Data-Driven Insights from National-Scale Learning Analytics: How Self-Regulated Learning Mitigates Summer Learning Loss

Abstract

Summer Learning Loss (SLL) remains a persistent educational concern. However, prior research offers limited generalizability for policy and practice due to the limited to small-scale controlled settings. This study addresses that gap by analyzing national-scale learning data from 70,677 elementary students, focusing on TALP supported self-regulated learning (SRL) during the summer of 2023 in Taiwan. Using biannual PRIORI-tbt assessments as benchmarks, we examined 6.79 million TALP learning logs to assess engagement patterns and outcomes. Results show that students who used TALP during summer outperformed non-users, with the most significant gains observed among those who engaged for two or more consecutive weeks. These findings highlight effective engagement strategies and optimal intervention timing, offering empirical support for leveraging digital SRL to mitigate SLL.