RESEARCH LIBRARY

Educational Assessment

This study proposes four indices to quantify item influence and distinguishes them from other available item and test measures. We use simulation methods to evaluate and provide guidelines for interpreting each index, followed by a real data application to illustrate their use in practice. We discuss theoretical considerations regarding when influence presents a psychometric concern and other practical concerns such as how the indices function when reducing influence imbalance.

Journal of Applied Technology: Volume 23 - Special Issue 1 - Pages 30-40

The interpretations of test scores in secure, high-stakes environments are dependent on several assumptions, one of which is that examinee responses to items are independent and no enemy items are included on the same forms. This paper documents the development and implementation of a C#-based application that uses Natural Language Processing (NLP) and Machine Learning (ML) techniques to produce prioritized predictions of item enemy statuses within a large item bank.

Handbook of Automated Scoring

In this chapter we describe the historical background that led to development of the simulations and the subsequent refinement of the construct that occurred as the interface was being developed. We then describe the evolution of the automated scoring procedures from linear regression modeling to rule-based procedures.