DepEd Enrollment Data 2017-2025: Comprehensive 360-Degree Statistical Audit

Analyze 8 years of Philippine public school enrollment data. Discover trends in gender parity, SHS dynamics, regional inequality, and resource ratios across 243 divisions.

Executive Summary

This comprehensive audit provides a complete 360-degree statistical analysis of Philippine Department of Education (DepEd) enrollment data, spanning eight school years from SY 2017-18 to SY 2024-25. The analysis encompasses 16 distinct analytical modules (A through P), examining enrollment trends, gender parity, internal efficiency, inequality metrics, Senior High School dynamics, resource allocation, and gross enrollment rates.

Dataset Overview

Metric	Value
Total Records	487,221
Total Cumulative Enrollment (8 years)	215,424,288
Regions Covered	20
Divisions Covered	243
School Years Analyzed	8 (2017-18 to 2024-25)

Key Findings at a Glance

Declining Total Enrollment: National enrollment peaked at 27.79 million in SY 2022-23 before declining to 26.40 million in SY 2024-25
Gender Disparity: 15 of 19 regions show male-favoring gender disparity (GPI < 0.97)
SHS Academic Track Dominance: Academic track increased from 61.92% to 70.02% of SHS enrollment
High Inequality: 97% of divisions classified as "High Inequality" by Gini coefficient
Resource Gaps: NCR has highest classroom-learner ratio (55.1) while CAR has lowest (24.1)

A. Trends & Growth Analysis

National Enrollment Trends

Table A.1 presents the national enrollment figures across all education levels from SY 2017-18 to SY 2024-25.

Table A.1: National Enrollment by Level and Year

School Year	Total	Elementary	JHS	SHS	Schools	Total Growth (%)
2017-18	26,311,900	15,752,100	7,826,410	2,733,460	61,563	—
2018-19	27,018,500	15,675,000	8,320,630	3,022,840	61,916	+2.69
2019-20	27,030,400	15,332,700	8,503,650	3,194,040	61,923	+0.04
2020-21	26,227,000	14,650,800	8,339,390	3,236,830	60,957	-2.97
2021-22	27,560,700	14,978,000	8,757,960	3,824,710	60,429	+5.08
2022-23	27,794,300	15,188,400	8,426,200	4,179,640	60,137	+0.85
2023-24	27,081,300	15,202,000	7,749,260	4,130,080	60,167	-2.57
2024-25	26,400,200	14,748,800	7,665,610	3,985,810	60,129	-2.52

The data reveals a cyclical pattern in national enrollment. The COVID-19 pandemic caused a 2.97% decline in SY 2020-21, followed by a strong 5.08% recovery in SY 2021-22. However, enrollment has declined for two consecutive years since 2022-23, suggesting structural demographic shifts beyond pandemic effects. Senior High School shows the most dramatic growth trajectory, increasing from 2.73 million to 3.99 million (+45.8%) over the period.

Line chart showing national enrollment trends by education level from 2017-18 to 2024-25 — Figure A.1: National Enrollment by Level (SY 2017-18 to 2024-25). Elementary maintains the largest share while SHS shows strongest growth trajectory.

Bar chart showing total national enrollment by school year — Figure A.2: Total National Enrollment (SY 2017-18 to 2024-25). Peak enrollment of 27.79 million reached in SY 2022-23.

Year-over-Year Growth Rates

Regional Compound Annual Growth Rate (CAGR)

Table A.2: Regional CAGR (2017-18 to 2024-25)

Region	CAGR (%)	Interpretation
Region IV-A (CALABARZON)	+0.69	Highest sustainable growth
Region X (Northern Mindanao)	+0.46	Moderate growth
Region XI (Davao)	+0.35	Moderate growth
Region III (Central Luzon)	+0.35	Moderate growth
NCR	-0.53	Declining enrollment
Region VII (Central Visayas)	-2.81	Significant decline
Region VI (Western Visayas)	-8.27	Severe decline

Note: BARMM, PSO, and NIR show infinite CAGR due to data availability starting mid-period.

Horizontal bar chart showing regional CAGR with top 10 and bottom 10 regions — Figure A.4: Regional CAGR: Top 10 & Bottom 10. Region IV-A leads growth while Region VI shows severe 8.27% annual decline.

