These notes summarise classroom research and cohort outcomes. They document my past practice, not a program or service. From 2022–2025 my Grade 5/6 classes recorded large within-cohort gains on national assessments. These outcomes were associated with explicit instruction, daily practice and weekly progress monitoring in standard class sizes. Methods, code and de-identified extracts are available on request.
| Year | Measure | n | Mean gain | SD(gain) | d | Headline |
|---|---|---|---|---|---|---|
| 2025 | PAT-M | 22 | 11.40 | 7.21 | 1.58 | 50th → 94–95th pct |
| 2025 | PAT-R | 21 | 8.22 | 6.95 | 1.18 | 50th → 88th pct |
| 2024 | PAT-M | 28 | 6.31 | 6.01 | 1.05 | High growth |
| 2024 | PAT-R | 27 | 5.83 | 7.31 | 0.80 | Strong growth |
| 2024 | DIBELS ORF | 28 | 145.64 | 58.69 | 2.48 | Corroboration |
| 2023 | DIBELS MAZE | 26 | 6.81 | 5.85 | 1.16 | 4-month window |
Grade 5/6 · Victorian Government School · South Western Victorian Region (SWVR)
In a complex, low-socioeconomic Grade 5/6 setting, these outcomes were associated with sustained explicit-instruction routines, with effect sizes aligned with the upper range reported in published interventions. This 12-month window tracked matched PAT-Mathematics and PAT-Reading growth for the 2025 cohort.
All student data is fully anonymised (Student 1–N).
Effect sizes rely on gain-score standard deviations computed in R 4.5.2 and benchmarked against national research datasets.
Cohen's d (effect size)
Very large impact: the average student moved from the 50th to the 94th–95th percentile.
Observed GrowthCohen's d (effect size)
Large impact: the average student moved from the 50th to the 88th percentile.
Large Observed GrowthWhole-Class Samples
Mathematics n = 22 · Reading n = 21
Full CohortQuantitative interpretation: A Cohen's d of 1.58 means the average student scored 1.58 standard deviations above their baseline, lifting the median learner from the 50th to roughly the 94th–95th percentile.
Research context (Hattie, 2009): This exceeds the "hinge point" of d = 0.40 for educationally significant impact. These results above d ≈ 1.2 align with the upper range reported in published interventions.
Effect sizes of d = 1.58 (Mathematics) and d = 1.18 (Reading) shift typical learners to the 94th–95th and 88th percentiles respectively, aligning this cohort's growth with the upper range reported in published interventions (Hattie, 2009; Kane & Staiger's MET Project findings (2012); Chetty et al. (2014) Teacher Value-Added Study). These results exceed typical Year 5/6 growth benchmarks and are consistent with high-impact instructional practice reported in the literature. Students achieved gains typically expected after two or more years of instruction.
Quantitative interpretation: The average reader improved by 1.18 standard deviations, moving from the 50th to approximately the 88th percentile.
Research context: Typical reading interventions deliver d = 0.50–0.70. Achieving d = 1.18 represents reading progress almost double the national intervention average, placing these reading outcomes in the upper range reported in published studies.
Combined PAT growth (mean d = 1.38) is aligned with the upper range reported in published interventions, with effect sizes exceeding typical Year 5/6 benchmarks. Applying the ≥8 scale-point PAT growth threshold (a practical benchmark for two years' growth, not an ACER standard), 68.2% (15 of 22) of students achieved at least two years' growth in mathematics and 47.6% (10 of 21) in reading.
Effect sizes were computed using the gain-score method (Cohen's d = mean gain ÷ SD of gain) on matched pre–post data, appropriate for within-cohort designs.
References: Visible Learning (Hattie, 2009); Kane & Staiger's MET Project findings (2012); Hanushek (2011) Economic Value of Teacher Quality; Chetty et al. (2014) Teacher Value-Added Study. Analyses cross-checked against PAT technical manuals.
