DepEd NAT Grade 6 2023-2024 Results: Comprehensive Analysis & Key Findings
Explore the detailed analysis of DepEd NAT Grade 6 (NATG6) 2023-2024 results. Review school proficiency stats, regional performance, and the critical mathematics gap findings.
School Year 2023-2024: Comprehensive Data Analysis Report
Data Source: Department of Education (DepEd), Philippines
Analysis Date: December 2025
Dataset Coverage: 6,636 Schools • 52,761 Test-Takers • 5 Regions • 44 Divisions
1. Executive Summary
This comprehensive analysis examines the National Achievement Test for Grade 6 (NATG6) results for School Year 2023-24, covering 6,636 schools across 5 regions and 44 divisions with a total of 52,761 test takers.
1.1 Key Highlights
Critical Context: Pursuant to DepEd Order No. 027, s. 2022, the assessment administered at the end of SY 2023-2024 serves as the New National Assessment Baseline for the basic education system. These results constitute the official "zero point" against which the impact of the new MATATAG Curriculum, the Basic Education Development Plan (BEDP) 2030, and the newly established ARAL Program will be measured.
Furthermore, this performance landscape serves as the primary evidence base for the strategic shift in the medium of instruction mandated by DepEd Order No. 020, s. 2025, and the targeted interventions in Region IX via DepEd Memorandum No. 033, s. 2025.
| Metric | Value | Status |
|---|
| National Overall MPS | 60.6% | Nearly Proficient |
| Highest Performing Subject | Filipino (66.1%) | Nearly Proficient |
| Lowest Performing Subject | Science (54.0%) | Nearly Proficient |
| Schools Meeting Proficiency (≥75%) | 1,236 (18.6%) | Below Target |
| Schools Below Near Proficiency (<50%) | 1,702 (25.6%) | Needs Intervention |
Table 1.1: Key Highlights of the NATG6 2023-24 Results
1.2 Critical Finding
The Mathematics Challenge: In 69.5% of schools (4,613 schools), Mathematics performance is lower than the average of other subjects, with an average gap of 5.3 percentage points. This systemic pattern indicates a nationwide need for targeted numeracy intervention. Specifically, the 1,702 schools falling below near proficiency are the priority targets for the ARAL-Mathematics component of the Academic Recovery and Accessible Learning (ARAL) Program (RA 12028 / DO 018, s. 2025), which mandates intervention for learners performing below minimum proficiency levels.
2. Data Overview & Methodology
2.1 Dataset Composition
As shown in Table 2.1, the analysis covers a broad scope of the Philippine education system.
Important Note on Dataset Scope: While DepEd Memorandum No. 016, s. 2024 mandated a "Census" of public and private schools, the analyzed dataset of 6,636 schools represents approximately 18% of the total public elementary schools in the country. Furthermore, the 52,761 test takers represent a stratified sample (approx. 2.3% of the estimated 2.3 million Grade 6 learner population). This is consistent with the Technical Notes on Learning Outcomes Data (March 2025) which cite restrictive data sharing guidelines (e.g., only 10% of examinees) for public release. Therefore, findings should be interpreted as derived from a robust stratified sample rather than a total population census.
| Parameter | Value |
|---|
| Total Schools | 6,636 |
| Total Test Takers | 52,761 |
| Regions Covered | 5 (CAR, Region I, III, VIII, IX) |
| Divisions Covered | 44 |
| Average Test Takers per School | 8.0 |
| School Year | 2023-24 |
Table 2.1: Dataset Composition of the NATG6 2023-24 analysis
2.2 Variables Analyzed
The dataset contains the following Mean Percentage Scores (MPS) for each school:
- Filipino - National language proficiency
- Mathematics - Numeracy and problem-solving skills
- English - English language proficiency
- Science - Scientific literacy
- Araling Panlipunan - Social studies/civic awareness
- Overall MPS - Aggregate performance
2.3 Compliance Statement
This analysis strictly adheres to DepEd's Terms of Use and Fair Use Policy under Executive Order No. 2, 2016:
✅ No Ranking - Schools and divisions are NOT ranked
✅ Benchmark Comparisons Only - Performance compared against DepEd proficiency standards
✅ No Cross-Year Comparison - Test difficulty varies annually; results are strictly for SY 2023-24 baseline analysis per Technical Notes (March 2025)
✅ Data "As Is" - No modification to original data
✅ No Endorsement Implied - Analysis is independent of DepEd
3. DepEd Assessment Framework
3.1 21st Century Skills Context
Crucially, DepEd Order No. 29, s. 2017 and DepEd Memorandum No. 016, s. 2024 clarify that NATG6 is not designed solely to measure subject content mastery. Instead, it utilizes the 5 learning areas to measure 21st Century Skills, specifically:
- Problem-Solving
- Information Literacy
- Critical Thinking
Therefore, low scores in subjects like Science and Math should be interpreted as deficits in critical thinking and problem-solving skills applied within those contexts, rather than solely as a lack of rote knowledge.
