Enhancing academic performance and student success through learning analytics-based personalised feedback emails in first-year chemistry

Abstract

Recent developments in digital technologies, including learning analytics are changing educational practices due to the wealth of information available and its utility to inform academic interventions for students. This study investigates the impact of personalised feedback emails on students’ academic performance and student success in large first-year undergraduate chemistry courses. Learning analytics was used to inform and generate feedback emails to students at various timepoints during the semester. The feedback emails to students included an evaluation of their current performance, and advice of support systems and resources to support their learning. We analysed the marks of 6334 students at three timepoints during the semester in addition to their final course grade, and compared academic performance across three years of course offerings (2019–2021). We compared students that did not receive feedback (2019 control groups, n = 2391) with students that did receive feedback (2020–2021 experimental groups, n = 3943). Our findings suggest that students receiving personalised emails during the semester were more likely to pass their first-year chemistry course. Furthermore, our data showed that sending personalised feedback emails fostered higher student success among a greater number of students within the cohort, as well as students' appraisal of the personalised feedback.