The study was conducted in a government primary school in Melbourne's outer west (ICSEA ≈ 930, 17th percentile; 47% language background other than English (LBOTE), 18% Aboriginal and Torres Strait Islander students), representing a richly diverse, high-equity context. Despite these complexity factors, students recorded growth in the upper range reported in published classroom studies.
Daily routines combined explicit instruction with peer-assisted learning and weekly progress monitoring. This approach aligns with Rosenshine's Principles of Instruction (2012) and Hattie's synthesis of high-impact strategies (2009). Partner Reading and Paragraph Shrinking routines are based on Fuchs et al.'s Peer-Assisted Learning Strategies (1997) and integrated into Tier 1 using Burns et al. (2016).
Assessment window: 12 months · n = 22 students · Mean gain = 11.40 scale points · SDgain = 7.21 · Mean pre = 113.27 · Mean post = 124.67 · Cohen's d = 1.58 · Hedges' g = 1.52
| Student ID | Pre-Test | Post-Test | Gain | Growth Visual |
|---|---|---|---|---|
| Student 1 | 136.1 | 155.5 | +19.4 | |
| Student 2 | 124.8 | 136.2 | +11.4 | |
| Student 3 | 119.5 | 135.5 | +16.0 | |
| Student 4 | 120.4 | 127.9 | +7.5 | |
| Student 5 | 110.8 | 127.3 | +16.5 | |
| Student 6 | 121.2 | 127.1 | +5.9 | |
| Student 7 | 117.8 | 126.9 | +9.1 | |
| Student 8 | 120.4 | 125.5 | +5.1 | |
| Student 9 | 113.9 | 124.5 | +10.6 | |
| Student 10 | 115.7 | 124.3 | +8.6 | |
| Student 11 | 91.5 | 124.3 | +32.8 | |
| Student 12 | 114.9 | 124.1 | +9.2 | |
| Student 13 | 116.3 | 123.4 | +7.1 | |
| Student 14 | 116.2 | 122.9 | +6.7 | |
| Student 15 | 114.0 | 122.9 | +8.9 | |
| Student 16 | 109.8 | 122.5 | +12.7 | |
| Student 17 | 113.4 | 121.2 | +7.8 | |
| Student 18 | 96.8 | 120.2 | +23.4 | |
| Student 19 | 107.5 | 116.5 | +9.0 | |
| Student 20 | 96.6 | 110.2 | +13.6 | |
| Student 21 | 96.6 | 104.7 | +8.1 | |
| Student 22 | 104.3 | 104.3 | +0.0 | |
| Student 23 | 96.8 | 107.0 | +10.2 |
Assessment window: 12 months · n = 21 students · Mean gain = 8.22 scale points · SDgain = 6.95 · Mean pre = 114.54 · Mean post = 122.76 · Cohen's d = 1.18 · Hedges' g = 1.14
| Student ID | Pre-Test | Post-Test | Gain | Growth Visual |
|---|---|---|---|---|
| Student 1 | 115.5 | 138.3 | +22.8 | |
| Student 2 | 129.5 | 135.5 | +6.0 | |
| Student 3 | 125.1 | 134.7 | +9.6 | |
| Student 4 | 116.7 | 131.7 | +15.0 | |
| Student 5 | 120.7 | 131.4 | +10.7 | |
| Student 6 | 128.9 | 129.8 | +0.9 | |
| Student 7 | 119.4 | 128.9 | +9.5 | |
| Student 8 | 111.1 | 127.1 | +16.0 | |
| Student 9 | 124.1 | 125.1 | +1.0 | |
| Student 10 | 118.9 | 124.3 | +5.4 | |
| Student 11 | 120.9 | 123.9 | +3.0 | |
| Student 12 | 116.9 | 118.8 | +1.9 | |
| Student 13 | 111.9 | 118.5 | +6.6 | |
| Student 14 | 86.6 | 118.5 | +31.9 | |
| Student 15 | 115.5 | 116.8 | +1.3 | |
| Student 16 | 108.2 | 114.8 | +6.6 | |
| Student 17 | 88.6 | 111.6 | +23.0 | |
| Student 18 | 101.9 | 110.2 | +8.3 | |
| Student 19 | 92.6 | 107.2 | +14.6 | |
| Student 20 | 102.3 | 105.1 | +2.8 | |
| Student 21 | 99.1 | 103.5 | +4.4 |
Replicated Effect Sizes
Replicated effect sizes across four consecutive cohorts (2022–2025).