3.2 Proficiency Levels
The following DepEd-defined proficiency levels are used throughout this analysis. Note that the Technical Notes on Learning Outcomes Data (March 2025) indicate that the proficiency cutoff of 75% was "arbitrarily set," which should be considered when evaluating the "Below Target" status of schools.
| MPS Range | Proficiency Level | Description |
|---|
| 90-100% | Highly Proficient | Learners are highly capable of solving problems, managing and communicating accurate information, and analyzing and evaluating data to create/formulate ideas |
| 75-89% | Proficient | Learners are skilled in solving problems, managing and communicating information, and analyzing and evaluating data to create/formulate ideas |
| 50-74% | Nearly Proficient | Learners meet the minimum level of skills in solving problems, managing and communicating information, and analyzing and evaluating data to comprehend ideas |
| 25-49% | Low Proficient | Learners can identify strategies in solving problems and differentiate and organize information |
| 0-24% | Not Proficient | Learners can solve simple problems, classify, and identify the source of information |
Table 3.1: DepEd Proficiency Levels for NATG6
3.3 Achievement Levels (Mastery Scale)
| MPS Range | Achievement Level |
|---|
| 96-100% | Mastered |
| 86-95% | Closely Approximating Mastery |
| 66-85% | Moving Towards Mastery |
| 35-65% | Average Mastery |
| 15-34% | Low Mastery |
| 5-14% | Very Low Mastery |
| 0-4% | Absolutely No Mastery |
Table 3.2: Achievement Levels (Mastery Scale)
3.4 Quartile Distribution
| MPS Range | Quartile | Description |
|---|
| 76-100% | Q1 | Superior |
| 51-75% | Q2 | Upper Average |
| 26-50% | Q3 | Lower Average |
| 0-25% | Q4 | Poor |
Table 3.3: Quartile Distribution for NATG6 results
3.5 Overall Statistics
As summarized in Table 3.5, all learning areas fall within the "Nearly Proficient" range:
| Subject | Mean MPS | Median | Std Dev | Min | Max | Proficiency Level |
|---|
| Filipino | 66.1% | 66.7% | 12.9 | 14.8% | 98.5% | Nearly Proficient |
| Mathematics | 56.4% | 55.8% | 19.5 | 7.7% | 100.0% | Nearly Proficient |
| English | 63.7% | 65.4% | 16.8 | 13.0% | 100.0% | Nearly Proficient |
| Science | 54.0% | 54.1% | 15.8 | 9.3% | 92.6% | Nearly Proficient |
| Araling Panlipunan | 62.9% | 64.8% | 17.1 | 9.3% | 100.0% | Nearly Proficient |
| Overall | 60.6% | 61.6% | 14.6 | 11.9% | 92.9% | Nearly Proficient |
Table 3.5: National Summary Statistics by Subject
3.6 Performance Ranking by Subject
- 🥇 Filipino - 66.1% (Strongest subject nationally)
- 🥈 English - 63.7%
- 🥉 Araling Panlipunan - 62.9%
- Mathematics - 56.4%
- Science - 54.0% (Weakest subject nationally)
3.7 Key Observation
All five learning areas fall within the "Nearly Proficient" category (50-74%), indicating that while learners meet minimum skill levels, they have not yet achieved full proficiency. The 12.0 percentage point spread between the highest (Filipino) and lowest (Science) performing subjects suggests significant variance in learning outcomes across disciplines.
4. Subject-Level Analysis
4.1 Filipino Score Distribution
Figure 1: Filipino Score Distribution with DepEd Proficiency Zones
Interpretation:
Filipino emerges as the strongest performing subject with a mean of 66.1% and median of 66.7%. The distribution shows:
- Shape: Slightly right-skewed normal distribution centered around 65-70%
- Concentration: Peak frequency occurs in the 60-70% range with approximately 500+ schools
- Low-end tail: Very few schools (<50) fall below 25% (Not Proficient zone)
- High-end performance: A healthy proportion of schools extends into the Proficient zone (75-89%)
Key Insight: Filipino shows the most favorable distribution profile. Pursuant to DepEd Memorandum No. 016, s. 2024 and DO 55, s. 2016, the assessment utilizes both English and Filipino languages, with the Filipino subject being tested in Filipino. The high performance here suggests minimal linguistic barriers to demonstrating 21st-century skills when learners are assessed in their primary academic language.
