Development and initial validation of a diagnostic computer-adaptive profiler of vocabulary knowledge

Kremmel, Benjamin (2018) Development and initial validation of a diagnostic computer-adaptive profiler of vocabulary knowledge. PhD thesis, University of Nottingham.

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Vocabulary knowledge is key to the successful use of any language skill (Nation & Webb, 2011) and learning to map a particular meaning to an L2 form for a great number of words is therefore crucial for learners of a foreign language. Vocabulary assessments can play a facilitating role in this learning process, which is why there is now an abundance of assessment tools to measure lexical knowledge. However, few of these tests have undergone sophisticated validation, even after their release into the public domain. Although vocabulary tests are used in numerous pedagogical and research settings, there has been “relatively little progress in the development of new vocabulary tests” (Webb & Sasao, 2013, p. 263). Instead, conventionalized traditions are being reiterated without questioning them. This PhD project has set out to address this gap of an innovative measure of vocabulary knowledge by developing a new diagnostic computer-adaptive measure of form-meaning link knowledge: The Vocabulary Knowledge Profiler.

The present test development project started from scratch by questioning the underlying assumptions and trying to make design decisions based not only on theoretical considerations but empirical evidence. In a series of studies, three major weaknesses of existing vocabulary tests were problematized: (1) selection of item formats, (2) sampling in terms of unit of counting, frequency bands and representativeness, and (3) the general lack of validation evidence and validation models. These issues were explored across four studies in this thesis to design a novel instrument and gather initial validation evidence for it along the way.

The first set of studies presented in this thesis investigated the usefulness and informativeness of different item formats for vocabulary tests and found in a comparison of four different formats that all formats show considerable error in measurement but the MC format may be the most useful because of its systematicity in overestimating scores. The second set of studies found support for the adoption of the lemma as an appropriate counting unit and for a new approach to frequency banding that takes into account the relative importance of frequency bands in terms of the coverage they provide. Based on these foundation studies, test specifications were drawn up and an item bank was created, which was subjected to a large scale trial to admit functioning items to an item pool for creating a computer-adaptive test. A study was conducted to compare two different computer-adaptive algorithms for implementation in the test design, suggesting that a “floor first” design would generate more consistent and representative score profiles. For initial validation evidence, a final study was then conducted to relate scores from the finished test to that of a reading comprehension measure. The findings of the studies presented throughout the thesis are then synthesized to produce an initial version of a validation argument in the structure of Bachman and Palmer’s (2010) Assessment Use Argument to outline both the necessary areas for further research before the launch of the test as well as the collected validation evidence to date that builds a tentative argument that the Vocabulary Knowledge Profiler and of the diagnostic decisions that are made based on its results and use are beneficial to English as a foreign language (EFL) learners and EFL teachers for classroom learning and teaching.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Schmitt, Norbert
Sotirova, Violeta
Keywords: vocabulary, test, assessment, test formats, language testing, frequency bands, validation, diagnostic
Subjects: P Language and literature > P Philology. Linguistics
Faculties/Schools: UK Campuses > Faculty of Arts > School of English
Item ID: 49085
Depositing User: Kremmel, Benjamin
Date Deposited: 17 Jul 2018 04:40
Last Modified: 08 May 2020 08:02

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