# Songea Girls High School: A Five-Year Data-Driven Analysis of NECTA Performance (2014–2019)
This case study analyzes academic trends at Songea Girls High School using NECTA A-Level exam data (ACSEE) from 2014 to 2019. The dataset was compiled by Yusuph and made publicly available on Kaggle: NECTA Test Results Dataset.
As a graduate of the Songea Girls class of 2018 and now a data scientist, I revisited the performance data of my former school to understand long-term academic trends and uncover areas of improvement. The project simulates what it would be like to consult for an NGO focused on enhancing educational outcomes for girls in Tanzania.
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## Objectives
- Analyze subject group performance across five academic years
- Identify top-performing subjects
- Track student enrollment by subject combination
- Evaluate performance trends per subject combination
- Estimate changes in total student participation over time
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## Assumptions
- Grading standards were consistent across all years (2014–2019)
- Subject scores are proxies for both student comprehension and curriculum delivery quality
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## Guiding Questions
- How strong was performance in Science and Arts over time?
- How did the class of 2018 compare to other years?
- Which subject groups need targeted support from administrators or education partners?
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## Analytical Approach
- Merged and cleaned yearly NECTA ACSEE data using R
- Transformed wide-format datasets into long-form for flexible analysis
- Grouped subjects into five categories: Science, Math, Languages, Arts, and Business
- Created plots to visualize academic performance and enrollment patterns
- Focused exclusively on Songea Girls' data using filtering techniques and visual breakdowns
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## Key Insights
### Subject Group Performance
- **Languages** improved steadily, peaking in 2019.
- **Science and Math** had moderate results, with a performance dip in 2016.
- A consistent decline was observed across all groups in 2016, l …