This course focuses on the fundamental concepts, theories, and
algorithms for Computerized Adaptive Testing (CAT). The course
will introduce item pool construction, item selection, ability
estimation, stopping criteria, exposure control, content
balancing control, and CAT security, as well as programming
skills related to CAT.
Athena Title
Computerized Adaptive Testing
Pre or Corequisite
(ERSH 8610 or ERSH 8610E) and ERSH 8620
Semester Course Offered
Not offered on a regular basis.
Grading System
A - F (Traditional)
Student learning Outcomes
After completing this course, students will be able to determine when computerized adaptive testing (CAT) is an appropriate methodological technique.
After completing this course, students will be able to explain how to construct an item pool for a CAT.
After completing this course, students will be able to understand key components of CAT algorithms, including item selection, ability estimation, stopping criteria, exposure control, and content balancing.
After completing this course, students will be able to describe issues related to test security of CATs.
After completing this course, students will be able to program a CAT algorithm using appropriate software.
After completing this course, students will be able to evaluate results (e.g., reliability, model fit, estimation accuracy) from CAT analyses.
After completing this course, students will be able to draw appropriate conclusions from CAT analyses.
After completing this course, students will be able to knowledgeably understand and critique CAT literature.
