Abstract
The project aims to explore a data-driven approach to enhance student engagement and achievement in Higher Education (HE),with the ultimate goal of promoting student success. The project utilised a case study approach at the University of Salford, employing data analysis and Machine Learning (ML) techniques to understand corelation between students' engagement and academic performance to support strategy of students support in their learning process. Being a project in progress, this paper delves into the initial phase of our research findings. This phase focuses on the data collected from a pilot module, specifically pertaining to student engagement and progression data. Additionally, the paper presents a prototype of a ML algorithm that aims to facilitate decision-making in the realm of student support. Moving forward, the next stage of the project aims to automate the entire process, spanning from data analysis to student intervention. It aims to use this automation to drive student success throughout their HE journey.
Recommended Citation
Chen, Yun and Han, Kate, "Driving Student Success through a Data-Driven Approach in Higher Education" (2024). UK Academy for Information Systems Conference Proceedings 2024. 4.
https://aisel.aisnet.org/ukais2024/4