Free Data Synthesis Quantitative Research Template
Data Synthesis Quantitative Research
Introduction
This study combines data from three evaluations to assess a new educational intervention's impact on student performance. It examines overall effectiveness and variations across schools, offering insights for optimizing implementation and outcomes.
Objective
To evaluate the effectiveness of a new educational intervention in improving student performance across various schools.
Methodology
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Data Sources: Data were collected from three independent studies conducted in different school districts, assessing the impact of the intervention on student test scores over one academic year.
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Sample Size: The combined sample size from the three studies was 1,200 students.
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Data Variables: Student test scores (pre- and post-intervention), school demographics, and intervention dosage.
Data Synthesis Process
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Descriptive Statistics:
Measurement
Pre-Intervention
Post-Intervention
Mean Score
65.4
72.3
Standard Deviation
12.1
11.8
Sample Size (N)
1,200
1,200
Summary:
The average pre-intervention test score was 65.4 with a standard deviation of 12.1. Post-intervention, the average score increased to 72.3 with a standard deviation of 11.8.
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Effect Size Calculation:
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Cohen's d: Measures the magnitude of the intervention effect.
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Formula: d=Mean Post-Intervention Score−Mean Pre-Intervention ScorePooled Standard Deviationd = \frac{\text{Mean Post-Intervention Score} - \text{Mean Pre-Intervention Score}}{\text{Pooled Standard Deviation}}d=Pooled Standard DeviationMean Post-Intervention Score−Mean Pre-Intervention Score
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Pooled Standard Deviation: 12.12+11.822=11.95\sqrt{\frac{12.1^2 + 11.8^2}{2}} = 11.95212.12+11.82=11.95
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Effect Size (d): 72.3−65.411.95=0.58\frac{72.3 - 65.4}{11.95} = 0.5811.9572.3−65.4=0.58
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Interpretation: Cohen's d = 0.58, indicating a moderate effect size.
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Meta-Analysis Results:
Study
Mean Pre-Intervention Score
Mean Post-Intervention Score
Effect Size (d)
95% Confidence Interval (CI)
Study A
64.0
71.0
0.58
[0.45, 0.71]
Study B
66.5
73.0
0.55
[0.42, 0.68]
Study C
65.7
71.5
0.63
[0.50, 0.76]
Overall Effect Size:
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The random-effects model was applied to account for study variability.
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Overall Effect Size (d): 0.55
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95% Confidence Interval: [0.45, 0.65]
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Heterogeneity Analysis:
Statistic
Value
Interpretation
Q Statistic
15.8
p < 0.05 (indicating significant heterogeneity)
I² Statistic
62%
Moderate heterogeneity, suggesting variability among study results
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Subgroup Analysis:
School Type
Mean Effect Size (d)
95% Confidence Interval (CI)
Urban
0.62
[0.48, 0.76]
Rural
0.47
[0.32, 0.62]
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Summary: The intervention had a greater impact in urban schools compared to rural ones.
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Publication Bias Assessment:
7.6 Funnel Plot Analysis:
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Visual inspection of the funnel plot showed no significant asymmetry, suggesting minimal publication bias.
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Conclusion
The educational intervention demonstrates a moderate positive effect on student performance across the studies. The intervention's impact is notably higher in urban schools compared to rural ones. Despite some variability among studies, the overall evidence supports the effectiveness of the intervention, with no significant publication bias detected.
Recommendations
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Further Research: Investigate factors contributing to the varied impact in different school settings, including socio-economic factors and implementation fidelity.
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Long-Term Evaluation: Conduct studies with larger sample sizes and extended follow-up periods to assess the long-term sustainability of the intervention’s effects.