Effect sizes and ≥2-year growth proportions were recalculated in R 4.5.2 (November 2025) using the gain-score method on matched pre–post data (n = 21–22). Analyses verified against ACER PAT technical manuals and benchmarked to national norms (Hattie, 2009).
Study Limitations: Single-school cohort design without randomized control group. While effect sizes are benchmarked against national norms, causal attribution requires controlled comparison. Results reflect within-cohort growth and may be influenced by cohort-specific factors.
Implementation Note: These outcomes were achieved with standard class sizes (21–22 students), regular curriculum time blocks (90 min/day literacy + numeracy), and no additional staffing or funding. Evidence-based routines included daily explicit instruction (Rosenshine's Principles of Instruction (2012)), Partner Reading & Paragraph Shrinking (Fuchs et al. (1997) Peer-Assisted Learning Strategies; Burns et al. (2016) Tier 1 Reading Framework) and weekly progress monitoring with targeted intervention grouping.
Methodology Transparency: Analysis code, simulation protocols, and methodological documentation available in repository. Contact for access to anonymized data extracts and pre-post matching protocols.
Research notes: Explicit instruction and daily review informed by Rosenshine (2012) and Hattie (2009); peer-assisted learning draws on Fuchs et al. (1997) and Burns et al. (2016). Full references →
Grade 5/6 · Victorian Government School · North Western Victorian Region (NWVR)
Across 2024, the cohort recorded effect sizes in the upper range of published interventions, with independent corroboration across multiple assessment domains.
Matched PAT-Mathematics and PAT-Reading growth for the 2024 cohort, with all analysis conducted and interpreted by Jay Spudvilas.
All student data is fully anonymised (Student 1–N). Effect sizes computed using the gain-score method on matched pre–post data.
Cohen's d (effect size)
Very large effect: ≥8 pts growth: 32.1% (9/28).
High GrowthCohen's d (effect size)
Large effect: ≥8 pts growth: 44.4% (12/27).
Strong GrowthWhole-Class Samples
Mathematics n = 28 · Reading n = 27
Full CohortQuantitative interpretation: A Cohen's d of 1.05 means the average student scored 1.05 standard deviations above their baseline. Average gain of 6.31 scale points (SDgain = 6.01), with 32.1% of students achieving ≥8-point gains (9 of 28).
Research context: Effect sizes above d = 1.0 are rare in educational interventions. This result sits within ranges reported in high-performing interventions and is consistent with patterns seen in the research literature.
Effect sizes of d = 1.05 (Mathematics) and d = 0.80 (Reading) indicate strong within-cohort growth across both domains, with outcomes comparable to the top 5–15% of effects reported in published interventions. Combined with independent corroboration (MathFactLab d = 2.26, DIBELS ORF d = 2.48), these results exceed typical Year 5/6 growth benchmarks and are aligned with patterns seen in high-performing interventions. Students achieved gains typically expected after one to two years of instruction, illustrating how evidence-informed routines aligned with published research coincided with measurable gains for this group.
Quantitative interpretation: The average reader improved by 0.80 standard deviations. Average gain of 5.83 scale points (SDgain = 7.31), with 44.4% of students achieving ≥8-point gains (12 of 27).
Research context: Typical reading interventions deliver d = 0.50–0.70. Achieving d = 0.80 represents reading progress 30–60% above the national intervention average, placing the literacy routines used in this classroom within ranges reported in published studies.
