Work

A Bayesian approach to implicit L2 learning: Web-based replication of Williams (2005) and Kim et al. (2023) with underrepresented learners

Year: 2025

Type: article

Abstract: Expanding participation beyond university samples is increasingly seen as key to more inclusive and generalizable SLA research. This study examined the effectiveness of web-based experimentation for L2 grammar learning among adults without post-secondary education—an underrepresented population in the field. Building on Williams (2005) and replicating Kim et al. (2023), we implemented a fully remote, researcher-supervised design to enhance accessibility and participant engagement. Forty-nine participants without college degrees completed a semi-artificial language learning task. Bayesian analyses indicated comparable overall learning outcomes, with greater variability in training accuracy and item reliability in the web-based condition. Crucially, no evidence of implicit learning was found among unaware learners—replicating Kim et al. (2023) and highlighting limits to generalizing such effects to non-traditional populations. These findings underscore the importance of inclusive research designs that expand research access while safeguarding data quality.

Source: Research Methods in Applied Linguistics

DOI: 10.1016/j.rmal.2025.100242

Authors: Kathy Minhye Kim, Michael Bornstein, Xiaoyi Liu, Yongyue Li

Institutions: Boston University, Wheelock College, Western New England University

Language: English

Topic: EFL/ESL Teaching and Learning

Subfield: Language and Linguistics

Field: Arts and Humanities

Domain: Social Sciences

SDGs: Quality education, Reduced inequalities

Open Access status: hybrid

Estimated APC paid: $2,000