Corpora, large collections of computer-searchable texts, have long been used in data-driven learning (DDL) of languages. However, despite growing evidence of DDL effectiveness, teacher uptake has been low. Recent studies propose DDL teacher education models and open access materials, reporting positive learning outcomes and teacher perceptions. However, almost all research has focused on English teaching, and studies on post-course DDL implementation are rare. This study addresses these gaps by evaluating a 16-week DDL teacher education course at a US university attended by graduate student teachers ( n = 7) of English, Spanish, and less commonly taught languages (LCTLs)—Polish, Russian, and Ukrainian. The course covered corpus literacy, corpus-based pedagogy, reflective practice, and empirical DDL research. Using descriptive statistical analysis of post-course surveys and thematic analysis of lesson plans and teaching journals, the study assessed immediate and delayed learning outcomes and participant perceptions. The results indicated high perceived and attested benefits in both academic and pedagogical DDL knowledge, surpassing previous research findings. LCTL teachers used more traditional, printed corpus-based materials focusing on lexico-grammatical features, while English and Spanish teachers expanded DDL to language variation and cultural topics with direct corpus searches. Despite LCTL teachers’ challenges with limited or user-unfriendly corpora, all teachers developed viable DDL proposals, with three participants implementing DDL post-course. Both trainee teachers and their students viewed the DDL approach as novel and demanding but reported superior learning outcomes compared with traditional methods. This study confirms the effectiveness of the proposed corpus-based language pedagogy education model for teachers of diverse languages, including LCTLs.
Nina Vyatkina (Tue,) studied this question.
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