Combined PAT growth (mean d = 0.93) is aligned with the upper range reported in published interventions, with effect sizes exceeding typical Year 5/6 benchmarks.
Effect sizes were computed using the gain-score method (Cohen's d = mean gain ÷ SD of gain) on matched pre–post data, appropriate for within-cohort designs.
Figures recalculated 4 Nov 2025 using the gain-score method on matched pre–post data.
n = 28 · Mean gain = 6.31 · SDgain = 6.01 · Cohen's d = 1.05 · Hedges' g = 1.02 · ≥8-point growth: 32.1%
| Student ID | Pre-Test | Post-Test | Gain | Growth Visual |
|---|---|---|---|---|
| Student 1 | 94.7 | 98.1 | +3.4 | |
| Student 2 | 108.7 | 108.6 | -0.1 | |
| Student 3 | 130.7 | 133.8 | +3.1 | |
| Student 4 | 114.4 | 125.2 | +10.8 | |
| Student 5 | 109.6 | 119.6 | +10.0 | |
| Student 6 | 132.3 | 137.2 | +4.9 | |
| Student 7 | 97.0 | 111.0 | +14.0 | |
| Student 8 | 90.0 | 110.9 | +20.9 | |
| Student 9 | 118.9 | 122.5 | +3.6 | |
| Student 10 | 124.1 | 122.8 | -1.3 | |
| Student 11 | 119.2 | 122.4 | +3.2 | |
| Student 12 | 135.7 | 137.4 | +1.7 | |
| Student 13 | 122.2 | 126.3 | +4.1 | |
| Student 14 | 119.8 | 122.0 | +2.2 | |
| Student 15 | 118.3 | 125.9 | +7.6 | |
| Student 16 | 106.1 | 103.8 | -2.3 | |
| Student 17 | 111.0 | 125.9 | +14.9 | |
| Student 18 | 130.0 | 132.8 | +2.8 | |
| Student 19 | 95.2 | 102.0 | +6.8 | |
| Student 20 | 115.3 | 123.5 | +8.2 | |
| Student 21 | 125.3 | 137.5 | +12.2 | |
| Student 22 | 132.0 | 144.4 | +12.4 | |
| Student 23 | 117.2 | 135.4 | +18.2 | |
| Student 24 | 116.7 | 117.8 | +1.1 | |
| Student 25 | 97.5 | 100.8 | +3.3 | |
| Student 26 | 108.4 | 106.2 | -2.2 | |
| Student 27 | 131.1 | 138.3 | +7.2 | |
| Student 28 | 108.5 | 114.5 | +6.0 |
n = 27 · Mean gain = 5.83 · SDgain = 7.31 · Cohen's d = 0.80 · Hedges' g = 0.77 · ≥8-point growth: 44.4%
| Student ID | Pre-Test | Post-Test | Gain | Growth Visual |
|---|---|---|---|---|
| Student 1 | 103.8 | 103.3 | -0.5 | |
| Student 2 | 106.8 | 107.3 | +0.5 | |
| Student 3 | 126.6 | 132.0 | +5.4 | |
| Student 4 | 123.2 | 126.9 | +3.7 | |
| Student 5 | 111.5 | 125.5 | +14.0 | |
| Student 6 | 109.0 | 106.6 | -2.4 | |
| Student 7 | 78.3 | 90.7 | +12.4 | |
| Student 8 | 119.2 | 110.8 | -8.4 | |
| Student 9 | 113.6 | 132.6 | +19.0 | |
| Student 10 | 103.3 | 120.1 | +16.8 | |
| Student 11 | 127.4 | 136.7 | +9.3 | |
| Student 12 | 133.5 | 121.7 | -11.8 | |
| Student 13 | 120.1 | 123.8 | +3.7 | |
| Student 14 | 110.3 | 121.6 | +11.3 | |
| Student 15 | 109.3 | 110.4 | +1.1 | |
| Student 16 | 118.1 | 128.0 | +9.9 | |
| Student 17 | 111.6 | 116.3 | +4.7 | |
| Student 18 | 75.7 | 86.6 | +10.9 | |
| Student 19 | 116.3 | 116.4 | +0.1 | |
| Student 20 | 131.9 | 143.9 | +12.0 | |
| Student 21 | 127.6 | 127.1 | -0.5 | |
| Student 22 | 124.8 | 131.8 | +7.0 | |
| Student 23 | 122.2 | 126.3 | +4.1 | |
| Student 24 | 107.3 | 121.3 | +14.0 | |
| Student 25 | 91.7 | 101.4 | +9.7 | |
| Student 26 | 116.2 | 125.3 | +9.1 | |
| Student 27 | 113.8 | 116.2 | +2.4 |
Data Source: PAT-Mathematics and PAT-Reading (2024). Assessment window varied by student. All student data is fully anonymised (Student 1–N).
