Sampling Bias and the Problem of Generalizability in Applied Linguistics

By Sible J. Andringa, Aline Godfroid. Annual Review of Applied Linguistics, 2020

112 citations recorded by the source corpus.

Abstract In this final contribution to the issue, we discuss the important concept of generalizability and how it relates to applied linguists’ ability to serve language learners of all shades and grades. We provide insight into how biased sampling in Applied Linguistics currently is and how such bias may skew the knowledge that we, applied linguists, are building about second language learning and instruction. For example, our conclusions are often framed as universally-applying, even though the samples that have given rise to them are highly specific and Western, Educated, Industrialized, Rich, and Democratic (WEIRD; Henrich, Heine, & Norenzayan, 2010). We end with a call for research and replication in more diverse contexts and with more diverse samples to promote progress in the field of Applied Linguistics as ARAL celebrates its 40th anniversary.

Subfields: Language and Linguistics

View Paper: https://www.semanticscholar.org/paper/67e59bda9d8b824585ddffebee852243106ca55f

Citations in the corpus

• Engagement in language learning: A systematic review of 20 years of research methods and definitions (2021, unknown): “In line with recent L2 research syntheses (see, for example, Andringa & Godfroid, 2020) we restricted our analysis to reports published in L2 journals in the Web of Science’s Social Science Citation Index (SSCI) as these journals have been observed to present high-quality research (for a rationale…”