Developing and validating an Internet-based battery of Tests of Aptitude for Language Learning (TALL)
Year: 2023
Type: dissertation
Abstract: Measuring language learning aptitude faces theoretical and methodological challenges.First, the development of aptitude batteries has not generally kept pace with changes in theoretical frameworks that conceptualise aptitude constructs pertaining to second language (L2) learning.Second, it is crucial to ascertain the reliability and validity of aptitude batteries prior to conducting aptitude-learning research, yet this step has been surprisingly neglected to date (cf.Bokander & Bylund, 2020).In response to these gaps, an internetbased battery, Tests of Aptitude for Language Learning (TALL), has been developed, informed by the theoretical frameworks of the Stages Approach (Skehan, 2016) and the Phonological/Executive (P/E) Model (Wen, 2016), as well as major existing aptitude batteries.TALL measures four facets of aptitude that represent cognitive abilities involved in the early stages of L2 learning and development: associative memory, phonetic coding ability, language analytic ability, and working memory (specifically, phonological short-term memory and executive control capacity).These abilities are measured by five subtests, i.e., Vocabulary Learning, Sound Discrimination, Language Analysis, Serial Nonwords Recall, and Complex Span Tasks, respectively.TALL employs domain-specific verbal stimuli and has two separate test suites to differentiate the modalities (aural and written) of test items.Initial validation checks were conducted with 165 participants (L1 Chinese undergraduates with L2 English) taking two sessions of tests with items counterbalanced across modality and test session.Results of analyses at the subtest, item, and battery levels suggested that, in general, TALL displayed satisfactory reliability and internal validity for measuring aptitude conceptualised in the theoretical frameworks.Linear mixed-effects modelling analyses revealed significant effects of modality on test results.Multiple regression analyses revealed that aural and written suite of TALL could explain 16% and 19% variance, respectively, of the self-reported L2 proficiency scores.Implications for battery refinement, further scrutiny of validation, utilisation of TALL in aptitude related research, and the potential of TALL as an open research tool are discussed.
Author: Pan, Junlan
Language: English
Subfield: Language and Linguistics
Field: Arts and Humanities
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7037024621