B. Gender Parity Analysis

The Gender Parity Index (GPI) measures the ratio of female to male enrollment. A value of 1.0 indicates perfect parity, while values below 0.97 or above 1.03 indicate gender disparity.

Table B.1: Gender Parity Index by Region (SY 2024-25)

Region	Male Enrollment	Female Enrollment	GPI	Status
Region VI	571,485	533,122	0.933	Disparity
Region VII	855,653	805,316	0.941	Disparity
Region I	617,064	581,227	0.942	Disparity
Region V	858,889	813,114	0.947	Disparity
Region IV-A	1,985,630	1,886,130	0.950	Disparity
PSO	12,605	12,250	0.972	Balanced
Region XII	582,369	567,860	0.975	Balanced
Region IX	516,583	504,814	0.977	Balanced
BARMM	527,107	557,023	1.057	Disparity

The analysis reveals a consistent pattern of male-favoring gender disparity across 15 of 19 regions. BARMM is the only region showing female-favoring disparity (GPI = 1.057). Only three regions (PSO, Region XII, Region IX) achieve gender balance. This systematic under-enrollment of females warrants targeted interventions, particularly in Regions VI, VII, and I where disparities are most pronounced.

Horizontal bar chart showing Gender Parity Index by region with parity thresholds — Figure B.1: Gender Parity Index by Region (SY 2024-25). 15 of 19 regions show male-favoring disparity (GPI < 0.97).

Scatter plot comparing male vs female enrollment by region — Figure B.2: Male vs Female Enrollment by Region (SY 2024-25). Points below the parity line indicate male-favoring regions.

C. Internal Efficiency - Flow Analysis

This section analyzes transition rates (movement between levels) and retention rates (continuation within levels) following DepEd Technical Notes methodology.

Note: These are apparent rates calculated without repeater data. True transition rates per DepEd formula require: Transition Rate = (New Entrants in Grade N, SY X) / (Enrollment in Grade N-1, SY X-1) × 100.

Transition Rate Summary

Table C.1: Average Transition Rates (8-Year Mean)

Transition	Average Rate (%)	Interpretation
Kindergarten → Grade 1	102.13	Above capacity (includes late entrants)
Grade 3 → Grade 4	98.96	High retention
Grade 6 → Grade 7	98.09	Strong elementary-to-JHS transition
Grade 10 → Grade 11	99.55	Excellent JHS-to-SHS transition

Transition Rates: Grade 6 → Grade 7 (Elementary to JHS)

Table C.2: G6 to G7 Transition by Year

From Year	To Year	G6 Enrollment	G7 Enrollment	Transition Rate (%)
2017-18	2018-19	2,485,840	2,447,556	98.46
2018-19	2019-20	2,297,486	2,287,310	99.56
2019-20	2020-21	2,259,667	2,096,738	92.79
2020-21	2021-22	2,115,040	2,137,995	101.09
2021-22	2022-23	2,046,708	2,037,475	99.55
2022-23	2023-24	1,862,909	1,808,212	97.06
2023-24	2024-25	2,183,355	2,141,724	98.09

The G6→G7 transition shows high efficiency at 98.09% average, indicating minimal dropout at the elementary-to-JHS transition point. The pandemic caused a notable dip to 92.79% for the 2019-20 to 2020-21 transition, followed by a compensatory surge to 101.09% as returning learners enrolled.

Line chart showing Kindergarten to Grade 1 transition rates over time — Figure C.1: Apparent Transition Rate: Kindergarten → Grade 1. Rates above 100% indicate influx of late entrants.

Line chart showing Grade 6 to Grade 7 transition rates — Figure C.2: Apparent Transition Rate: Grade 6 → Grade 7. Pandemic impact visible in 2019-20 to 2020-21 dip.

Line chart showing Grade 10 to Grade 11 transition rates — Figure C.3: Apparent Transition Rate: Grade 10 → Grade 11. Near-perfect transition to Senior High School.

Retention Rate Summary

Table C.3: Average Retention Rates by Level

Level	Average Rate (%)	Interpretation
Elementary (G1-G5 → G2-G6)	98.95	Excellent retention
JHS (G7-G9 → G8-G10)	96.49	Good retention
SHS (G11 → G12)	93.14	Moderate retention

Retention rates decrease progressively from Elementary (98.95%) to SHS (93.14%), indicating increasing dropout pressure at higher levels. The 6.86 percentage point gap between Elementary and SHS retention warrants targeted intervention programs for senior high school students.

