Improving Our School Through Student Surveys
Created byDel Shepherd
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Improving Our School Through Student Surveys

Grade 7MathEnglish10 days
Seventh-grade students explore the use of surveys and statistical methods to analyze student opinions and suggest school improvements. Through a structured project, they design unbiased surveys, utilize random sampling for data collection, and apply statistical concepts like measures of center and variability. The project culminates with students presenting their data-backed recommendations to school stakeholders, enhancing their analytical and communication skills while connecting mathematics and English disciplines.
SurveysStatisticsRandom SamplingData AnalysisSchool ImprovementGraphical RepresentationStudent Engagement
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Inquiry Framework

Question Framework

Driving Question

The overarching question that guides the entire project.How can we, as researchers, use surveys and statistical methods to analyze student opinions, and make informed recommendations to improve our school?

Essential Questions

Supporting questions that break down major concepts.
  • How do we collect data from a population through sampling?
  • What is the importance of random sampling in statistics?
  • How can we use measures of center and variability to make inferences about a population?
  • What role do surveys play in understanding student opinions and interests?
  • How can data representation (like box plots and dot plots) help in comparing data distributions?
  • In what ways can we ensure a survey sample is representative of a whole school population?
  • Why is it important to understand the variability in data when making predictions or estimates?
  • How can statistics help improve decision-making within a school setting?

Standards & Learning Goals

Learning Goals

By the end of this project, students will be able to:
  • Students will understand and apply the concept of random sampling to conduct surveys that accurately reflect a larger population.
  • Students will analyze survey data to make informed decisions about school improvements based on student opinions and interests.
  • Students will be able to create and interpret graphical data representations, such as box plots and dot plots, to identify trends and differences in survey results.
  • Students will learn to calculate and interpret measures of center (mean and median) and variability (interquartile range, mean absolute deviation) to draw inferences from data sets.
  • Students will develop communication skills by presenting their findings and recommendations on school improvements to relevant stakeholders.

Kentucky Academic Standards

KY.7.SP.1
Primary
Understand that statistics can be used to gain information about a population by examining a sample of the population; generalizations about a population from a sample are valid only if the sample is representative of that population. Understand that random sampling tends to produce representative samples and support valid inferences.Reason: The project involves understanding statistics to gain information about student opinions and interests using surveys, aligning perfectly with understanding how statistics reflect a population through samples.
KY.7.SP.2
Primary
Use data from a random sample to draw inferences about a population with an unknown characteristic of interest.Reason: Students are tasked with drawing inferences from survey data, necessitating an understanding of using data from random samples, which aligns directly with this standard.
KY.7.SP.3
Secondary
Describe the degree of visual overlap (and separation) from the graphical representations of two numerical data distributions with similar variabilities with similar contexts, measuring the difference between the centers by expressing this difference as a multiple of a measure of variability.Reason: The project involves using graphical representations like box plots to compare student opinion data distributions, which corresponds with this standard.
KY.7.SP.4
Primary
Calculate and use measures of center (mean and median) and measures of variability (interquartile range when comparing medians and mean absolute deviation when comparing means) for numerical data from random samples to draw informal comparative inferences about two populations.Reason: Students will calculate and use measures of center and variability to analyze survey results, aligning this project with the standard of drawing inferences from numerical data.

Entry Events

Events that will be used to introduce the project to students

The School Improvement Challenge: A Statistical Adventure

In this adventure, students are tasked with a school improvement challenge where they use statistics to make informed suggestions. The event sets up a competitive, yet collaborative, environment where teams work to gather and analyze data effectively, fostering a deeper understanding of how quantitative insights can drive tangible change in familiar settings.
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Portfolio Activities

Portfolio Activities

These activities progressively build towards your learning goals, with each submission contributing to the student's final portfolio.
Activity 1

Survey Blueprint Workshop

This activity introduces students to the process of designing a survey. Through guided practice, students will learn to create clear, unbiased questions that will elicit informative responses about school improvements.

Steps

Here is some basic scaffolding to help students complete the activity.
1. Introduce the concept of survey design and its importance in gathering accurate data. Discuss the essentials of creating unbiased questions.
2. Students work in pairs to brainstorm areas for potential school improvements they want to explore.
3. Guide students in drafting questions for their survey. Encourage the creation of both multiple-choice and open-ended questions.
4. Review questions with peers or the teacher for feedback and revision to ensure clarity and neutrality.
5. Finalize the survey by selecting the best questions for inclusion.

