Exploring the relationship between digital connectivity and educational assessment outcomes across the United States.
Introduction
This dashboard explores the relationship between broadband access (FCC Form 477) and educational outcomes (Stanford SEDA test scores) across US counties. We aim to:
Identify correlations between connectivity and student achievement.
Examine variations across different demographic groups.
Provide interactive tools for exploring these connections.
What You Can Explore
Use the interactive map and filters to investigate:
Connectivity vs. Performance: How does internet access correlate with test scores, especially for specific demographic groups?
Performance Over Time: Do changes in scores align with broadband deployment trends (using the 'Year' filter)?
Demographic Insights: How does connectivity relate to performance for different races, genders, or economic statuses?
Geographic Patterns: Drill down into state/county data to compare local and regional trends.
Discover patterns and draw your own conclusions using the provided tools.
Datatable Output
A random sample of 10 rows from the underlying data to illustrate the available fields:
State
County
Year
Subject
Grade Level
Total Connections
Total Score
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Total Connections Over Time
This graph shows the trend of total fixed internet connections across all reporting counties over the years.
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Overall, total fixed internet connections across reporting counties increased between 2009 and 2019. However, the trend shows a sharp decline around 2014, followed by a period of recovery and further growth. Further investigation would be needed to understand the cause of the 2014 anomaly.
Mean Scores Over Time (Math vs. Language)
This graph shows the trend of average assessment scores for Math and Language subjects over the years.
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Average assessment scores for both Math and Language generally improved from 2009 to 2013. After peaking around 2013, Math scores saw a notable decline before leveling off. Language scores peaked slightly later and declined more gradually. The differing trajectories after 2013 suggest potential shifts in educational focus or external factors influencing performance differently across subjects.
Live Data Visualization
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User Research Insights
We conducted interviews with potential users to gather feedback on the dashboard concept and interface. Below are summaries of the key insights:
Interview 1: Dr. Ariel Han
Faculty Member & Researcher (HCI, Learning Sciences, EdTech), USC Iovine and Young Academy
Key Feedback & Insights
Interface feels familiar, resembling curated research datasets.
Expressed positive anticipation for the planned geographic visualization features.
Recommendation: Enhance flexibility by allowing users to define their own correlation queries (select variables) instead of being limited to pre-set options.
Background: Experienced with quantitative analysis, uses LLMs for visualization, familiar with data platforms.
Identified Use Case
Supporting initiatives for rural, underconnected communities (e.g., computational thinking education).
Geographic visualization is seen as ideal for identifying target areas for outreach and resource allocation in such projects.
Potential Actions & Next Steps
Prioritize implementing user-selectable variables for correlation analysis.
Highlight geographic features in documentation/marketing for outreach use cases.
Consider outreach to professionals in EdTech, public service, and rural development.
Overall Conclusion: Dr. Han recognizes the tool's strong potential, especially its geographic capabilities. Implementing user-defined queries is a key suggestion to significantly boost flexibility and relevance for academic research and social impact applications.
