From Struggle to Strategy: How Low-Stakes Assessments Foster Self-Regulation
Ravshon Otojanov, QMUL
Steve Brant, QMUL
This study investigates whether compulsory, low-stakes formative assessments, supported by learning analytics, can help undergraduate students develop self-regulated learning and improve academic performance. Conducted within an undergraduate economics module at Queen Mary University of London, the randomised controlled study compared a group receiving weekly conditional-access quizzes, email prompts and personalised learning analytics feedback with a control group receiving standard instruction.
Drawing on Zimmerman’s self-regulation framework, the research examines students’ planning, monitoring and evaluation of their learning, alongside engagement indicators and academic outcomes. Preliminary findings from the first cohort show no statistically significant differences between the intervention and control groups in module marks, examination performance, engagement or measured aspects of metacognition. However, student feedback suggests that weekly quizzes encouraged reflection, regular study and greater awareness of learning needs. Evaluative metacognition emerged as a strong predictor of examination performance, while engagement analytics provided additional insight into student learning.
The findings suggest that embedding formative assessment into the weekly learning process offers a practical, scalable approach to supporting self-regulation. Although the small sample limits the conclusions that can be drawn about the intervention’s effectiveness, the study provides a foundation for further research into how assessment design and learning analytics can support student learning in higher education.
Key findings
No statistically significant differences between groups: The study found no statistically significant differences in module marks, final examination results, engagement scores or metacognition measures between students receiving the intervention and those receiving standard instruction.
Positive student perceptions: Qualitative feedback indicated that weekly quizzes helped students identify gaps in their knowledge, reflect on their understanding and maintain a more consistent study routine. Conditional access to subsequent learning materials was also perceived by some students as helping them stay on track.
Evaluation matters for academic performance: Evaluative metacognition—the process of reflecting on learning strategies and their effectiveness—emerged as a strong predictor of examination performance in this study.
Engagement analytics offer additional insights: Engagement indicators, particularly participation in active learning tasks, contributed useful information for understanding and predicting academic outcomes.
A promising, practical approach: The intervention uses existing virtual learning environment tools and can be implemented without specialist technology or substantial additional infrastructure.
Limitations and next steps
The findings are preliminary and based on a small first-cohort sample. Although 54 students were assigned to the two study groups, the survey analysis included 26 students. The study was therefore limited in its ability to detect anything other than large differences between groups. Future work will expand the sample, measure metacognition at multiple points during the semester, explore students’ use of learning analytics feedback in greater depth, and examine whether the findings generalise to other disciplines.
Overall conclusion
The study highlights the potential of integrating compulsory formative assessment and learning analytics into everyday teaching to encourage reflective learning and support student engagement. Further research is needed to establish whether these approaches lead to measurable improvements in academic performance and self-regulation.