Final Product

What students will submit as the final product of the activityA finalized survey ready to be distributed among a sample population of students.

Alignment

How this activity aligns with the learning objectives & standardsAligns with KY.7.SP.1; introduces the concept of collecting data from a population using a sample.
Activity 2

Random Sampling Strategy Session

Through this activity, students will explore the significance of random sampling. They will design a sampling strategy for distributing their surveys to ensure a representative student sample reflecting the school population.

Steps

Here is some basic scaffolding to help students complete the activity.
1. Discuss the importance of random sampling and its role in making valid inferences about the whole population.
2. Provide examples of random and non-random sampling. Highlight the potential biases with non-random methods.
3. Students collaborate to outline a plan for distributing their survey to a random sample of the student population.
4. Review and evaluate each sampling plan as a class, providing constructive feedback on representation and potential biases.

Final Product

What students will submit as the final product of the activityA detailed plan describing the sampling strategy to be used in collecting survey responses.

Alignment

How this activity aligns with the learning objectives & standardsAligns with KY.7.SP.1; emphasizes the need for representative samples in making valid generalizations.
Activity 3

Data Collection & Analysis Lab

In this collaborative lab activity, students will collect data using their surveys and begin the analysis process, focusing on measures of center and variability.

Steps

Here is some basic scaffolding to help students complete the activity.
1. Distribute the finalized surveys to the students selected through the sampling strategy.
2. Collect completed surveys and begin the initial data entry into spreadsheets for electronic analysis.
3. Introduce students to measures of center (mean, median) and variability (range, interquartile range, mean absolute deviation).
4. Students calculate these statistics for their data sets, identifying trends and anomalies.

Final Product

What students will submit as the final product of the activityA comprehensive dataset complete with calculated measures of center and variability.

Alignment

How this activity aligns with the learning objectives & standardsAligns with KY.7.SP.4; focuses on calculating and using measures of center and variability for data analysis.
Activity 4

Graphical Insight Illustration

This activity teaches students to create and interpret box plots and dot plots, using them to compare and visualize survey data. Students will identify overlaps and differences in data distributions.

Steps

Here is some basic scaffolding to help students complete the activity.
1. Guide students in plotting their surveyed numerical data using both box plots and dot plots.
2. Discuss how these graphical representations can visually illustrate trends, overlaps, and differences between data distributions.
3. Students compare their plots against one another, highlighting key differences or similarities.
4. Class discussion on how observed data overlaps and separations could affect conclusions drawn from the data.

Final Product

What students will submit as the final product of the activityA series of box and dot plots comparing student opinion data.

Alignment

How this activity aligns with the learning objectives & standardsAligns with KY.7.SP.3; involves using visual data representations to describe distribution overlaps and differences.
Activity 5

Inference & Recommendation Declaration

Students will synthesize their findings into actionable recommendations for school improvements. They will draw inferences from their data analysis and graphical insights to support their suggestions.

Steps

Here is some basic scaffolding to help students complete the activity.
1. Review the analyzed survey data and graphical illustrations.
2. Brainstorm possible recommendations for school improvements based on collected data.
3. Craft a persuasive report that includes statistical evidence and recommendations.
4. Prepare a presentation for school stakeholders incorporating key data insights and suggested actions.

Final Product

What students will submit as the final product of the activityA detailed report and presentation showcasing students' recommendations for school improvements backed by statistical data.

Alignment

How this activity aligns with the learning objectives & standardsAligns with KY.7.SP.2; focuses on using random sample data to make inferences about a population and suggest informed actions.
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Rubric & Reflection

Portfolio Rubric

Grading criteria for assessing the overall project portfolio

Survey-Based School Improvement Project Rubric

Category 1

Survey Design

Assesses the ability to create unbiased, clear, and relevant survey questions.
Criterion 1

Question Clarity

Evaluates the clarity and simplicity of the survey questions.

Exemplary
4 Points

All survey questions are exceptionally clear, concise, and designed to elicit accurate responses.

Proficient
3 Points

Most survey questions are clear, concise, and effective in eliciting accurate responses.

Developing
2 Points

Some survey questions lack clarity and may not elicit accurate responses.

Beginning
1 Points

Most survey questions are unclear and do not effectively elicit accurate responses.

Criterion 2

Bias Avoidance

Measures the extent to which survey questions are free from bias.

Exemplary
4 Points

Questions are completely unbiased and neutral, ensuring fair responses from all participants.