Line chart showing elementary school retention rates — Figure C.4: Elementary Retention Rate (G1-G5 → G2-G6). Consistently high retention above 97%.

Line chart showing Senior High School retention rates — Figure C.5: SHS Retention Rate (G11 → G12). Lowest retention among all levels at 93.14% average.

D. Inequality Analysis - Gini Coefficient

The Gini coefficient measures enrollment inequality within divisions, ranging from 0 (perfect equality) to 1 (maximum inequality). Values above 0.4 indicate "High Inequality."

Table D.1: Gini Coefficient by Division (Top 20)

Division	Gini Coefficient	School Count	Avg Enrollment	Inequality Level
Antipolo City	0.726	226	1,000	High
Bacoor City	0.686	172	696	High
Bacolod City	0.681	199	735	High
Angeles City	0.629	122	940	High
Balanga City	0.609	41	731	High
Antique	0.588	609	251	High
Baguio City	0.586	154	583	High
Aklan	0.572	472	305	High
Abra	0.563	351	162	High

97% of divisions are classified as "High Inequality" (Gini > 0.4), indicating significant enrollment concentration in larger schools while numerous small schools serve relatively few students. Urban divisions (Antipolo City, Bacoor City, Bacolod City) show the highest inequality, reflecting the presence of both mega-schools and small neighborhood schools. This distribution pattern has implications for resource allocation and school consolidation policies.

Horizontal bar chart showing Gini coefficients for top 30 divisions — Figure D.1: Top 30 Divisions: Highest Gini Coefficient (SY 2024-25). Urban centers show highest enrollment inequality.

Histogram showing distribution of Gini coefficients across all divisions — Figure D.2: Distribution of Gini Coefficients Across Divisions. Mean Gini of 0.54 indicates systemic high inequality.

E. Senior High School Dynamics

Track Preference Trends

Table E.1: SHS Track Distribution by Year

School Year	Academic	TVL	Arts & Sports	Total SHS	Academic (%)	TVL (%)
2017-18	1,692,592	1,025,907	14,961	2,733,460	61.92	37.53
2018-19	1,918,540	1,085,926	18,375	3,022,841	63.47	35.92
2020-21	2,225,468	993,856	17,503	3,236,827	68.75	30.70
2022-23	2,947,371	1,210,330	21,943	4,179,644	70.52	28.96
2024-25	2,790,623	1,168,349	26,755	3,985,727	70.02	29.31

The Academic track has grown from 61.92% to 70.02% of SHS enrollment, while TVL has declined from 37.53% to 29.31%. This 8-percentage point shift toward academic tracks may indicate changing student/parent preferences for college-preparatory education over technical-vocational pathways. Arts & Sports remains marginal at less than 1% of total enrollment.

Chi-Square Test: STEM vs HUMSS Preference Shift

Table E.2: Chi-Square Test Results

Test	Comparison	Chi² Statistic	p-value	Significant
Chi-Square Test of Independence	STEM vs HUMSS: 2017-18 vs 2024-25	37,915.2	< 0.001	Yes

The highly significant chi-square statistic (χ² = 37,915.2, p < 0.001) confirms a fundamental shift in strand preferences over the eight-year period. HUMSS has surpassed STEM as the leading academic strand, reflecting evolving student interests and possibly career outlook perceptions.

Line chart showing SHS track preference trends over time — Figure E.1: SHS Track Preference Trends (% Distribution). Academic track rose from 62% to 70% over eight years.

Pie chart showing SHS strand distribution — Figure E.2: SHS Strand Distribution (SY 2024-25). TVL leads (29.3%), followed by HUMSS (27.2%) and STEM (19.7%).

F. Anomaly Detection

Z-score analysis identifies schools with enrollment deviations exceeding 3 standard deviations from their historical mean.

Findings: No significant anomalies (|Z| > 3) were detected among schools with 3+ years of enrollment history. This indicates stable enrollment patterns without extreme year-to-year fluctuations at the school level.

Histogram showing Z-score distribution for all schools — Figure F.1: Distribution of Enrollment Z-Scores (SY 2024-25). Normal distribution centered at zero with threshold lines at ±3.

