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5. Be a Data Champion

You've now explored key aspects of data literacy and visualization. As a Data Champion, your role extends beyond simply understanding these concepts. It's about actively promoting a positive data culture within your setting, empowering others to use data effectively, and ensuring that data is used to drive equitable outcomes for all pupils.

This final section provides you with practical activities designed to solidify your knowledge and equip you to champion the data cause. By engaging with these tasks, you'll gain the confidence to:

  • Advocate for Data Literacy: Clearly articulate the importance of data literacy in improving teaching and learning, mirroring the principles highlighted by Education Scotland.
  • Promote Effective Data Visualization: Encourage the use of clear and accurate data visualizations to communicate insights and inform decision-making, building on the techniques you've learned.
  • Foster a Positive Data Culture: Lead by example, demonstrating how data can be used to understand progress, identify challenges, and work collaboratively towards shared goals, particularly in closing the poverty-related attainment gap.
  • Use Data for Equity: Use your knowledge to help identify and address equity issues within your setting.

Let's put your skills into action and empower you to become a true Data Champion!

Data Set: Student Performance Data
Student Name Gender Class SIMD Decile Attendance (%) Homework Completion (%) Prelim (%) Exam (%)
Alice Smith F 10A 2 95 100 78 82
Bob Johnson M 10A 4 88 90 65 70
Carol White F 10B 1 92 95 92 94
David Brown M 10B 3 85 80 85 80
Eve Davis F 10A 5 90 85 70 75
Frank Miller M 10A 2 98 100 95 98
Grace Wilson F 10B 4 82 75 88 85
Harry Moore M 10B 1 75 70 60 65
Ivy Taylor F 10A 3 88 90 90 92
Jack Anderson M 10A 5 95 85 82 88
Kelly Thomas F 10B 2 90 80 75 80
Liam Jackson M 10B 4 85 70 98 95
 
 
Task: Data Analysis and Visualization
  1. Conditional Formatting:
    • Apply conditional formatting to the "Prelim (%)" and "Exam (%)" columns to highlight:
      • Scores above 90% in green.
      • Scores below 70% in red.
    • Use data bars to visualize the "Attendance (%)" and "Homework Completion (%)" columns.
  2. Pivot Tables:
    • Create a pivot table to show the average "Prelim (%)" and "Exam (%)" scores for each class (10A and 10B).
    • Create a pivot table to show the average "Attendance (%)" and "Homework Completion (%)" for each SIMD decile.
    • Create a pivot table to show the average "Exam (%)" score for each gender in each class.
  3. Google Sheets Functions:
    • IMPORTRANGE: If you have another sheet with student names and their corresponding teacher, use IMPORTRANGE to bring that data into this sheet.
    • FILTER: Use the FILTER function to:
      • Show only the data for students in class 10A.
      • Show only the data for students with attendance above 90%.
      • Show only the data for male students who scored above 80% in the exam.
    • Text Functions:
      • If the "Student Name" column had inconsistent capitalization, use the PROPER function to capitalize the first letter of each name.
      • If there were extra spaces in the "Student Name" column, use the TRIM function to remove them.

Additional Tips:

  • This data set is designed to be used in Google Sheets or Microsoft Excel.
  • Feel free to modify or expand the data set to further explore different scenarios.
  • For an extra challenge, try creating different types of charts to visualize the data (e.g., bar charts, scatter plots).

 

Communicating Data to Different Audiences

  • Task: Choose a dataset and create two different data visualizations for it – one for teachers and one for parents.

  • Consider: How would you tailor the visuals and language to each audience?

  • Discuss: What are the challenges of communicating data effectively to different stakeholders?

Predictive Analytics (Simplified)

  • Task: Explore basic predictive modelling using historical student data. For example, can you predict which students might be at risk of failing a course based on their past performance?

  • Tool: Use spreadsheet software

  • Reflection: Discuss the potential benefits and ethical considerations of using predictive analytics in education.

Storytelling with Data

  • Task: Choose a dataset related to student achievement or well-being.

  • Create: Develop a data-driven story that highlights a key trend or insight from the data.

  • Format: This could be a short presentation, a blog post, or even a social media post.

  • Focus: Emphasize clear visuals and a compelling narrative.

Interactive Data Dashboard

  • Task: Design a mock-up of an interactive data dashboard for teachers or school leaders.

  • Tool: Use a design tool like Canva, Figma, or even PowerPoint/Google Slides.

  • Content: What data would you include? How would you visualize it? Consider how users could interact with the dashboard to explore the data.

  • Presentation: Present your dashboard design to a colleague and gather feedback.

 

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