Proficient
3 Points

Most questions are unbiased, with one or two needing slight adjustments for neutrality.

Developing
2 Points

Questions show some bias, potentially influencing participants' responses.

Beginning
1 Points

Questions are biased, leading to misinformed responses.

Category 2

Sampling Strategy

Evaluates the plan for selecting a representative sample of the school population.
Criterion 1

Representativeness

Assesses how well the sampling strategy represents the entire school population.

Exemplary
4 Points

The sampling strategy is exceptionally well-designed, ensuring a highly representative sample.

Proficient
3 Points

The sampling strategy is sound, with a mostly representative sample.

Developing
2 Points

The sampling strategy is somewhat flawed, resulting in a partially representative sample.

Beginning
1 Points

The sampling strategy is poorly designed and does not yield a representative sample.

Criterion 2

Randomization

Measures the degree of randomness in the sampling method.

Exemplary
4 Points

The sampling method is completely randomized, eliminating bias.

Proficient
3 Points

The sampling method is mostly randomized, with minimal potential for bias.

Developing
2 Points

The sampling method includes some random elements but is mostly systematic.

Beginning
1 Points

The sampling method lacks randomization, leading to potential bias.

Category 3

Data Analysis and Interpretation

Assesses the ability to accurately analyze data and draw informed conclusions.
Criterion 1

Statistical Calculations

Evaluates the accuracy of calculations for measures of center and variability.

Exemplary
4 Points

All statistical calculations are accurate and demonstrate a sophisticated understanding of data analysis.

Proficient
3 Points

Most statistical calculations are accurate and demonstrate a good understanding of data analysis.

Developing
2 Points

Some statistical calculations are incorrect, indicating basic understanding of data analysis.

Beginning
1 Points

Most calculations are incorrect, indicating minimal understanding of data analysis.

Criterion 2

Graphical Representation

Evaluates the ability to use graphs to compare data distributions.

Exemplary
4 Points

Graphical representations are accurate, detailed, and clearly illustrate data distribution comparisons.

Proficient
3 Points

Most graphical representations are accurate and illustrate data distribution comparisons well.

Developing
2 Points

Some graphs lack accuracy and clarity in illustrating data distribution comparisons.

Beginning
1 Points

Graphical representations are inaccurate and unclear in illustrating data distribution comparisons.

Criterion 3

Inference and Conclusion

Assesses the ability to draw relevant conclusions and make recommendations based on data.

Exemplary
4 Points

Conclusions and recommendations are highly logical, well-supported by data, and innovative.

Proficient
3 Points

Conclusions and recommendations are logical and well-supported by data.

Developing
2 Points

Conclusions and recommendations are somewhat supported by data, with room for logical consistency.

Beginning
1 Points

Conclusions and recommendations are poorly supported by data and lack logical consistency.

Category 4

Communication and Presentation

Measures the ability to effectively communicate findings and persuade stakeholders.
Criterion 1

Clarity of Presentation

Assesses how clearly and effectively findings are communicated.

Exemplary
4 Points

The presentation is engaging, exceptionally clear, and effectively communicates findings to stakeholders.

Proficient
3 Points

The presentation is clear and effectively communicates findings to stakeholders.

Developing
2 Points

The presentation communicates findings but lacks clarity and effectiveness.

Beginning
1 Points

The presentation is unclear and ineffective in communicating findings.

Criterion 2

Use of Evidence

Evaluates the use of statistical evidence to support arguments in the presentation.

Exemplary
4 Points

The presentation uses comprehensive statistical evidence in a compelling manner to support arguments.

Proficient
3 Points

The presentation uses sufficient statistical evidence to support arguments.

Developing
2 Points

The presentation uses limited statistical evidence to support arguments.

Beginning
1 Points

The presentation lacks statistical evidence and fails to support arguments.

Reflection Prompts

End-of-project reflection questions to get students to think about their learning
Question 1

Reflect on the process of designing your survey. What challenges did you encounter, and how did you overcome them?

Text
Required
Question 2

Explain how random sampling helped you ensure that your survey results were representative of the school population.

Text
Required
Question 3

How confident are you in your ability to calculate measures of center and variability after completing this project?

Scale
Required
Question 4

Which data visualization technique (box plot or dot plot) did you find most effective in communicating your results?

Multiple choice
Required
Options
Box Plot
Dot Plot
Both were equally effective
Neither was effective
Question 5

How likely are you to apply the statistical methods learned in this project to real-world situations outside of a school setting?

Scale
Required