Fragmented Weekly Test Data
Multiple instructors maintained separate sheets across a rigid ten-week testing cycle, preventing a unified view of student progress.
Scholarship Student Progress & Learning Performance Intelligence Platform
Developed an interactive Power BI analytics platform for a high-stakes international scholarship program, centralizing fragmented weekly test data and enabling academic leaders to track student growth, compare instructional performance, identify skill gaps, and intervene before students fell behind.
Scholarship Analytics
Longitudinal Progress Tracking
Student-Level Intelligence
Teacher Comparison
Language Skill Analysis
1.
Business Challenge
Student test data was distributed across independently managed weekly spreadsheets, creating serious visibility gaps in a scholarship program where funding, retention, and institutional reputation depended on student success.
Limited Real-Time Visibility
Academic leaders could not quickly identify slipping students, weak cohorts, or underperforming instructional groups.
Risk of Silent Student Failure
Struggling scholarship students could fall behind unnoticed until the program was too advanced for effective intervention.
Inconsistent Teaching Evaluation
Leaders lacked a standardized framework for comparing progress across teachers, classes, and student groups.
Hidden Skill-Specific Weaknesses
Listening, Reading, Speaking, and Writing performance could not be tracked consistently across milestones.
2.
Solution
A structured Power BI reporting solution transformed raw weekly test scores into longitudinal, teacher-level, class-level, group-level, and skill-level intelligence.
Power Query Data Consolidation
Ingested, cleaned, standardized, and unpivoted fragmented Excel test datasets into one analytical structure.
Star-Schema Data Model
Organized students, teachers, classes, groups, tests, weeks, and language attributes for scalable analysis.
Advanced Progress Measures
DAX calculated ST10–ST1 progress, incremental STn–ST1 deltas, milestone growth, and average attribute values.
Three-Level Drill-Down
Teacher → Class → Group navigation supported executive auditing and granular academic review.
Skill-Based Performance Tracking
Listening, Reading, Speaking, and Writing trends were compared across Mock Tests and Sunday Tests.
All Tests Comparison
An interactive trend visual compared weekly performance across all Sunday Tests and instructional cohorts.
Dynamic Academic Filtering
Slicers for teachers, classes, students, and test types enabled focused intervention and side-by-side comparison.
3.
Business Impact
Weekly Tests Tracked
The reporting model preserved the complete Sunday Test sequence from ST1 through ST10.
Core Language Skills Monitored
Listening, Reading, Speaking, and Writing were benchmarked continuously across testing milestones.
Writing Score Growth Quantified
Average Writing performance increased from 1.55 at the Initial Mock Test to 2.32 by Sunday Test 4—a gain of 0.77 points.
Academic Drill-Down Levels
Teacher, Class, and Group analysis connected executive oversight to targeted student support.
Silent Failures Reduced
Centralized progress visibility enabled academic directors to identify struggling students before scholarship cycles concluded.
Teaching Impact Made Measurable
Institutional leaders could compare classes and instructors, identify stronger teaching patterns, and scale successful methods.
Skill-Specific Intervention Enabled
Granular language-attribute analysis exposed where students needed focused academic support.
Standardized Academic Reporting
Disjointed instructor-managed spreadsheets were replaced by one consistent source of performance intelligence.
Quantification note: The 49.7% Writing improvement is calculated from the documented increase from 1.55 to 2.32. No unsupported financial or retention claims were added.
4.
Solution Architecture
Scholarship Learning Analytics Architecture
Instructor Excel FilesWeekly Test Scores
Student & Cohort DataTeachers, Classes, Groups
Skill AttributesListening, Reading, Speaking, Writing
↓↓↓
Power QueryClean, Standardize, Unpivot
→
Star SchemaStructured Academic Model
→
DAX MeasuresProgress, Deltas, Averages
↓
Power BI Scholarship Progress & Learning Performance Suite
Fragmented weekly test records are transformed into a governed model for longitudinal, cohort, teacher, and skill-level analysis.
5.
Analytics Delivery Flow
Collect
Mock and Sunday Test spreadsheets
Prepare
Clean, unpivot, and standardize
Model
Students, teachers, classes, groups, tests
Measure
ST10–ST1, incremental deltas, skill averages
Intervene
Identify risk and guide academic support
The delivery flow converts weekly academic records into targeted intervention and instructional intelligence.
6.
Technology Stack
Power BI DesktopPower BI ServicePower QueryDAXExcelStar SchemaTime-Series Test DeltasAttribute Mean AggregationsHierarchical Drill-DownInteractive Line ChartsDynamic SlicersCross-Filtering
7.
Dashboard Gallery
8.
Project Showcase
Live Power BI Dashboard
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Video Walkthrough
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9.
GitHub Repository
Explore the Scholarship Learning Analytics Project
The repository contains project documentation, dashboard screenshots, Power BI implementation details, and supporting analytical assets.
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