4.2 Mathematics Score Distribution
Figure 2: Mathematics Score Distribution with DepEd Proficiency Zones
Interpretation:
Mathematics shows the highest variability (σ=19.5) among all subjects with concerning performance patterns:
- Shape: Flatter, more dispersed distribution compared to other subjects
- Bimodal tendency: Two visible peaks around 40-45% and 55-60%
- Wide spread: Significant number of schools across the entire 20-80% range
- Low Proficient zone: Substantial proportion of schools fall in the 25-49% (Low Proficient) range
Critical Finding & Policy Validation: Mathematics has the highest standard deviation (19.5). Consistent with DepEd Memorandum No. 016, s. 2024, Mathematics is tested in English. The performance gap between Math (56.4%) and Filipino (66.1%) serves as strong evidence validating the policy shift in DepEd Order No. 020, s. 2025. This order discontinues the use of Mother Tongue as the medium of instruction for Kindergarten to Grade 3 in favor of Filipino and English, aiming to bridge the linguistic gap that hinders performance in English-tested subjects like Mathematics.
4.3 English Score Distribution
Figure 3: English Score Distribution with DepEd Proficiency Zones
Interpretation:
English performance (Mean: 63.7%, Median: 65.4%) shows:
- Shape: Approximately normal distribution with slight right skew
- Center: Peak concentration in the 60-70% range
- Standard Deviation: 16.8 (moderate variability)
- Range: 13.0% to 100.0%
Key Insight: English performance is stronger than Mathematics and Science but trails Filipino by 2.4 percentage points. The distribution suggests most schools achieve "Nearly Proficient" status with a reasonable proportion reaching "Proficient."
4.4 Science Score Distribution
Figure 4: Science Score Distribution with DepEd Proficiency Zones
Interpretation:
Science emerges as the lowest performing subject (Mean: 54.0%):
- Shape: Left-skewed distribution with peak around 50-55%
- Concentration: Heavy clustering in the Low Proficient to Nearly Proficient transition zone
- Ceiling effect: Maximum score of only 92.6% (no school achieved 100%)
- Floor concerns: 9.3% minimum indicates some schools struggle severely
Critical Finding: Science has the lowest maximum score (92.6%) among all subjects. Only 9 schools (0.1%) achieved "Highly Proficient" status in Science. Like Mathematics, Science is tested in English (DM No. 016, s. 2024). This "double burden" of content complexity and language barrier reinforces the rationale behind DO 020, s. 2025 to strengthen English proficiency from the early grades to support STEM learning.
4.5 Araling Panlipunan Score Distribution
Figure 5: Araling Panlipunan Score Distribution with DepEd Proficiency Zones
Interpretation:
Araling Panlipunan shows moderate performance (Mean: 62.9%):
- Shape: Normal distribution centered around 60-65%
- Variability: Standard deviation of 17.1 (moderate-high)
- Range: 9.3% to 100.0% (full range achieved)
- Position: Third-highest performing subject
Key Insight: Tested in Filipino, performance in Social Studies is relatively balanced and strong, reinforcing the observation that subjects tested in the national language yield higher proficiency rates than those tested in English (Math/Science).
4.6 Overall Score Distribution
Figure 6: Overall MPS Distribution with DepEd Proficiency Zones
Interpretation:
The aggregate Overall MPS (Mean: 60.6%, Median: 61.6%) represents combined performance:
- Shape: Well-defined normal distribution
- Center: Peak frequency at approximately 65-70%
- Symmetry: Mean and median are close (0.9 percentage point difference), indicating minimal skew
- Range: 11.9% to 92.9%
Critical Observation: The overall distribution is more compact than individual subjects due to averaging effects, with standard deviation of 14.6 (lower than all individual subjects except Filipino). Only 12 schools (0.2%) achieved "Highly Proficient" status overall (≥90%), with the maximum at 92.9%.
