2025–2026 Wellness Analysis

Comprehensive analysis of student wellbeing data across Middle and High School at Delta Global School, examining belonging, positivity, workload management, and peer and teacher support

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Project Overview

This project involved designing, implementing, and analyzing a comprehensive student wellbeing survey at Delta Global School. The research aimed to understand student emotional, mental, and social experiences to identify areas for support and drive positive change in school policies and programs.

Key Objectives

  • Understand student wellbeing across emotional, mental, and social dimensions
  • Identify key wellbeing challenges including stress, workload, and access to support
  • Use data to inform programs, policies, and initiatives to strengthen the school community
  • Develop improved data collection methodologies for future assessment

Methodology

The study employed a mixed-methods approach, combining quantitative survey data with qualitative insights to provide a comprehensive understanding of student wellbeing.

Survey Design

Developed a comprehensive survey measuring multiple dimensions of student wellbeing using Likert-scale questions and open-ended responses.

Data Collection

Administered surveys to middle and high school students across three terms (Fall 2024, Winter 2024, Spring 2025) to track changes over time.

Statistical Analysis

Used ANOVA to compare means across multiple groups and terms, identifying statistically significant changes in wellbeing indicators.

Qualitative Follow-up

Conducted focus groups and interviews to contextualize quantitative findings and gather in-depth student perspectives.

Key Findings

Overall Trends

  • Student wellbeing remained relatively stable across the school year with minor fluctuations
  • High school students reported notable improvement in workload management by Term 3
  • Middle school students consistently felt supported by teachers and advisors
  • Stress levels remained moderate across all terms with no significant increases

Outlier Analysis

Identified student subgroups whose experiences differed significantly from the overall positive trends, highlighting the importance of looking beyond averages to understand the full picture of student wellbeing.

Outlier Analysis Chart

Visualization of outlier students whose experiences differed significantly from overall trends

Critical Questions from Outlier Analysis

  • Who are the outliers in our wellbeing data?
  • What specific challenges do these students face?
  • How can we better support these student subgroups?
  • What changes to our data collection would help identify these students earlier?

Statistical Analysis

Used Analysis of Variance (ANOVA) to determine whether changes in wellbeing across terms were statistically significant or due to random variation.

F-value

Measured how much group means differed between terms, with higher values indicating more substantial differences.

P-value

Determined statistical significance, with values below 0.05 indicating changes were unlikely due to chance.

Effect Size (η²)

Measured the practical significance of findings, distinguishing between statistically significant and educationally meaningful changes.

Statistical Analysis Results

Visualization of ANOVA results showing significant changes across terms

Research Implications

What We Know

  • Overall patterns of student wellbeing across the school year
  • Areas of strength in teacher and advisor support
  • Workload management improvements in high school
  • Consistent moderate stress levels across terms

What We Don't Know

  • Why certain wellbeing areas improved or declined
  • How individual student experiences differ beyond averages
  • The impact of external factors (exams, events) on wellbeing
  • The effectiveness of current support strategies

Recommendations & Future Research

Proposed Data Collection Improvements

  • Collect demographic data to better identify subgroup differences
  • Implement longitudinal tracking of individual students
  • Add qualitative components to understand the "why" behind the numbers
  • Develop targeted surveys for identified at-risk groups

Research Timeline

Phase 1: Qualitative Data Collection

Conduct focus groups and interviews to gather in-depth student insights

Phase 2: Survey Refinement

Use qualitative findings to improve quantitative survey instruments

Phase 3: Expanded Data Collection

Implement improved surveys with broader demographic tracking

Phase 4: Policy Development

Develop targeted wellbeing policies based on comprehensive findings

Proposed Wellbeing Initiatives

  • Targeted support programs for identified outlier groups
  • Workload management strategies for high school students
  • Enhanced advisor training based on student feedback
  • Regular wellbeing check-ins rather than annual surveys

Project Resources

Download Presentation Slides View Full Data Analysis Research Methodology Document

Skills Demonstrated

Research Design

Developed comprehensive mixed-methods research approach

Data Analysis

Applied statistical methods including ANOVA to educational data

Survey Methodology

Designed and implemented effective data collection instruments

Educational Leadership

Translated research findings into actionable policy recommendations