Toward More Rigorous and Transparent Online Experimentation in Applied Linguistics

Online experimental methods have become increasingly prevalent in second language (L2) research. This introduction to the special issue on online experimentation in applied linguistics begins by outlining the key challenges that online data collection poses for experimental research, organized around three domains: technology, participant recruitment, and performance-related factors. The first section provides an overview of the contributions to the special issue, which include eight empirical studies, three methodological guidance papers, a conceptual article, and five responses. The second section presents a synthesis of validation reporting practices across a sample of 13 online L2 studies, coded against Rodd's (2024) framework across the three domains. This synthesis reveals that reporting is heavily skewed toward participant performance safeguards, with technology- and recruitment-related safeguards considerably underreported. A further finding is that researchers tend to rely on reactive, back-end measures to address data quality concerns rather than proactive, design-based safeguards. The third section draws on these findings to offer 10 recommendations as a principled framework to guide researchers in designing, conducting, and reporting online L2 experiments more transparently and rigorously.