5. Regional Performance Analysis
5.1 Regional Comparison by Overall MPS
As shown in Table 5.1 and Figure 6, Region VIII leads the national performance:
Figure 7: Regional Performance Comparison by DepEd Proficiency Level
Regional Performance Summary:
| Rank | Region | Overall MPS | Proficiency Level |
|---|
| 1 | Region VIII (Eastern Visayas) | 66.3% | Nearly Proficient |
| 2 | Region I (Ilocos) | 59.6% | Nearly Proficient |
| 3 | Region III (Central Luzon) | 59.4% | Nearly Proficient |
| 4 | CAR (Cordillera) | 57.2% | Nearly Proficient |
| 5 | Region IX (Zamboanga Peninsula) | 53.8% | Nearly Proficient |
Table 5.1: Regional Performance Summary by Overall MPS
Interpretation:
- Regional spread: 12.5 percentage points between highest (Region VIII: 66.3%) and lowest (Region IX: 53.8%)
- All regions classified as "Nearly Proficient" - none reached the 75% Proficient threshold
- Region VIII significantly outperforms other regions by 6.7+ percentage points
- Region IX requires focused attention as the only region approaching the Low Proficient threshold
Targeted Intervention in Region IX: The critical situation in Region IX has directly precipitated the launch of the Bawat Bata Makababasa Program (BBMP) via DepEd Memorandum No. 033, s. 2025. As stated in Item 3 of the memorandum, the BBMP pilot phase aims to ensure all struggling readers attain grade-level proficiency, focusing specifically on learners in Region IX (Zamboanga Peninsula) to address the learning gaps identified in this baseline data.
5.2 Subject Performance Heatmap by Region
Figure 8: Subject Performance Heatmap by Region (Learning Areas)
Detailed Regional-Subject Matrix:
| Region | Filipino | Mathematics | English | Science | Araling Panlipunan |
|---|
| Region VIII | 69.7% | 63.8% | 69.3% | 59.7% | 69.0% |
| Region I | 65.6% | 55.5% | 62.1% | 53.3% | 61.7% |
| Region III | 65.5% | 54.9% | 62.5% | 52.7% | 61.5% |
| CAR | 64.0% | 50.6% | 61.6% | 50.3% | 59.5% |
| Region IX | 60.9% | 47.8% | 56.6% | 47.4% | 56.0% |
Table 5.2: Subject Performance Heatmap by Region
Interpretation:
The heatmap reveals consistent patterns across regions:
- Subject consistency: Filipino > English > Araling Panlipunan > Mathematics > Science (pattern holds across all regions)
- Mathematics in Region IX falls below 50% (47.8%), placing it in the "Low Proficient" category
- Science in Region IX also falls below 50% (47.4%), indicating critical intervention needs
- Region VIII demonstrates balanced excellence across all subjects
- Temperature gradient: Darker (warmer) colors in Region VIII rows versus cooler colors in Region IX
Critical Finding: The subject-region interaction reveals that while Region VIII maintains relatively strong performance across all subjects, Region IX shows concerning performance drops specifically in Mathematics and Science that push these subjects into the "Low Proficient" zone.
5.3 Schools and Test Takers by Region
Figure 9: Schools and Test Takers Distribution by Region
Distribution Analysis:
The dataset shows varying regional coverage:
- Region distribution is not uniform, reflecting sampling methodology
- Test taker concentration varies significantly by region
- School sizes differ across regions, affecting weighted interpretations
5.4 Division Performance Analysis
Figure 10: Division Performance (20 Largest by Test Taker Count)
Interpretation:
The division-level analysis (showing top 20 divisions by test taker count) reveals:
- Substantial within-region variation exists at the division level
- Division performance ranges span the full Nearly Proficient zone
- Larger divisions (by test taker count) show moderating mean-reversion effects
- Context matters: Division performance should not be used for ranking; factors like urbanization, resources, and demographics differ significantly
6. Correlation & Relationship Analysis
6.1 Subject Correlation Matrix
Figure 11: Subject Correlation Matrix (Pearson Coefficients)
Correlation Coefficients
As shown in Table 6.1 and Figure 11, all subject pairs show strong positive correlations:
| Filipino | Mathematics | English | Science | Araling Panlipunan |
|---|
| Filipino | 1.000 | 0.692 | 0.697 | 0.677 | 0.736 |
| Mathematics | 0.692 | 1.000 | 0.762 | 0.781 | 0.744 |
| English | 0.697 | 0.762 | 1.000 | 0.780 | 0.744 |
| Science | 0.677 | 0.781 | 0.780 | 1.000 | 0.772 |
| Araling Panlipunan | 0.736 | 0.744 | 0.744 | 0.772 | 1.000 |
Table 6.1: Subject Correlation Matrix of Pearson Coefficients
Interpretation:
All subject pairs show strong positive correlations (r > 0.67), indicating:
- Strongest correlation: Mathematics-Science (r = 0.781) - Schools strong in Math tend to be strong in Science. Both are tested in English.
- Second strongest: English-Science (r = 0.780) - Suggests English proficiency aids Science comprehension.
- Third strongest: Science-Araling Panlipunan (r = 0.772)
- Weakest correlation: Filipino-Science (r = 0.677) - Still strong but relatively weaker
Key Insight: The uniformly high correlations suggest that school-level factors (teaching quality, resources, leadership, community support) affect all subjects similarly. A school performing well in one subject tends to perform well in others.