G. Cohort Survival Analysis

Average Elementary Survival Rates

Table G.1: Elementary Survival by Grade Transition

Grade Transition	Avg Survival Rate (%)
G5 → G6	98.63
G4 → G5	98.95
G3 → G4	98.96
G1 → G2	98.98
G2 → G3	99.28

Average JHS Survival Rates

Table G.2: JHS Survival by Grade Transition

Grade Transition	Avg Survival Rate (%)
G9 → G10	95.82
G8 → G9	96.32
G7 → G8	97.31

Elementary survival rates are consistently above 98%, indicating excellent grade-to-grade progression. JHS shows progressive decline from G7→G8 (97.31%) to G9→G10 (95.82%), suggesting increasing dropout pressure as students approach the junior high school exit point. The 2.49 percentage point difference warrants targeted retention interventions for Grade 9-10 students.

Bar chart showing average elementary survival rates by grade transition — Figure G.1: Average Elementary Survival Rates (8-Year Mean). All transitions exceed 98% survival.

Bar chart showing average JHS survival rates by grade transition — Figure G.2: Average JHS Survival Rates (8-Year Mean). G9→G10 shows lowest survival at 95.82%.

H. School Size Distribution

Table H.1: School Distribution by Size Category (SY 2024-25)

Size Category	School Count	Total Enrollment	School (%)	Enrollment (%)	Avg Size
Very Small (<50)	6,005	165,860	9.99	0.63	28
Small (50-149)	16,827	1,677,040	28.00	6.35	100
Medium (150-499)	24,081	6,684,130	40.06	25.32	278
Large (500-999)	7,210	4,992,280	12.00	18.91	692
Very Large (1000-1999)	3,762	5,197,840	6.26	19.69	1,382
Mega (2000+)	2,220	7,683,030	3.69	29.10	3,461

Table H.2: School Enrollment Statistics

Statistic	Value
Mean	439
Median	206
Std Dev	756
Min	1
Max	17,064
Q1	103
Q3	443
IQR	340

The distribution is highly skewed (Mean = 439, Median = 206), with a small number of mega-schools (3.69% of schools) serving 29.10% of all learners. Meanwhile, 37.99% of schools are classified as "Very Small" or "Small" (<150 students), collectively serving only 6.98% of enrollment. This highly right-skewed distribution has significant implications for resource allocation and potential school consolidation policies.

Bar chart showing number of schools by size category — Figure H.1: Number of Schools by Size Category. Medium-sized schools (150-499) are most common at 40%.

Histogram showing school enrollment distribution — Figure H.2: School Enrollment Distribution. Right-skewed distribution with mean (439) exceeding median (206).

I. Correlation Analysis

Table I.1: Correlation Matrix - Enrollment Metrics

	ES Total	JHS Total	SHS Total	Male Total	Female Total	Total Enrollment
ES Total	1.000	-0.093	-0.088	0.548	0.513	0.532
JHS Total	-0.093	1.000	0.593	0.735	0.751	0.745
SHS Total	-0.088	0.593	1.000	0.629	0.664	0.649

Table I.2: Correlation Significance Tests

Variable Pair	Pearson r	p-value	Significant
ES vs JHS	0.989	< 0.001	Yes
JHS vs SHS	0.995	< 0.001	Yes
School Count vs Total Enrollment	0.771	< 0.001	Yes

Heatmap showing correlation matrix of enrollment metrics — Figure I.1: Correlation Matrix: Enrollment Metrics. Strong correlations between gender totals and level-specific enrollments.

J. Grade-Level Pyramid

Table J.1: Enrollment by Grade and Gender (SY 2024-25)

Grade	Male	Female	Total	Gender Ratio (F/M)
K	945,359	881,899	1,827,260	0.933
G1	1,077,850	992,511	2,070,360	0.921
G6	1,159,030	1,116,330	2,275,350	0.963
G7	1,091,060	1,050,660	2,141,720	0.963
G9	931,270	936,244	1,867,510	1.005
G10	939,840	965,179	1,905,020	1.027
G11	1,012,890	1,028,710	2,041,600	1.016
G12	964,324	979,887	1,944,210	1.016

The gender ratio shifts from male-dominated at lower grades (K: 0.933, G1: 0.921) to female-dominated at higher grades (G10: 1.027, G11-12: 1.016). This crossover occurs around Grade 9 (1.005), suggesting either higher male dropout rates in upper grades or delayed female enrollment in higher education levels.

