School Performance

 

That's an ambitious goal! Scatter plots are powerful for revealing relationships, trends, and outliers in data. For a school performance data app, the most effective ideas will focus on clear, actionable insights for students, teachers, parents, and administrators.

Here are 100 scatter plot ideas, broken down into categories based on the kind of correlation they can reveal. The data points will typically be individual students, classes, subjects, or schools over a specific time period (e.g., a semester, year, or unit).

🚀 I. Student-Level Performance & Effort (1-30)

These plots focus on individual student data to find correlations between effort, specific behaviors, and academic outcomes.

A. Effort vs. Achievement

1. Hours Studied vs. Exam Score (Individual Student)

2. Homework Completion Rate vs. Course Grade

3. App/Platform Usage Time vs. Quiz Average

4. Attendance Rate (%) vs. Final Grade (%)

5. Drafts Submitted (Essay) vs. Final Essay Score

6. Minutes Read (Reading Log) vs. Reading Comprehension Score

7. Time to Complete Test vs. Test Score (Identify fast/accurate vs. slow/careful students)

8. Formative Assessment Average vs. Summative Assessment Score

9. Practice Problems Solved vs. Unit Exam Score

10. Number of Extra Credit Assignments vs. Overall Grade

B. Skills vs. Skills (Cross-Subject Correlation)

11. Math Grade vs. Physics Grade (Identify STEM aptitude)

12. Reading Comprehension Score vs. History Essay Score

13. Vocabulary Test Score vs. Foreign Language Grade

14. Programming Assignment Score vs. Math Test Score

15. Art Class Grade vs. Creative Writing Score

16. In-Class Participation Score vs. Group Project Score

17. Pre-test Score vs. Post-test Score (Show learning gain)

18. Midterm Grade vs. Final Grade (Consistency/Improvement)

19. Typing Speed (WPM) vs. Digital Presentation Score

20. Lab Report Score vs. Lecture Exam Score

C. Behavior & Wellbeing vs. Performance

21. Disciplinary Referrals vs. GPA

22. Sleep Hours Reported vs. Next Day's Quiz Score

23. Extracurricular Activities (Count) vs. GPA (Look for the "sweet spot")

24. Library Visits/Resources Checked Out vs. Research Project Grade

25. Self-Reported Stress Level vs. Test Score

26. Time Spent on Social Media (Self-Reported) vs. Homework Completion Rate

27. Peer-Review Score vs. Final Assignment Score

28. Days Absent (Unexcused) vs. Course Failure Rate

29. Tutoring Sessions Attended vs. Exam Score Improvement

30. Parent-Teacher Conference Attendance vs. Student Grade Change

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🏫 II. Class & Subject Analysis (31-60)

These plots aggregate data to compare different subjects, teachers, or intervention groups.

A. Teacher and Class Comparison

31. Class Average (Teacher A) vs. Class Average (Teacher B) (Color-coded by subject)

32. Teacher Experience (Years) vs. Class Average Test Scores

33. Class Size vs. Student Grade Distribution (Standard Deviation)

34. Average Time-on-Task (Class) vs. Average Test Score (Class)

35. Teacher Absenteeism Rate vs. Subject Pass Rate

36. Textbook Reading Level vs. Comprehension Quiz Average

37. Funding per Student (Class/Program) vs. Average Subject Grade

38. Technology Usage (Hours/Week) vs. End-of-Year Proficiency

39. Average Teacher Rating (Student Survey) vs. Average Test Score

40. Percentage of Students Reaching Mastery vs. Teacher Professional Development Hours

B. Curriculum and Standard Alignment

41. Standard A Mastery (%) vs. Standard B Mastery (%) (Identify co-dependent skills)

42. Difficulty Rating (Question) vs. Student Success Rate (%)

43. Curriculum Unit Time Allocation vs. Unit Mastery Score

44. Average Item Analysis Score (Subject A) vs. Average Item Analysis Score (Subject B)

45. Subject Retention Score (6 months post-course) vs. Final Exam Grade

46. Cognitive Load Rating (Activity) vs. Student Engagement Score

47. Multiple Choice Score vs. Free Response Score (Diagnostic for recall vs. application)

48. Student Growth Percentile (SGP) in Math vs. Reading

49. Average Grade in Prerequisite Course vs. Average Grade in Current Course

50. Number of Curriculum Revisions vs. Year-over-Year Score Change

C. Intervention and Program Effectiveness

51. Time in Intervention Program vs. Standardized Test Score Change

52. Cost of Program per Student vs. Average Grade Improvement

53. Special Education Service Hours vs. Inclusion Class Performance

54. EL (English Learner) Support Hours vs. English Proficiency Gain

55. Attendance at Study Hall vs. Grade in Most Difficult Subject

56. Group Project Score vs. Individual Project Score (Assess collaborative versus independent performance)

57. Peer Tutor Score vs. Tutee Score

58. Lunch Program Participation vs. Afternoon Class Test Scores

59. School Budget Allocation (Per Subject) vs. Subject Average Score

60. Number of Field Trips vs. Student Engagement Score

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🌐 III. School, District, and Equity (61-80)

These plots compare schools or analyze demographics to address systemic performance issues.

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A. School-Wide Comparison (for a district dashboard)

61. School Budget (Per Student) vs. Graduation Rate

62. Student-to-Counselor Ratio vs. College Acceptance Rate

63. