Leveraging Learning Analytics in Formative Assessment: Insights from a Scoping Review of Blended Learning Courses in Higher Education

In recent years, the expansion of advanced digital technologies in the learning field has caused a deep change in educational platforms and revolutionized the tools and systems that support online learning. Within this context, the rapid development of Learning Analytics (LA) in blended and online higher education has transformed assessment practices, enabling personalized feedback and more targeted instructional strategies. This scoping review investigates how LA is integrated into formative assessment practices within blended learning courses in higher education. By analysing 13 selected studies, the review identifies the main techniques, purposes, and roles attributed to LA, such as student profiling, predictive modeling, teacher support, and feedback automation. The restricted number of papers examined could limit the broader applicability of the conclusions. However, findings highlight how LA is increasingly employed to support formative assessment in blended higher education, with methods such as process mining, predictive modeling, and visualization enabling more precise monitoring of student learning and the provision of timely, personalized feedback. Yet, the pedagogical challenge lies in ensuring that these tools are not reduced to mere instruments of control, but are instead leveraged to foster engagement, support teachers' decision-making, and promote more inclusive and meaningful learning experiences.