Jordan Targeting Support for Foundational Skills Using Assessment Data
Case Study
Jordan Targeting Support for Foundational Skills Using Assessment Data
Jordan’s Ministry of Education (MoE) has given foundational reading and numeracy high national attention and priority. Using data-driven decision-making to guarantee that resources reach students, schools, and places most in need has been a major enabler of this effort.
Results of the Early Grade Reading Assessment (EGRA) and Early Grade Mathematics Assessment (EGMA) showed that many students in Grades 2 and 3 struggled with fundamentally reading and math skills. Lot Quality Assurance Sampling (LQAS) simultaneously offered localized defines of learning levels, therefore highlighting significant differences both between regions and between schools.The MoE channeled help and resources toward underprivileged geographic areas and low-performing schools, therefore adopting a targeted strategy instead of a uniform one, through the following:
Leveraging Data to Allocate Resources: LQAS data enabled the identification of “hot spots” whereby students routinely performed below national benchmarks. These schools came first for teacher training, remedial help, and extra instructional materials.
Results from EGRA and EGMA highlight particular ability gaps (e.g., fluency, understanding, number recognition). These deficiencies informed training materials and coaching initiatives, therefore ensuring that teachers in underprivileged schools received targeted, relevant help.
National Planning and Budgeting: Central MoE planners used assessment results to support specific budget allocations.
Monitoring Improvement Over Time: Follow-up assessments served as feedback loops, showing whether resource allocation strategies were having the intended effect and allowing for mid-course corrections, and by identifying trends of improvement.
Outcomes and Lessons Learned: By grounding decisions in robust data, the MoE was able to respond more strategically and equitably, reaching students who were most at risk of falling behind. Early findings revealed improved foundational math and reading skills in selected schools as well as raised awareness among leaders and teachers on the need of data use.
Key Takeaway:
Jordan’s experience highlights the power of assessment data—not just for measuring learning, but for driving targeted resource allocation. Tools like EGRA, EGMA, and LQAS enabled the system to move from reactive to proactive, ensuring that support reached the learners and schools that needed it most