Population pyramid showing enrollment by grade and gender — Figure J.1: Enrollment Pyramid by Grade & Gender. Gender ratio shifts from male-dominated (lower grades) to female-dominated (upper grades).

K. Public vs Private Analysis

Table K.1: Market Share by Sector

School Year	Public (%)	Private (%)	SUC/LUC (%)	PSO (%)
2017-18	83.98	15.45	0.57	—
2020-21	86.60	12.87	0.45	0.08
2024-25	85.39	14.21	0.31	0.09

Table K.2: Mann-Whitney U Test

Test	Comparison	U Statistic	p-value	Significant
Mann-Whitney U Test	Public vs Private School Sizes	375,345,215	< 0.001	Yes

Public schools dominate the education sector with 85.39% market share in SY 2024-25. The pandemic temporarily increased public school share to 86.60% in SY 2020-21 as families shifted from private to public education. The Mann-Whitney test confirms a statistically significant difference in school size distributions between sectors, with public schools generally larger than private counterparts.

Line chart showing market share trends by sector — Figure K.1: Market Share Trends (% of Total Enrollment). Public sector maintains 85%+ share throughout the period.

L. Enhanced SHS Analysis - Gender by Strand

Table L.1: Gender Distribution by SHS Strand (SY 2024-25)

Strand	Male	Female	Total	Male (%)	Female (%)	Gender Ratio (F/M)
TVL	719,169	449,180	1,168,349	61.55	38.45	0.625
HUMSS	504,583	580,992	1,085,575	46.48	53.52	1.151
STEM	357,053	429,658	786,711	45.39	54.61	1.203
GAS	242,438	258,477	500,915	48.40	51.60	1.066
ABM	135,708	276,661	412,369	32.91	67.09	2.039
MARITIME	4,737	316	5,053	93.75	6.25	0.067

Significant gender segregation exists across strands:

Male-dominated: TVL (61.55% male), Maritime (93.75% male), Sports (71.94% male)
Female-dominated: ABM (67.09% female), Arts (57.64% female), STEM (54.61% female), HUMSS (53.52% female)

The ABM strand shows the most extreme gender imbalance with females outnumbering males 2:1. Notably, STEM is female-dominated, contrary to common assumptions about STEM gender gaps.

Stacked bar chart showing gender distribution by SHS strand — Figure L.1: Gender Distribution by SHS Strand. TVL and Maritime are male-dominated; ABM shows 2:1 female preference.

Bar chart showing gender ratio by strand — Figure L.2: Gender Ratio (Female/Male) by Strand. Parity line at 1.0; ABM shows highest female preference at 2.039.

M. Volatility & Stability Analysis

Table M.1: Regional Enrollment Volatility (Coefficient of Variation)

Region	Mean Enrollment	Std Dev	CV (%)	Min	Max	Range
PSO	20,402	3,780	18.53	13,492	24,855	11,363
Region VI	1,935,400	337,073	17.42	1,104,610	2,104,060	999,453
BARMM	1,004,250	97,874	9.75	870,322	1,086,030	215,705
Region IV-A	3,838,640	117,166	3.05	3,662,580	3,994,310	331,731
NCR	2,836,840	86,812	3.06	2,670,620	2,944,980	274,356

PSO (Philippine Schools Overseas) shows highest volatility (CV = 18.53%) due to its small scale and sensitivity to overseas Filipino population movements. Region VI shows concerning volatility (CV = 17.42%), reflecting the severe enrollment decline noted in the CAGR analysis. Large Metro regions (NCR, Region IV-A) exhibit the most stable enrollment patterns (CV ≈ 3%).

Bar chart showing top 15 most volatile regions by CV — Figure M.1: Top 15 Most Volatile Regions (CV%). PSO and Region VI show highest enrollment volatility.

Heatmap showing enrollment stability for top 10 regions over time — Figure M.2: Enrollment Stability: Top 10 Regions Over Time. Darker colors indicate higher enrollment.

