Showing 1 - 2 of 2 Research Library Publications
Posted: | Ian Micir, Kimberly Swygert, Jean D'Angelo

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.

Posted: | S. Pohl, M. von Davier

Front. Psychol. 9:1988

 

In their 2018 article, (T&B) discuss how to deal with not reached items due to low working speed in ability tests (Tijmstra and Bolsinova, 2018). An important contribution of the paper is focusing on the question of how to define the targeted ability measure. This note aims to add further aspects to this discussion and to propose alternative approaches.