Description

The "Mathematics Reactivation" project was implemented under the Human Capital Operational Programme (Priority III "High Quality of the Education System"). Its aim was to support upper secondary school students in learning mathematics, particularly those who struggle, including those from small towns or with limited access to tutoring. 349 schools from across Poland participated in the project, along with 13,702 students who participated over three years of upper secondary education.

How data and ICT were used:

• Electronic/e-learning materials allowed for immediate practice after learning a new topic and automatic monitoring of student progress. rezerwip2.ore.edu.pl
• Data on student performance was collected systematically—both through online assignments and by teachers/tutors. This enabled monitoring of which topics were most challenging. resourcesip2.ore.edu.pl
• Teachers were supported by consultants who helped analyze data, identify problem areas, and tailor educational interventions (e.g., additional exercises, catching up) for students who needed them.

Outcomes/Effectiveness:

• Thanks to the project, students from smaller towns or with limited resources had access to a remedial course, which provided equal educational opportunities.
• Students could work at their own pace, using electronic materials and progress monitoring—allowing for faster identification of gaps and intervention before they became a larger problem.
• The project reported significant improvements in topic mastery, a reduction in disparities, and increased student engagement in mathematics.

Why is this case study a good example of the effectiveness of data-driven teaching?

1. Using data for diagnostics and corrections – because the system and teachers received information about which topics students were doing well and which were not, it was possible to respond more quickly to student needs and provide targeted support.
2. Equal educational opportunities – students from smaller towns or with limited access to additional lessons/tutoring received better access to materials and support, reducing the barrier to accessing a quality education.
3. Collaboration between teachers and consultants – not only technology, but also methodological support was important. This demonstrates that implementing technology alone is not sufficient for data-driven learning without appropriate training and support for teachers.
4. Scalability – the project involved a large number of schools and students, demonstrating that a data-driven and e-learning approach can be implemented on a large scale.
5. Cost and time efficiency – thanks to electronic materials and the automation of certain stages (e.g., independent exercises, assessment of selected assignments), resources (e.g., teacher time) were used more efficiently.

Reference Link

https://matematyka-reaktywacja.pwr.edu.pl/oprojekcie.html