N. Statistical Tests Summary

Table N.1: Comprehensive Statistical Tests

Test	Hypothesis	Statistic	p-value	Result	Interpretation
Kruskal-Wallis H	Enrollment distributions differ across regions	H = 781.03	< 0.001	Reject H₀	Significant differences exist
Normality Test	Enrollment follows normal distribution	k² = 64,971.72	< 0.001	Reject H₀	Non-normal (Skew=5.49, Kurt=47.76)
Paired t-test	Male and female enrollments differ	t = 35.18	< 0.001	Reject H₀	Significant gender difference
Mann-Whitney U	Public and private school sizes differ	U = 375,345,215	< 0.001	Reject H₀	Significant size difference

All statistical tests confirm significant differences in enrollment patterns across:

Regions: The Kruskal-Wallis test (H = 781.03) confirms heterogeneous enrollment distributions
Distribution: Enrollment is highly non-normal with positive skew (5.49) and excess kurtosis (47.76)
Gender: Males systematically outnumber females in aggregate enrollment
Sector: Public and private schools serve fundamentally different population segments

O. Resource Ratios (SY 2023-24 Public Schools)

Note: This analysis is based on SY 2023-24 data only and includes only Public Schools.

Table O.1: Summary of Resource-Learner Ratios

Indicator	National Ratio	Schools Analyzed	Median School Ratio
Teacher-Learner Ratio	25.5	47,674	22.7
Classroom-Learner Ratio	35.1	46,939	27.2
Toilet-Learner Ratio	27.5	46,454	21.7
Computer-Learner Ratio	10.4	36,040	23.1

Teacher-Learner Ratio by Region

Table O.2: Regional Teacher-Learner Ratio

Region	Total Enrollment	Total Teachers	Schools	TLR
BARMM	911,221	29,767	2,591	30.6
Region IV-A	3,179,220	107,120	3,550	29.7
NCR	2,094,090	76,233	822	27.5
CAR	357,504	18,447	1,841	19.4

The national TLR of 25.5 aligns with DepEd standards, but significant regional disparities exist. BARMM has the highest TLR (30.6), indicating teacher shortages relative to enrollment. CAR has the lowest TLR (19.4), reflecting better teacher distribution.

Bar chart showing national resource-learner ratios — Figure O.1: SY 2023-24 Public Schools: Resource-Learner Ratios. Classroom ratio (35.1) highest among all resources.

Horizontal bar chart showing TLR by region — Figure O.2: Teacher-Learner Ratio by Region. BARMM highest at 30.6; CAR lowest at 19.4.

Classroom-Learner Ratio by Region

Table O.3: Regional Classroom-Learner Ratio

Region	Total Enrollment	Total Classrooms	Schools	CLR
NCR	2,088,240	37,880	816	55.1
BARMM	870,897	18,390	2,410	47.4
Region IV-A	3,181,250	70,615	3,541	45.1
CAR	353,387	14,648	1,772	24.1

NCR faces severe classroom shortage with a CLR of 55.1—meaning 55 students share each instructional room on average. This exceeds DepEd's recommended 35-student class size. CAR (24.1) and Region II (27.5) show more favorable ratios.

Horizontal bar chart showing CLR by region — Figure O.3: Classroom-Learner Ratio by Region. NCR critical at 55.1; dashed line shows 35-student standard.

Computer-Learner Ratio by Region

Table O.4: Regional Computer-Learner Ratio

Region	Total Enrollment	Total Computers	Schools	ComLR
BARMM	539,694	27,853	1,275	19.4
Region V	1,348,070	69,315	3,015	19.4
NCR	2,008,640	435,091	785	4.6
CAR	319,999	41,458	1,507	7.7

NCR has the best computer availability (4.6 students per computer), while BARMM and Region V share the worst ratio (19.4). Digital divide is evident between urban and rural regions.

Horizontal bar chart showing computer-learner ratio by region — Figure O.4: Computer-Learner Ratio by Region. NCR leads at 4.6; BARMM and Region V lag at 19.4.

P. Gross Enrollment Rate (SY 2023-24 Public Schools)

Note: GER is calculated using population estimates from PSA 5-year age groups. Single-year populations are estimated assuming uniform distribution within age groups.

Data Sources

Population Data:

Source: Philippine Statistics Authority (PSA)
Dataset: Philippines - Subnational Population Statistics (OCHA HDX)
Reference: 2023 projected population based on Census of Population and Housing

Enrollment Data:

Source: DepEd Learner Information System (LIS)
Reference: Beginning of School Year (BOSY) enrollment, SY 2023-24

NIR Note: Negros Island Region (RA 12000) is excluded from GER analysis as PSA age-group data is pending.

