Delta Global School Wellness Data:�-Fall 2024 to Spring 2025�-Quantitative Data Survey�-Statistical Analysis and Visualization

WHAT DO WE KNOW?

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HOW CAN WE KNOW MORE?

Survey Goals

• Understand Student Wellbeing�Gain meaningful insights into students’ emotional, mental, and social experiences at school.

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• Identify Areas for Support�Highlight key wellbeing challenges such as stress, workload, and access to trusted adults.

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• Drive Positive Change�Use data to inform programs, policies, and initiatives that strengthen our school community.

Survey Questions

• How often do you feel positive in school?

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• How often do you feel supported by your teachers and advisors?

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• How often do you feel listened to by your teachers and advisors?

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• How often do you feel listened to and supported by your friends?

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• How do you feel you are managing the workload?

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• To what extent do you feel the workload is making you feel stressed?

Analysis 1: Outliers

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• Are we missing anyone?

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• Overall positive results can hide significant problems

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• Is there a subgroup not doing great?

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• Who are they?

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• Good news and bad news

Outlier Analysis

Questions

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• Who are these outliers?

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• Is this still a problem?

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• What do they need and how do we help them?

Research Proposal

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• See if we find similar outliers in this year’s survey

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• Collect data by year level

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• Collect demographics

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• Use qualitative methods to better identify

Analysis 2: Trend across year

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• Do we see any patterns from one survey to the next?

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• Are we seeing anything statistically significant?

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• If so, at what magnitude?

ANOVA

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• ANOVA (Analysis of Variance) is a statistical test that compares the means of three or more groups to see if the differences are significant.

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• In this survey, ANOVA was used to assess whether student wellbeing changed meaningfully across Term 1, Term 2, and Term 3—not just due to chance.

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Interpreting Data

• F-value�Measures how much the group means differ. A higher F-value suggests a bigger difference between terms.

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• P-value�Tells us whether the result is likely due to chance. A p-value below 0.05 means the difference is statistically significant.

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• Effect Size (η²)�Shows how strong the difference is. Even if something is statistically significant, the effect size tells us if it’s meaningful in practice.

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• Significant�A "Yes" means the change over time is real and reliable—not just random variation.

Middle School Wellness

High School Wellness

Whole School Wellness

What We Know

• Overall student wellbeing remains relatively stable across the school year, with a few key areas showing meaningful change.

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• High School students reported notable improvement in how they manage workload by Term 3.

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• Middle School students consistently felt supported by teachers and advisors, especially in Term 1 and Term 3.

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• Stress levels remained moderate across all terms and school levels, with no significant increase or decrease.

What We Don’t Know

• Why certain wellbeing areas improved or declined — the data shows changes, but not the causes behind them.

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• How individual student experiences differ — the averages hide variation between specific year groups or student backgrounds.

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• Whether external factors (e.g. exams, events) played a role in wellbeing shifts across terms.

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• If current support strategies are effective — we see patterns, but need more feedback to evaluate impact.

What do we need

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• Qualitative data

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• Research design to use respond to data

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• Develop proposals based on data

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• Implementation

Research Proposal

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• First: Gather qualitative data

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• Second: Use qualitative data to inform collection of quantitative data

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• Third: Collect quantitative data

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• Fourth: Develop policy in response

Qualitative Data Collection

• Purpose:�To gather in-depth, student-driven insights that explain the patterns in our survey data.
• Why Focus Groups?
• Encourage group discussion and shared experiences.
• Useful for exploring common themes, building on peer comments.
• Ideal for understanding general school climate and culture.
• Why Interviews?
• Allow for privacy and depth, especially around sensitive topics like stress or workload.
• Help uncover individual experiences that may not emerge in group settings.

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Procedure

• Focus Groups:
• Middle & High School groups
• Mixed by grade level and gender to ensure diverse perspectives.
• Guided by open-ended prompts (e.g., "When do you feel most supported at school?").
• Interviews:
• Voluntary sign-up or targeted invitation based on survey trends.
• Conducted 1:1 in a quiet, safe setting.
• Semi-structured format with room for free expression and storytelling.
• Timeline:
• Sessions held in early Term 1 of the next school year.
• Results summarized and presented to leadership to inform wellbeing planning.

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Data Analysis

• Transcribe responses: Convert audio recordings or notes into written text for detailed review.
• Code themes: Use thematic coding to identify patterns, keywords, and repeated ideas across responses.
• Group by category: Organize insights into key themes (e.g. stress, support, workload, relationships).
• Compare by school level: Highlight differences and similarities between Middle School and High School students.
• Link to survey data: Match qualitative themes with quantitative trends to understand the context behind survey scores.

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Surveys

• Extract key phrases: Use student language and concerns as inspiration for phrasing questions.

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• Test assumptions: Create items that explore potential causes for patterns in the original survey.

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• Pilot new questions: Try revised items with a small student sample before full distribution.

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• Ensure variety: Include a mix of Likert-scale, open-ended, and multiple-choice items.

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• Focus on actionability: Prioritize questions that can inform policy, programming, or student support.

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Other Considerations

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• Timeline in general

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• How often should we collect surveys?

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• When should we collect surveys?

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• When to take action?

Thanks for listening.�Questions?