Automated assessment using Natural Language Processing (NLP) has the potential to make English speaking assessments more reliable, authentic, and accessible. Yet without careful examination, NLP may exacerbate social prejudices based on gender or native language (L1). Current NLP-based assessments are prone to such biases, yet research and…

Speaking performance tests typically employ raters to produce scores; accordingly, variability in raters' scoring decisions has important consequences for test reliability and validity. One such source of variability is the rater's level of expertise in scoring. Therefore, it is important to understand how raters' performance is influenced by…

Information technology (IT) certifiers evaluate risk and develop mitigations ensuring IT infrastructures remain protected within acceptable levels of operation, which if not properly maintained can potentially result in loss of life within Department of Defense (DoD) and federal environments. This qualitative phenomenological exploratory study…

By centralizing the issue of test fairness in language proficiency assessments, this study responds to a call by researchers for developing greater social responsibility in the language testing agenda. As inquiries into language attitude and psychology indicate, there is an underlying uncertainty pertaining to the validity of test use and score…