6.2 Mathematics vs English Performance
Figure 12: Mathematics vs English Performance Scatter Plot
Interpretation:
The scatter plot reveals:
- Positive linear relationship with upward trend line
- Correlation coefficient: r ≈ 0.76
- Wider scatter at lower performance levels indicating greater variability among struggling schools
- Diagonal reference line shows many schools perform better in English than Mathematics
Key Finding: Schools below 50% in Mathematics tend to have relatively better English scores, suggesting English comprehension may not be the primary barrier to Mathematics achievement.
6.3 Filipino vs English Performance
Figure 13: Filipino vs English Performance Scatter Plot
Interpretation:
- Strong positive correlation between the two language subjects
- Filipino generally outperforms English in most schools (points cluster above diagonal)
- Gap is consistent across performance levels
- Bilingual advantage: Schools strong in Filipino leverage this for English performance
7. School Size Impact Analysis
7.1 Performance by School Size (Box Plot)
Figure 14: Performance Distribution by School Size Category
School Size Categories and Performance:
| Category | Test Takers | n (Schools) | Median MPS | IQR |
|---|
| Very Small | 1-5 | 3,153 | ~62% | ~50-75% |
| Small | 6-10 | 2,167 | ~60% | ~48-72% |
| Medium | 11-20 | 966 | ~62% | ~52-73% |
| Large | 21-50 | 287 | ~63% | ~50-74% |
| Very Large | 51-100 | 61 | ~55% | ~48-67% |
| Extra Large | 100+ | 2 | ~43% | ~41-45% |
Table 7.1: Performance Distribution by School Size Category
Interpretation:
- Inverse relationship in larger schools: Very Large (51-100) and Extra Large (100+) schools show lower median performance
- Small to Medium schools show most consistent performance with similar medians
- Variance is highest in Very Small schools (widest box and whiskers)
- Extra Large schools (n=2) show notably lower performance - possibly due to resource strain
Critical Insight: The data suggests a threshold effect where schools with more than 50 test takers begin showing performance declines. This could indicate resource constraints, classroom management challenges, or sampling effects in larger schools.
7.2 School Size Density Analysis
Figure 15: School Size vs Performance Density Analysis
Interpretation:
The hexbin density plot shows:
- Heavy concentration of schools in the 1-20 test taker range
- Logarithmic trend line shows slight negative relationship
- Performance ceiling appears around 90% regardless of school size
- Few very large schools in the dataset
8. Performance Gap Analysis
8.1 Distribution of Performance Gaps Between Subjects
Figure 16: Distribution of Performance Gaps Between Subjects
Gap Statistics
As shown in Table 8.1 and Figure 16, there are significant performance gaps between subjects:
| Comparison | Mean Gap | Interpretation |
|---|
| Filipino - Mathematics | +9.7 pp | Filipino significantly outperforms Math |
| Filipino - English | +2.4 pp | Filipino slightly outperforms English |
| Mathematics - Science | +2.4 pp | Math slightly outperforms Science |
Table 8.1: Performance Gaps Between Subjects
Interpretation:
- Filipino-Math gap is substantial (9.7 percentage points) and consistent across schools
- Distribution shapes differ: Filipino-Math gap shows clear right shift (positive)
- Math-Science gap is centered near zero with symmetric distribution
- Filipino-English gap is small reflecting linguistic subject similarity
Key Finding & Language Factor: The 9.7 percentage point advantage of Filipino over Mathematics correlates with the fact that Math is tested in English while Filipino is tested in the native language (DM 016, s. 2024). This linguistic disadvantage serves as the core justification for DepEd Order No. 020, s. 2025, which mandates the return to English and Filipino as the primary media of instruction to close this gap.
