Data-Driven Learning in EFL Grammar: Student Attitudes and Teacher Perceptions in Bangladesh

Data-Driven Learning (DDL) has gained increasing attention as an innovative pedagogical approach in English as a Foreign Language (EFL) instruction, particularly in grammar teaching. DDL empowers learners to explore authentic language data from corpora, promoting inductive learning and enhancing grammatical understanding. However, traditional grammar instruction in Bangladesh largely relies on rote memorization and teacher-centered methods, limiting opportunities for students to develop critical thinking and language discovery skills. This discrepancy between traditional methods and the potential benefits of DDL presents a significant challenge for educators seeking to modernize EFL instruction. Therefore, this study investigates student attitudes and teacher perceptions of DDL in grammar instruction using a mixed-method approach. Surveys and semi-structured interviews were conducted with EFL students and teachers at secondary and tertiary levels. The results show that while students demonstrate enthusiasm for DDL’s interactive and discovery-based learning model, teachers express concerns regarding inadequate resources, training, and institutional support for integrating DDL in their classrooms. The findings suggest that for DDL to be successfully implemented in Bangladesh, there is a need for comprehensive teacher training and investment in educational infrastructure. This study contributes to the growing body of literature on DDL and highlights its potential to reshape grammar teaching in EFL contexts, particularly for non-native learners.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-05
DOI
https://doi.org/10.5281/zenodo.14284160
Primary Topic
Educational Assessment and Improvement
Type
article
Field-Weighted Citation Impact
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article

Data-Driven Learning in EFL Grammar: Student Attitudes and Teacher Perceptions in Bangladesh

Zenodo (CERN European Organization for Nuclear Research)
Educational Assessment and Improvement
article

Data-Driven Learning in EFL Grammar: Student Attitudes and Teacher Perceptions in Bangladesh

article en

Abstract

Data-Driven Learning (DDL) has gained increasing attention as an innovative pedagogical approach in English as a Foreign Language (EFL) instruction, particularly in grammar teaching. DDL empowers learners to explore authentic language data from corpora, promoting inductive learning and enhancing grammatical understanding. However, traditional grammar instruction in Bangladesh largely relies on rote memorization and teacher-centered methods, limiting opportunities for students to develop critical thinking and language discovery skills. This discrepancy between traditional methods and the potential benefits of DDL presents a significant challenge for educators seeking to modernize EFL instruction. Therefore, this study investigates student attitudes and teacher perceptions of DDL in grammar instruction using a mixed-method approach. Surveys and semi-structured interviews were conducted with EFL students and teachers at secondary and tertiary levels. The results show that while students demonstrate enthusiasm for DDL’s interactive and discovery-based learning model, teachers express concerns regarding inadequate resources, training, and institutional support for integrating DDL in their classrooms. The findings suggest that for DDL to be successfully implemented in Bangladesh, there is a need for comprehensive teacher training and investment in educational infrastructure. This study contributes to the growing body of literature on DDL and highlights its potential to reshape grammar teaching in EFL contexts, particularly for non-native learners.

Zenodo (CERN European Organization for Nuclear Research)
Northern University of Malaysia (MY)
Quality Education
Openalex Percentile: Top 33%
Educational Assessment and Improvement
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