Table P.1: National Gross Enrollment Rates

Level	GER (%)	Interpretation
Kindergarten	82.3	Moderate access
Elementary (G1-6)	91.2	High access
K to Grade 6	89.9	Moderate access
Junior High (G7-10)	76.7	Moderate access
Senior High (G11-12)	63.0	Low access
K to 12	82.0	Moderate access

Public school GER shows progressive decline by level:

Elementary shows high access at 91.2%, approaching universal coverage
JHS drops to 76.7%, indicating 23.3% of the age-appropriate population is not enrolled in public schools (some in private)
SHS shows lowest coverage at 63.0%, suggesting significant gaps in senior high access

Table P.2: Regional Gross Enrollment Rates (K-12)

Region	Schools	GER Kinder	GER Elementary	GER JHS	GER SHS	GER K-12
Region IX	2,546	97.0	106.1	85.0	74.2	94.2
CARAGA	2,099	87.5	101.3	84.8	78.0	92.0
Region VI	4,057	78.5	97.2	88.1	88.4	91.6
BARMM	2,603	98.2	84.9	45.2	31.1	67.3
NCR	828	67.4	71.9	67.7	34.6	64.9

Interpretation:

Region IX leads with highest K-12 GER (94.2%), indicating near-universal public school coverage
BARMM shows concerning pattern: high Kindergarten enrollment (98.2%) but severe drop-off in JHS (45.2%) and SHS (31.1%)
NCR has lowest overall GER (64.9%), largely explained by high private school enrollment in Metro Manila

Bar chart showing national GER by education level — Figure P.1: SY 2023-24 Public Schools: Gross Enrollment Rate by Level. Progressive decline from Elementary (91.2%) to SHS (63.0%).

Horizontal bar chart showing K-12 GER by region — Figure P.2: K-12 Gross Enrollment Rate by Region. Region IX leads at 94.2%; NCR lowest at 64.9%.

Heatmap showing GER by region and education level — Figure P.3: Gross Enrollment Rate Heatmap. BARMM shows critical SHS access gap (31.1%).

Methodology

Statistical Methods Applied

Method	Application	Section
Compound Annual Growth Rate (CAGR)	Regional enrollment trends	A
Gender Parity Index (GPI)	Gender equity analysis	B
Transition Rate	Cross-level movement	C
Retention Rate	Intra-level continuation	C
Gini Coefficient	Enrollment inequality	D
Chi-Square Test of Independence	SHS track preference shifts	E
Z-Score Analysis	Anomaly detection	F
Cohort Survival Rates	Grade progression	G
Pearson Correlation	Variable relationships	I
Kruskal-Wallis H Test	Regional distribution differences	N
D'Agostino-Pearson Normality Test	Distribution assessment	N
Paired t-test	Gender enrollment comparison	N
Mann-Whitney U Test	Sector size comparison	K, N
Coefficient of Variation (CV)	Volatility measurement	M
Gross Enrollment Rate (GER)	Access indicators	P

Appendix A: Chart Index

Figure	Description	Filename
A.1	National Enrollment by Level	01a_national_enrollment_by_level.png
A.2	Total National Enrollment	01b_total_national_enrollment.png
A.3	Year-over-Year Growth Rates	01c_yoy_growth_rates.png
A.4	Regional CAGR	01d_regional_cagr.png
B.1	GPI by Region	02a_gpi_by_region.png
B.2	Male vs Female Enrollment	02b_male_vs_female_enrollment.png
C.1	Transition K to G1	03a_transition_k_g1.png
C.2	Transition G6 to G7	03c_transition_g6_g7.png
C.3	Transition G10 to G11	03d_transition_g10_g11.png
C.4	Retention Elementary	03e_retention_es.png
C.5	Retention SHS	03g_retention_shs.png
D.1	Gini by Division	04a_gini_by_division.png
D.2	Gini Distribution	04b_gini_distribution.png
E.1	SHS Track Trends	05a_shs_track_trends.png
E.2	Strand Distribution	05c_strand_distribution.png
F.1	Z-Score Distribution	06a_zscore_distribution.png
G.1	Elementary Survival Rates	07a_es_survival_rates.png
G.2	JHS Survival Rates	07b_jhs_survival_rates.png
H.1	Schools by Size Category	08a_schools_by_size_category.png
H.2	Enrollment Histogram	08b_enrollment_histogram.png
I.1	Correlation Heatmap	09a_correlation_heatmap.png
J.1	Enrollment Pyramid	10a_enrollment_pyramid.png
K.1	Market Share Trends	11a_market_share_trends.png
L.1	Gender by Strand	12a_gender_by_strand.png
L.2	Gender Ratio by Strand	12b_gender_ratio_by_strand.png
M.1	Regional Volatility	13a_regional_volatility.png
M.2	Stability Heatmap	13c_stability_heatmap.png
O.1	Resource Ratios National	15a_resource_ratios_national.png
O.2	Teacher-Learner by Region	15b_teacher_learner_by_region.png
O.3	Classroom-Learner by Region	15c_classroom_learner_by_region.png
O.4	Computer-Learner by Region	15e_computer_learner_by_region.png
P.1	GER National by Level	16a_ger_national_by_level.png
P.2	GER K-12 by Region	16b_ger_k12_by_region.png
P.3	GER Heatmap	16c_ger_heatmap.png

