Exploring the barriers to data-driven learning in the classroom: a systematic qualitative synthesis

Abstract

In the current study, we conducted a systematic qualitative synthesis of the literature on data-driven learning (DDL) to identify the potential difficulties, barriers, challenges, and obstacles associated with the implementation of DDL in the classroom. We found and gathered a total of 347 primary studies, including individual research articles or reports, published between 2012 and 2021. After a rigorous screening process based on four criteria, 94 target articles were selected and analyzed. These criteria were: (1) inclusion of empirical studies on DDL published between 2012 and 2021, (2) implementation of the DDL approach by instructors for English language learners, (3) utilization of research designs capturing qualitative data on learner and teacher perceptions of DDL, and (4) discussion of challenges and obstacles related to DDL from both learners' and teachers' perspectives. This screening resulted in 295 data segments, which are specific excerpts or portions within these target articles, each referring to one participant's experience and articulated challenges. These data segments were subsequently extracted and coded. The results suggest that the barriers to DDL can be categorized into two core groups: inherent and external factors. Inherent factors relate to the actual tasks involved in DDL, while external factors are connected to the users of this approach. Both categories may impact DDL's effectiveness. The findings imply that situational context and the emotional state of users should also be considered when designing tools, materials, and teaching methodologies for DDL. These insights have implications for both practitioners and researchers and could inform the development of training programs and materials aimed at enhancing the effectiveness of DDL in language learning and teaching.