Teacher Scaffolding in Data-Driven Learning: An Analysis of Elicitations to Assist Concordance Reading
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Abstract
This study investigates teacher scaffolding in Data-Driven Learning (DDL), focusing on elicitations that aid students’ use of concordances for language learning. Addressing a theory-practice gap in the literature, it explores how specific teacher interactions facilitate inductive reasoning and linguistic generalizations in an EFL context. The analysis draws on classroom interaction data collected from three Thai EFL students during DDL lessons. We coded teacher elicitations using Systemic Functional Grammar’s Transitivity framework, categorizing the data into material, mental, and relational clause types. The clause data was organized into concordance lines for generalizations based on the data-driven principle. The patterns found in relational and mental clauses that were used more frequently by the teacher revealed underlying efforts to engage learners in knowledge induction. Those in material clauses constructively helped learners notice and reason with tendencies in concordances. Through the collective enquiries, the teacher effectively fostered linguistic discovery and rule generalization, despite occasional counterproductive scaffolding due to over-reliance on grammatical terms. The findings highlight the importance of intentional teacher-talk strategies in DDL to support cognitive processing. Future research is invited to explore these dynamics across different linguistic topics and classroom settings.
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