EDUCATION ANALYTICS CASE STUDY

CBC Transition Readiness Analysis

An education analytics project evaluating county-level readiness for Kenya's Competency-Based Curriculum (CBC) by analysing infrastructure, teacher availability and learning resource distribution using Google Sheets, Power BI and Python.

CBC Transition Dashboard

Executive Overview

This education analytics project evaluates CBC implementation readiness across Kenya through infrastructure, staffing, and resource distribution analysis, identifying county-level disparities in preparedness for the Competency-Based Curriculum.

Problem Statement

Kenya's transition to the Competency-Based Curriculum requires adequate infrastructure, teaching capacity and learning resources across all counties. This project assesses how prepared different regions are for CBC implementation and identifies where readiness gaps remain.

Project Objectives

Assess Infrastructure Readiness Evaluate Teacher Availability Analyse Learner-to-Teacher Ratios Identify County-Level Disparities Develop Readiness Framework Provide Evidence-Based Recommendations

Methodology

Data Preparation
Data collection, validation, cleaning and standardization, including handling missing values and transforming data for analysis.


Exploratory Analysis
Descriptive statistics, county-level comparisons and resource distribution assessment.


Dashboard Development
Interactive Power BI visualizations showing readiness indicators by county and comparative analysis dashboards.


Statistical Analysis
Correlation analysis, readiness scoring, and trend identification using Python in Google Colab.

Technology Stack

Google Sheets Power BI Python Google Colab Data Cleaning Readiness Scoring Correlation Analysis

Dashboard Preview

Interactive Power BI dashboards mapping CBC readiness, teacher shortages and digital access across Kenyan counties.

CBC Readiness Kenya Map Dashboard

Teacher Shortage and Digital Access Dashboard

County Detail Dashboard

Python Analysis Highlights

Statistical analysis and modelling outputs from the Google Colab notebooks behind the readiness scoring.

Correlation Matrix

ASAL Boxplot

County Clusters by Teacher Shortage and Learning Outcome

FLANA Distribution: ASAL vs Non-ASAL Counties

Actual vs Predicted FLANA Scores

Top 10 vs Bottom 10 Counties

Key Findings

County Disparities

Readiness (FLANA score) ranges from 51.2% to 72.6% across the 46 counties analysed, averaging 64.2% — a 21-point spread between the most and least prepared counties.


The ASAL Gap

Kenya's 10 ASAL (arid and semi-arid land) counties average a FLANA score of just 56.2%, versus 66.4% for non-ASAL counties — a 10-point readiness gap. FLANA score and overall risk score are strongly correlated (r = -0.90): as readiness drops, risk climbs almost in lockstep.


Teacher Shortages Concentrated in ASAL Counties

All 10 ASAL counties report "Severe" teacher shortages and "Very Low" digital access — a complete overlap. Among the 36 non-ASAL counties, only 7 face severe shortages, and none report very low digital access.


Highest-Risk Counties

Samburu, Mandera, Garissa, Marsabit, Wajir, Tana River, Turkana, West Pokot, Lamu and Isiolo all score the maximum risk rating of 90/100 — and every one of them is an ASAL county. By contrast, Nyeri leads the country in readiness at 72.6%, with a risk score of 0.


Resource Allocation

Of the 46 counties, 17 fall in the "High" risk band and 20 in "Low" risk — but risk is not evenly spread: it is concentrated almost entirely in ASAL regions, pointing to a geographic rather than nationwide resource gap.

Project Outcomes

Assessed CBC readiness across counties Built interactive Power BI dashboards Developed a readiness scoring framework Identified teacher shortage patterns Mapped digital access disparities Delivered evidence-based recommendations

Strategic Recommendations

1. Prioritize Infrastructure Investment

Prioritize infrastructure investments in low-readiness counties.


2. Increase Teacher Recruitment

Increase teacher recruitment and deployment in underserved regions.


3. Improve Resource Distribution

Improve distribution of CBC learning resources.


4. Establish Monitoring Systems

Establish continuous readiness monitoring systems.


5. Support Equitable Implementation

Use data-driven planning to support equitable implementation.

Project Conclusion

This project demonstrates how education analytics can identify readiness gaps across Kenya's counties, providing county governments and education stakeholders with an evidence-based framework to guide infrastructure investment, teacher deployment and resource distribution for CBC implementation.


Limitations & Next Steps: The readiness score is based on available infrastructure and staffing data at a single point in time. Next step: pair the readiness scores with actual CBC exam outcomes once available, to test whether the readiness index actually predicts results.

Project Resources

This case study demonstrates the application of Power BI, Python and Google Sheets to evaluate CBC transition readiness across Kenyan counties and support evidence-based education planning.