Validation of two measures for assessing English vocabulary knowledge on web-based testing platforms: long-form assessments

Lee Drown; Nikole Giovannone; David B Pisoni; Rachel M Theodore

doi:10.1515/lingvan-2022-0115

Validation of two measures for assessing English vocabulary knowledge on web-based testing platforms: long-form assessments

Linguist Vanguard. 2023 Sep 13;9(1):113-124. doi: 10.1515/lingvan-2022-0115. eCollection 2023 Dec.

Authors

Lee Drown¹, Nikole Giovannone¹, David B Pisoni², Rachel M Theodore¹

Affiliations

¹ Department of Speech, Language, and Hearing Sciences, University of Connecticut, Storrs, CT, USA.
² Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.

Abstract

The goal of the current work was to develop and validate web-based measures for assessing English vocabulary knowledge. Two existing paper-and-pencil assessments, the Vocabulary Size Test (VST) and the Word Familiarity Test (WordFAM), were modified for web-based administration. In Experiment 1, participants (n = 100) completed the web-based VST. In Experiment 2, participants (n = 100) completed the web-based WordFAM. Results from these experiments confirmed that both tasks (1) could be completed online, (2) showed expected sensitivity to English frequency patterns, (3) exhibited high internal consistency, and (4) showed an expected range of item discrimination scores, with low frequency items exhibiting higher item discrimination scores compared to high frequency items. This work provides open-source English vocabulary knowledge assessments with normative data that researchers can use to foster high quality data collection in web-based environments.

Keywords: assessment; vocabulary; web-based testing.

Abstract

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