All research areas
Research Area
Mathematics & Statistics Education
Strong mathematical and statistical skills underpin every engineering and data career. This area studies how students learn these subjects and what helps them succeed. We combine educational data mining, statistical analysis of assessment results, and classroom research to identify students at risk early, improve course design, and support lecturers with evidence instead of intuition, with a focus on the needs of Cambodian higher education.
What we do
- Learning analytics and educational data mining
- Early-warning models for student performance and retention
- Assessment design, item analysis, and exam reliability studies
- Curriculum evaluation for mathematics, statistics, and data science programmes
- Survey design and analysis of student and teaching-quality feedback
- Research on active learning and computational tools in the classroom
Why it matters
- Earlier support for students at risk of failing or dropping out
- Fairer and more reliable exams and assessments
- Evidence-based improvements to courses and programmes
- Stronger mathematical and statistical foundations for engineering graduates
- Practical guidance for lecturers and academic leadership
Core technologies behind it