8.2 Performance Gaps by Region
Figure 17: Average Performance Gaps by Region
Regional Gap Patterns:
| Region | Fil-Math Gap | Fil-Eng Gap | Math-Sci Gap |
|---|
| Region VIII | +5.9 pp | +0.4 pp | +4.1 pp |
| Region I | +10.1 pp | +3.5 pp | +2.2 pp |
| Region III | +10.6 pp | +3.0 pp | +2.2 pp |
| CAR | +13.4 pp | +2.4 pp | +0.3 pp |
| Region IX | +13.1 pp | +4.3 pp | +0.4 pp |
Table 8.2: Average Performance Gaps by Region
Interpretation:
- CAR and Region IX show largest Filipino-Math gaps (>13 pp)
- Region VIII shows smallest gap (5.9 pp), indicating more balanced performance
- All regions show positive gaps confirming the national pattern
- Math-Science gaps are relatively small across all regions
9. Proficiency & Achievement Distribution
9.1 Schools by DepEd Proficiency Level
As summarized in Table 9.1, the majority of schools fall into the "Nearly Proficient" category:
Figure 18: Distribution of Schools by DepEd Proficiency Level
Distribution:
| Proficiency Level | MPS Range | Schools | Percentage |
|---|
| Not Proficient | 0-24% | 9 | 0.1% |
| Low Proficient | 25-49% | 1,693 | 25.5% |
| Nearly Proficient | 50-74% | 3,698 | 55.7% |
| Proficient | 75-89% | 1,224 | 18.4% |
| Highly Proficient | 90-100% | 12 | 0.2% |
Table 9.1: Distribution of Schools by DepEd Proficiency Level
Interpretation:
- Majority cluster in "Nearly Proficient" (55.7%) - just meeting minimum skill standards
- Only 18.6% meet or exceed Proficient status (75%+ MPS)
- Over one-quarter (25.6%) fall below the "Nearly Proficient" threshold
- Highly Proficient is extremely rare - only 12 schools (0.2%)
Critical Finding: The proficiency distribution shows a bell curve centered below the proficiency threshold, indicating systemic challenges in achieving DepEd's proficiency standards. However, it should be noted that the Technical Notes (March 2025) describe the 75% cutoff as "arbitrarily set," which may influence the interpretation of this gap.
9.2 Schools by Achievement Level (Mastery Scale)
Figure 19: Distribution of Schools by DepEd Achievement Level (Mastery
Scale)
Distribution:
| Achievement Level | MPS Range | Schools | Percentage |
|---|
| Absolutely No Mastery | 0-4% | 0 | 0.0% |
| Very Low Mastery | 5-14% | 1 | 0.0% |
| Low Mastery | 15-34% | 296 | 4.5% |
| Average Mastery | 35-65% | 3,684 | 55.5% |
| Moving Towards Mastery | 66-85% | 2,524 | 38.0% |
| Closely Approximating Mastery | 86-95% | 131 | 2.0% |
| Mastered | 96-100% | 0 | 0.0% |
Table 9.2: Distribution of Schools by Achievement Level
Interpretation:
- No school achieved "Mastered" status (96-100%)
- Average Mastery dominates (55.5%), indicating satisfactory but not exceptional performance
- 38% are "Moving Towards Mastery" - a positive trajectory indicator
- Only 2% reached "Closely Approximating Mastery"
- Very few schools in critical zones (Low Mastery: 4.5%)
9.3 Quartile Distribution
Figure 20: Distribution of Schools by Quartile
Distribution:
| Quartile | MPS Range | Description | Schools | Percentage |
|---|
| Q4 | 0-25% | Poor | 20 | 0.3% |
| Q3 | 26-50% | Lower Average | 1,818 | 27.4% |
| Q2 | 51-75% | Upper Average | 3,705 | 55.8% |
| Q1 | 76-100% | Superior | 1,093 | 16.5% |
Table 9.3: Distribution of Schools by Quartile
Interpretation:
- Majority in Q2 (Upper Average) - consistent with proficiency findings
- Only 16.5% in Q1 (Superior) quartile
- Over 27% in Q3 (Lower Average) - needing improvement
- Minimal Q4 representation (0.3%) - few extreme low performers
9.4 National Subject Comparison
Figure 21: National Average MPS by Subject (Learning Area)
Interpretation:
The bar chart (Figure 21) presents a comparative view of national average Mean Percentage Scores, as summarized in Table 9.4:
| Rank | Subject | Mean MPS | Gap from Proficient (75%) |
|---|
| 1 | Filipino | 66.1% | -8.9 pp |
| 2 | English | 63.7% | -11.3 pp |
| 3 | Araling Panlipunan | 62.9% | -12.1 pp |
| 4 | Mathematics | 56.4% | -18.6 pp |
| 5 | Science | 54.0% | -21.0 pp |
| Overall | 60.6% | -14.4 pp |
Table 9.4: National Average MPS and Gap from Proficient Benchmark
Key Observations:
-
All subjects fall short of the Proficient threshold (75%) – The green dashed line representing the Proficient benchmark remains unreached by all learning areas, confirming a systemic national challenge.
-
Clear subject hierarchy emerges – Language subjects (Filipino, English) outperform STEM subjects (Mathematics, Science) by approximately 10 percentage points, revealing a distinct performance pattern.
-
All subjects exceed the Nearly Proficient threshold (50%) – The orange dashed line is surpassed by all subjects, indicating learners meet minimum skill standards across all learning areas.
-
12.1 percentage point spread – The gap between the highest (Filipino: 66.1%) and lowest (Science: 54.0%) performing subjects represents a significant disparity in learning outcomes.