Corroboration: Independent measures (MathFactLab, DIBELS ORF) align with PAT growth patterns, providing triangulated evidence of instructional impact.
Implementation Note: Outcomes achieved with standard class sizes (27–28 students) and no additional resources. Daily routines: 15-min explicit math instruction (Rosenshine's Principles of Instruction (2012)), 20-min Partner Reading & Paragraph Shrinking (Fuchs et al. (1997) Peer-Assisted Learning Strategies; Burns et al. (2016) Tier 1 Reading Framework), weekly assessment-informed grouping. Time investment: 90 min/day structured literacy + numeracy blocks, weekly 30-min planning per learning group. Formative assessment and student feedback routines follow Wiliam's work on embedded formative assessment (2011) and Kane & Staiger's MET Project findings (2012).
All 2024 figures recomputed in November 2025 using the gain-score method on matched pre–post data (R 4.5.2).
Research notes: Formative assessment and student surveys guided by Wiliam (2011) and Kane & Staiger (2012); corroboration via MathFactLab and DIBELS ORF. Full references →
Grade 6 · Victorian Government School · South Western Victorian Region (SWVR)
During this 4-month period, the cohort recorded within-cohort growth aligned with the upper band of published interventions.
Focused comprehension routines and explicit instruction produced within-cohort growth aligned with the upper band of published interventions.
Conducted in a government primary school in Melbourne's outer western suburbs; 61% LBOTE, 1% Aboriginal and Torres Strait Islander students. All student data is fully anonymised (Student 1–N). Effect sizes computed using the gain-score method on matched pre–post DIBELS MAZE data.
Cohen's d (effect size)
Very large effect: 4-month window (n = 26).
Strong GrowthWhole-Class Sample
Grade 6 cohort · 4-month window
Full CohortQuantitative interpretation: A Cohen's d of 1.16 means the average student scored 1.16 standard deviations above their baseline. Average gain of 6.81 points (SDgain = 5.85), with mean scores rising from 12.54 to 19.35 (Hedges' g = 1.13).
Research context: DIBELS MAZE assesses reading comprehension via a cloze procedure. Achieving d = 1.16 in a 4-month window substantially exceeds typical short-term intervention benchmarks, placing these outcomes in the top 5–10% of published reading interventions. These outcomes sit well above typical short-term intervention benchmarks for DIBELS MAZE and highlight what this group achieved in a compressed window.
Effect sizes were computed using the gain-score method (Cohen's d = mean gain ÷ SD of gain) on matched pre–post data, appropriate for within-cohort designs.
