Enhancing inclusivity and equity through a broader understanding of data-driven learning in pre-tertiary education: A mixed-methods systematic review

Abstract

Data-driven learning (DDL) is a significant approach in computer-assisted language learning (CALL), but its adoption in pre-tertiary education is limited, raising concerns about education equity and inclusivity. This study reviews 39 empirical studies published between 1994 and 2023 to assess DDL’s effectiveness, efficiency, learner perceptions. Quantitative findings show a large within-group effect size (d = 1.77) and a medium-to-large between group effect size (d = 0.88). Qualitative findings reveal that most learners (74%) report positive views. This review confirms DDL’s suitability for non-university settings and offers strategies to enhance accessibility, address equity barriers, and promote inclusive practices, ensuring that all pre-tertiary learners, regardless of diverse background or resources, can benefit from DDL.