-
Overall MPS (60.6%) represents balanced aggregate – Positioned between language and STEM subjects, reflecting the averaging effect across diverse learning areas.
Implication: The visual representation reinforces the need for differentiated intervention strategies—while language subjects require refinement to reach proficiency, Mathematics and Science demand more intensive support programs to close the substantial gap to the 75% benchmark.
9.5 Mathematics Challenge Analysis
Figure 22: Mathematics Challenge Analysis - Schools with Math
Underperformance
Analysis:
| Category | Schools | Percentage |
|---|
| Math Lower than Other Subjects | 4,613 | 69.5% |
| Math Higher/Equal | 2,023 | 30.5% |
Table 9.5: Schools with Mathematics Underperformance relative to other subjects
Average Gap: 5.3 percentage points
Interpretation:
This visualization confirms the systemic Mathematics challenge:
- Nearly 70% of schools show Mathematics performance below their average in other subjects
- Average underperformance gap is 5.3 percentage points
- This is not a regional issue but a national pattern
- Only ~30% of schools have balanced or Math-strong profiles
Implication: This finding suggests a need for national-level Mathematics intervention programs, teacher training initiatives, and curriculum review.
9.6 Subject Radar by Region
Figure 23: Subject Performance Radar Chart by Region
Interpretation:
The radar chart visualizes regional performance profiles:
- Region VIII (purple) shows the largest, most outward polygon - strongest across all subjects
- Region IX (green) shows the smallest, most inward polygon - needs most support
- All regions show the same "shape" - Filipino strongest, Science/Math weakest
- CAR, Region I, and Region III cluster closely together in performance
Key Insight: The consistent polygon shape across regions reinforces that subject-specific challenges (Math, Science) are national rather than regional phenomena.
9.7 Proficiency by Subject
Figure 24: Proficiency Level Distribution by Subject
Subject-wise Proficiency Breakdown:
| Subject | Not Prof. | Low Prof. | Nearly Prof. | Proficient | Highly Prof. |
|---|
| Filipino | Very Low | Low | Highest | High | Low |
| Mathematics | Moderate | High | High | Low | Very Low |
| English | Very Low | Moderate | Highest | Moderate | Low |
| Science | Low | Highest | Highest | Low | Very Low (9) |
| Araling Panlipunan | Very Low | Moderate | Highest | Moderate | Low |
| Overall | Very Low | Moderate | Highest | Low | Very Low |
Table 9.7: Proficiency Level Distribution by Subject
Interpretation:
- Science has the highest "Low Proficient" proportion (2,554 schools), followed closely by Mathematics (2,474 schools)
- Science has the lowest "Highly Proficient" count - only 9 schools (0.1%), indicating a concerning ceiling
- Filipino shows the best proficiency profile with the highest "Proficient" count
- All subjects peak at "Nearly Proficient" - indicates systemic 50-74% clustering
10. Critical Insights & Recommendations
10.1 Summary of Key Findings
Finding 1: National Proficiency Gap
Only 18.6% of schools meet the DepEd Proficiency standard (≥75%)
The majority of schools (55.7%) fall in the "Nearly Proficient" category, indicating learners meet minimum skill levels but have not achieved full proficiency targets.
Finding 2: The Mathematics Crisis
69.5% of schools underperform in Mathematics relative to other subjects
Mathematics consistently shows:
- Lowest mean MPS among core subjects (tied with Science)
- Highest variability (σ=19.5)
- Systematic 9.7 percentage point gap below Filipino
Finding 3: Science Ceiling Effect
Only 9 schools (0.1%) achieved "Highly Proficient" in Science
The maximum Science MPS of 92.6% (vs. 100% in other subjects) and the extremely low proportion of highly proficient schools suggests potential issues with Science instruction or assessment alignment.
Finding 4: Regional Disparities
12.5 percentage point spread between highest and lowest performing regions
Region VIII significantly outperforms all other regions, while Region IX shows concerning performance levels, particularly in Mathematics (47.8%) and Science (47.4%) which fall into "Low Proficient" territory.
Finding 5: School Size Effect
Very large schools (50+ test takers) show lower performance
Performance declines in schools with larger test-taking populations, suggesting possible resource constraints or scale challenges.
