Affiliation:
1. University of Alberta, Canada
Abstract
Increasing demand for knowledge of our workers has prompted the increase in assessments and providing feedback to facilitate their learning. This and the increasingly computerized assessments require new test items beyond the ability for content specialists to produce them in a feasible fashion. Automatic item generation is a promising method that has begun to demonstrate utility in its application. The purpose of this chapter is to describe how AIG can be used to generate test items using the selected-response (i.e., multiple-choice) format. To ensure our description is both concrete and practical, we illustrate template-based item generation using an example from the complex problem-solving domain of the medical health sciences. The chapter is concluded with a description of the two directions for future research.