Appendix B: Statistical Methods Summary

Method	Formula/Description	Use Case
CAGR	((End Value / Start Value)^(1/n) - 1) × 100	Long-term growth trends
GPI	Female Enrollment / Male Enrollment	Gender equity measurement
Transition Rate	(Grade N Enrollment, SY X) / (Grade N-1 Enrollment, SY X-1) × 100	Cross-level flow
Retention Rate	(EnrollmentGrades N+1 to M, SY X) / (EnrollmentGrades N to M-1, SY X-1) × 100	Within-level continuation
Gini Coefficient	(2 × Σ(i × xi)) / (n × Σxi) - (n+1)/n	Inequality measurement
Chi-Square	χ² = Σ((O-E)²/E)	Independence testing
Z-Score	(x - μ) / σ	Anomaly detection
Pearson r	Σ((x-x̄)(y-ȳ)) / √(Σ(x-x̄)² × Σ(y-ȳ)²)	Linear correlation
Kruskal-Wallis H	Non-parametric ANOVA	Group distribution comparison
Mann-Whitney U	Rank-based comparison	Two-group difference
CV	(σ / μ) × 100	Relative volatility
GER	(Enrollment all ages / Population official age group) × 100	Education access

Technical Notes

Data Sources

Source	System	Coverage	Period
Learner Information System (LIS)	DepEd	Enrollment data	SY 2017-18 to 2024-25
Basic Education Information System (BEIS)	DepEd	Personnel, ICT	SY 2023-24
National School Building Inventory (NSBI)	DepEd	Facilities, sanitation	SY 2023-24
Philippine Statistics Authority	PSA	Population projections	2023

Data Files Used

File	Description	Records
enrollment_2017-18.csv.gz	Enrollment data SY 2017-18	61,563
enrollment_2018-19.csv.gz	Enrollment data SY 2018-19	61,916
enrollment_2019-20.csv.gz	Enrollment data SY 2019-20	61,923
enrollment_2020-21.csv.gz	Enrollment data SY 2020-21	60,957
enrollment_2021-22.csv.gz	Enrollment data SY 2021-22	60,429
enrollment_2022-23.csv.gz	Enrollment data SY 2022-23	60,137
enrollment_2023-24.csv.gz	Enrollment data SY 2023-24	60,167
enrollment_2024-25.csv.gz	Enrollment data SY 2024-25	60,129
personnel_2023-24.csv.gz	Teacher data	~47,674
facilities_2023-24.csv.gz	Classroom data	~46,939
sanitation_utilities_2023-24.csv.gz	Toilet data	~46,454
ict_2023-24.csv.gz	Computer data	~36,040
phl_admpop_adm1_2023.csv	Regional population	17 regions

Analytical Methods

Data Cleaning: Missing values handled via row-wise exclusion for ratio calculations
Aggregation: School-level data aggregated to regional and national levels
Statistical Testing: Alpha level set at 0.05 for all hypothesis tests
Visualization: All charts generated with matplotlib/seaborn with consistent branding
GER Estimation: Single-year populations estimated from 5-year age groups assuming uniform distribution

Data Limitations

Repeater Data: Not available, affecting true transition rate calculations
Age-Specific Enrollment: Not directly available, preventing NER calculation
NIR Population: PSA data pending for Negros Island Region
Private School Resources: NSBI covers only public schools