10.2 Recommendations
Based on the analysis findings and aligned with the newly established Academic Recovery and Accessible Learning (ARAL) Program mandated by Republic Act No. 12028 and implemented via DepEd Order No. 018, s. 2025 (which repeals the former National Learning Recovery Program/NLRP of DO 013, s. 2023), the following recommendations are offered:
| Priority | Recommendation | Rationale |
|---|
| High | Activate ARAL-Mathematics & Science | Prioritize implementation of ARAL-Mathematics (SY 2025-2026) and prepare for ARAL-Science (SY 2026-2027) as mandated by DO 018, s. 2025 to address the 69.5% Math underperformance and Science ceiling effect. Specifically target the 1,702 schools identified as Below Near Proficiency, as DO 018 explicitly mandates intervention for learners performing below minimum proficiency levels. |
| High | Monitor and Scale BBMP in Region IX | Region IX's low performance (53.8% MPS) has already triggered the launch of the Bawat Bata Makababasa Program (BBMP) (DM 033, s. 2025). Close monitoring of this pilot is essential to validate the intervention model before scaling it to other low-performing divisions. |
| High | Targeted Support for Region IX via SIIF | Leverage the School Innovation and Improvement Fund (SIIF) per DepEd Memorandum No. 073, s. 2025 alongside ARAL interventions to support Region IX schools identified as priority recipients. |
| Medium | Teacher Training in STEM Subjects | Strong Math-Science correlation suggests common instructional factors warranting unified training. |
| Medium | Resource Assessment for Large Schools | Inverse size-performance relationship requires investigation and resource allocation adjustments. |
| Low | Best Practice Sharing from Region VIII | Highest performing region can provide model interventions for replication. |
Table 10.2: Priority Recommendations based on performance analysis
11. Technical Notes & Limitations
11.1 Data Limitations
Per DepEd's Technical Notes on Learning Outcomes Data (March 2025):
- No cross-year comparison: Test difficulty varies annually; MPS should not be compared across school years.
- Restrictive Data Sharing: The dataset (52k learners) represents a stratified random sample due to data sharing guidelines (e.g., only 10% of examinees) despite the Census policy mandate.
- Test Design Comparability: Difficulty levels vary per year despite consistent test specifications.
- Ranking Invalidity: Direct school-to-school comparisons are not appropriate.
- Proficiency Cutoff: The 75% proficiency threshold is noted in the Technical Notes as "arbitrarily set" rather than empirically derived, which may affect the interpretation of the 'Proficient' category.
11.2 Assessment Design
- Coverage: Measures 21st-century Skills (Problem Solving, Information Literacy, Critical Thinking) using 5 learning areas as content.
- Format: Multiple choice
- Languages: English and Filipino
- Purpose: Exit assessment (not graduation requirement)
11.3 Statistical Considerations
- All analyses use unweighted school-level MPS
- Summary statistics are arithmetic means
- Proficiency classifications use DepEd-defined cutoffs
- Correlations are Pearson product-moment coefficients
12. References
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Department of Education, Philippines. (2024). National Achievement Test for Grade 6 (NATG6) School-Level Data, SY 2023-24.
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Department of Education, Philippines. (2017). DepEd Order No. 29, s. 2017: Policy Guidelines on System Assessment in the K to 12 Basic Education Program.
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Department of Education, Philippines. (2022). DepEd Order No. 027, s. 2022: Conduct of Rapid Assessment in School Year 2021-2022 for Learning Recovery as well as in Preparation for the 2024 Baseline System Assessment.
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Department of Education, Philippines. (2025). DepEd Order No. 018, s. 2025: Implementing Guidelines of the Academic Recovery and Accessible Learning (ARAL) Program. (Repeals DO 013, s. 2023).
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Department of Education, Philippines. (2025). Technical Notes on Learning Outcomes Data - ELLNA and NATG6.
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Department of Education, Philippines. (2024). DepEd Memorandum No. 016, s. 2024: Administration of the Early Language, Literacy, and Numeracy Assessment, National Achievement Test for Grade 6, and National Achievement Test for Grade 12 for School Year 2023-2024.
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Department of Education, Philippines. (2025). DepEd Memorandum No. 073, s. 2025: Allocation and Release of the School Innovation and Improvement Fund.
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Republic Act No. 12027. An Act Discontinuing the Use of Mother Tongue as Medium of Instruction from Kindergarten to Grade 3.
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Department of Education, Philippines. (2025). DepEd Order No. 020, s. 2025: Policy on the Medium of Instruction for Kindergarten to Grade 3 Effective School Year 2025-2026.
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Department of Education, Philippines. (2025). DepEd Memorandum No. 033, s. 2025: Supplemental Guidelines for the Implementation of the Bawat Bata Makababasa Program.
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Department of Education, Philippines. (2025). DepEd Memorandum No. 024, s. 2025: Administration of the National Achievement Test for Grade 6 for School Year 2024-2025.
Appendix: List of Visualizations
Table A.1: List of Visualizations included in the NATG6 Report