 – 3:30
• Class location: Axinn 105
• Instructor: Steve Hoffman
• Email: hoffman@middlebury.edu

II.   Course Description:

Achievement testing is now a cornerstone of education policy. It is also complex and routinely misunderstood by educators, policymakers, and the media. In this course students will use statistical methods to explore and address testing issues that arise in both policy and practice. We will examine the uses and abuses of educational assessment. We will examine and interrogate trends and group differences in achievement. And we will broaden our understanding of essential concepts of measurement, such as reliability, validity, and bias, by analyzing both large and small datasets. Prior experience with the statistical package “R” is not required, as learning this package will be part of the course. 3 hrs. lect.

III.  Learning Outcomes:

In this course, we will:

• critically examine the uses and abuses of educational assessment
• examine and interrogate trends and group differences in achievement
• broaden our understanding of essential concepts of measurement, such as reliability, validity, and bias
• gain facility employing statistical methods to explore and address testing issues that arise in both policy and practice
• use the statistical package “R” to analyze testing data sets
• communicate our understandings and findings clearly to the general public

IV.   Course Materials and Required Texts:

Koretz, D. (2008). Measuring up: What educational testing really tells us. Harvard University Press. (ebook OK)

• Early on (on page 2), Professor Koretz noted that at the time he wrote this book there were many books on educational testing. Some were very pro-testing while others were anti-testing. Fifteen years later this is still true. Koretz intended to provide a balanced approach to explaining the field of educational testing to a wide audience, and this book is still required for courses on testing at other colleges and universities — both those for the “informed consumers of test scores” as well as for more technical courses. So, while this book is not new, and we will come across explanations that seem dated, it remains an excellent resource for us as we work through today’s issues around educational testing.

Popham, W. (2016). The ABCs of Educational Testing, Corwin Press. (ebook OK) 

• This book is an easier read than the Koretz text. Professor Popham insists at the start of this book that it’s about “the basics of educational testing” written so that readers can learn “a handful of foundational concepts and procedures linked to the testing that routinely goes on in our schools” (p. 1). We won’t follow the contents in the exact order he outlined, but we will use the whole text during the semester.

Wickham, H., Çetinkaya-Rundel, M. & Grolemund, G. (2022). R for Data Science (2e).https://r4ds.hadley.nz (free to use)

• This ebook is about how to “do” data analysis and data science using the “R” package, which you may have used in other courses at Middlebury. We will utilize only a portion of this book, though you may find it useful to bookmark this for work outside of this course. For those of you with no experience with R at all, don’t fret. I and many others here at Middlebury will help you learn the basic tools in R, allowing you to thrive in this course. Be sure to use the second edition (2e). This is a substantial rewrite from the first edition, and you’ll be learning some different coding techniques from the students in the previous iterations of EDST 0213.