This edited volume offers critical reflections on an essential component of research method in the field of second language acquisition -- data. Scholars working on diverse areas (e.g., pragmatics, corrective feedback, phonology) and approaches (e.g., corpus linguistics, concept-oriented analyses, variationism) have come together to identify…

This study applied systematic meta-analytic procedures to summarize findings from experimental and quasi-experimental investigations into the effectiveness of using the tools and techniques of corpus linguistics for second language learning or use, here referred to as data-driven learning (DDL). Analysis of 64 separate studies representing 88…

Researchers on bilingual processing can benefit from computational tools developed in artificial intelligence. We show that a normalized Levenshtein distance function can efficiently and reliably simulate bilingual orthographic similarity ratings. Orthographic similarity distributions of cognates and non-cognates were identified across pairs of…

Despite considerable research interest, data-driven learning (DDL) has not become part of mainstream teaching practice. It may be that technical aspects are too daunting for teachers and students, but there seems to be no reason why DDL in its early stages should not eliminate the computer from the equation by using prepared materials on…