Figures computed 4 Nov 2025 using the gain-score method on matched pre–post data.
n = 26 · Mean gain = 6.81 · SDgain = 5.85 · Cohen's d = 1.16 · Hedges' g = 1.13 · 4-month assessment window
| Student ID | Pre-Test | Post-Test | Gain | Growth Visual |
|---|---|---|---|---|
| Student 1 | 12.5 | 11.5 | -1.0 | |
| Student 2 | 11.0 | 18.0 | +7.0 | |
| Student 3 | 13.5 | 19.0 | +5.5 | |
| Student 4 | 17.5 | 27.0 | +9.5 | |
| Student 5 | 14.0 | 20.0 | +6.0 | |
| Student 6 | 18.0 | 29.0 | +11.0 | |
| Student 7 | 15.0 | 15.0 | +0.0 | |
| Student 8 | 5.0 | 14.0 | +9.0 | |
| Student 9 | 10.5 | 18.5 | +8.0 | |
| Student 10 | 37.0 | 54.0 | +17.0 | |
| Student 11 | 13.5 | 16.5 | +3.0 | |
| Student 12 | 25.5 | 26.0 | +0.5 | |
| Student 13 | 7.5 | 7.5 | +0.0 | |
| Student 14 | 9.0 | 11.5 | +2.5 | |
| Student 15 | 10.0 | 16.5 | +6.5 | |
| Student 16 | 11.0 | 10.5 | -0.5 | |
| Student 17 | 3.0 | 7.5 | +4.5 | |
| Student 18 | 4.0 | 11.0 | +7.0 | |
| Student 19 | 15.0 | 24.5 | +9.5 | |
| Student 20 | 16.5 | 20.5 | +4.0 | |
| Student 21 | 7.5 | 15.0 | +7.5 | |
| Student 22 | 3.5 | 4.0 | +0.5 | |
| Student 23 | 9.0 | 33.0 | +24.0 | |
| Student 24 | 13.5 | 26.5 | +13.0 | |
| Student 25 | 7.0 | 18.5 | +11.5 | |
| Student 26 | 16.5 | 28.0 | +11.5 |
Context: This cohort was taught over a 4-month period (2023). DIBELS MAZE is a standardized reading comprehension assessment. All student data is fully anonymised (Student 1–N).
Implementation Note: Compressed 4-month intervention used daily 20-min explicit comprehension instruction (Rosenshine's Principles of Instruction (2012)) with MAZE practice (DIBELS MAZE). Standard class size (26 students), no additional resources. Demonstrates how focused, evidence-based routines can accelerate outcomes within regular curriculum constraints. The focus on reading comprehension and fluency reflects frameworks from Kilpatrick (2015) for preventing reading difficulties.
Figures computed in R 4.5.2 (November 2025) using the gain-score method on matched pre–post data.
Research notes: Tier 1 reading comprehension routines draw on Rosenshine (2012), Kilpatrick (2015), and DIBELS MAZE assessment framework. Full references →
Grade 5/6 · Victorian Government School · South Western Victorian Region (SWVR)
In a national pilot of student voice, agency and perception measures, this Grade 5/6 cohort ranked at the 97th percentile nationally, well above the Top 10 percent benchmark across every domain.
Surveyed learners attended a Victorian government primary school in Melbourne's outer western suburbs; the cohort included 41% LBOTE and 7% Aboriginal and Torres Strait Islander students. The PIVOT instrument captures student voice, agency, and perception across relationships, instruction, and classroom environment.
Analysis used a 5-million iteration Monte Carlo simulation benchmarked against the Pivot/Cyber Safety Project dataset, with all student data fully anonymised (Student 1–N).
Cohen's d (Medium-Large)
Student voice averaged +0.50 over staff across 10 items (focus, care, clarity).
Top 3%Monte Carlo Estimate
5M-simulation benchmark ranks Jay ahead of 97% of teachers in the Top-10% pilot.
Helps Students Focus
Classroom environment composite (focus + wellbeing) landed in the national Top 3%.
Quantitative interpretation: Students rated teaching quality +0.50 points above school-wide average (6-point scale) across 10 surveyed dimensions. Effect size (d = 0.56) represents a medium-large positive impact on student perception.
Research context: Typical teacher effects on student perception range from d = 0.20–0.40. Achieving d = 0.56 places these perception outcomes within ranges reported in published studies.
