The template-based automated item-generation (TAIG) approach that involves template creation, item generation, item selection, field-testing, and evaluation has more steps than the traditional item development method. Consequentially, there is more margin for error in this process, and any template errors can be cascaded to the generated items.…

In this article, we systematize the factors influencing performance and feasibility of automatic content scoring methods for short text responses. We argue that performance (i.e., how well an automatic system agrees with human judgments) mainly depends on the linguistic variance seen in the responses and that this variance is indirectly influenced…

In this digital ITEMS module, Dr. Sue Lottridge, Amy Burkhardt, and Dr. Michelle Boyer provide an overview of automated scoring. Automated scoring is the use of computer algorithms to score unconstrained open-ended test items by mimicking human scoring. The use of automated scoring is increasing in educational assessment programs because it allows…

Changes to the design and development of our educational assessments are resulting in the unprecedented demand for a large and continuous supply of content-specific test items. One way to address this growing demand is with automatic item generation (AIG). AIG is the process of using item models to generate test items with the aid of computer…

A framework for evaluation and use of automated scoring of constructed-response tasks is provided that entails both evaluation of automated scoring as well as guidelines for implementation and maintenance in the context of constantly evolving technologies. Consideration of validity issues and challenges associated with automated scoring are…