The teaching and learning processes in education need to be effective. This is something that all parents, teachers and educational scientists can agree on. To help us track the learners’ achievements and educational progress and ultimately show whether the teaching and learning processes are effective, we rely on formative assessment.

Learning analytics has the potential to assist in formative assessment. So far there has not been enough evidence collected to prove this potential support. Thus, many have reservations about the connection between the results of learning analytics and formative assessment models. If the results from learning analytics don’t match well with formative assessment approaches, teachers may be reluctant to trust, understand or use those insights to guide their teaching.

This issue is addressed in a recently published study which introduces a proven model for formative assessment. To investigate how learning analytics can benefit formative assessment the authors conducted a systematic review of 93 articles published between 2011 and 2023.

Using the formative assessment framework, the study shows how learning analytics can enhance this process by linking three key roles: teachers, students as peers and students as self-assessors with the three essential process stages of identifying the learner’s goals, understanding the learner’s current position and determining how to the learner reaches these goals. This study deepens our understanding of how learning analytics align with theoretical principles, which helps guide future research investigations in the field of learning analytics–supported formative assessment. Besides the theoretical insights, this study provides insights into the implementation and enhancement of learning analytics to increase the effectiveness of formative assessment approaches.

–> Feel free to read the full paper:

Banihashem, S. K., Gašević, D., Noroozi, O., Jarodzka, H., Joosten-ten Brinke, D., & Drachsler, H. (2025). Optimizing Formative Assessment with Learning Analytics. Review of Educational Research, 0(0). https://doi.org/10.3102/00346543251370753