Effect sizes of d = 0.56 (Overall), d = 0.63 (Classroom Environment), and d = 0.74 (Focus Support) represent strong student ratings across the surveyed domains, with outcomes around the 97th percentile nationally (Top 3%). Monte Carlo simulation (5 million iterations) indicates these results are consistent with the mean of the Top 10% benchmark from the Cyber Safety Project/Pivot (2025), exceeding typical teacher perception benchmarks and aligning with patterns reported in high-performing classrooms. These results sit near the upper end of national benchmarks for perception surveys, reflecting how this group rated clarity, support and learning environment in 2022.
Classroom Environment (d = 0.63): Students reported exceptional clarity, focus support, and behavioral expectations. Strongest item: "This teacher helps me focus on learning" (d = 0.74, large effect).
Instruction (d = 0.56): High ratings on responsiveness to feedback, connections to prior learning, and critical thinking encouragement.
Relationships (d = 0.51): Strong student perception of care, support, and respect. Scores exceed all six national Top 10% benchmark items.
Combined perception scores (mean d = 0.56) are aligned with the upper range reported in published teacher effectiveness studies, with effect sizes exceeding typical benchmarks.
Effect sizes were computed using the gain-score method (Cohen's d = mean gain ÷ SD) benchmarked against school-wide averages and national Top 10% data.
Analysis conducted 4 Nov 2025; Monte Carlo simulation code and results available for review.
| Item | Jay's Score | School Avg | Difference | Cohen's d | Effect |
|---|---|---|---|---|---|
| Helps me focus on learning | 5.69 | 5.02 | +0.67 | 0.74 | Large |
| Makes changes from feedback | 5.59 | 4.94 | +0.65 | 0.72 | Large |
| Cares about my wellbeing | 5.69 | 5.10 | +0.59 | 0.66 | Medium-Large |
| Supports me if confused | 5.66 | 5.07 | +0.59 | 0.66 | Medium-Large |
| Connects to prior learning | 5.45 | 4.87 | +0.58 | 0.64 | Medium-Large |
| Domain | Jay's Mean | School Mean | Difference | Cohen's d | Hedges' g | Interpretation |
|---|---|---|---|---|---|---|
| Classroom Environment | 5.39 | 4.82 | +0.57 | 0.63 | 0.61 | Medium-Large |
| Instruction | 5.27 | 4.77 | +0.50 | 0.56 | 0.54 | Medium |
| Relationships | 5.42 | 4.97 | +0.45 | 0.51 | 0.49 | Medium |
| Overall (10 items) | 5.37 | 4.86 | +0.50 | 0.56 | 0.54 | Medium-Large |
Effect size conventions: Small (d = 0.2), Medium (d = 0.5), Large (d = 0.8). Hedges' g applies small-sample correction (n ≈ 25).
Mean of 4 Items
Cares, supports, respects, connects to life.
CSP/Pivot (2025)
Mean of top 10% teachers nationally.
d = 0.19 above Top 10%
Exceeds all 6 benchmark items.
Interpretation: Jay's Relationships score (5.42) exceeds the mean of the national Top 10% (5.25), not just the threshold. This places Jay above the 95th percentile nationally. Monte Carlo estimate: 97th percentile.
Data Source: PIVOT Student Survey on Teaching (2022). Survey administered to Grade 5/6 cohort (n ≈ 25 students). School-wide averages represent mean scores across all teaching staff.
Benchmark: National Top 10% data from the Cyber Safety Project & Pivot Evidence & Impact Report (2025), based on pilot study across multiple Australian schools. Student perception data aligns with Kane & Staiger's MET Project (2012) on the value of student surveys for measuring teaching quality.
All analyses conducted in R 4.5.2 (November 2025). Monte Carlo simulation code (5M iterations), item-level data, and full methodological protocols available in repository.
Research notes: Student perception measurement informed by Kane & Staiger (2012) and Pivot/Cyber Safety Project (2025); classroom environment and relationships reflect self-determination theory (Ryan & Deci, 2017). Full references →
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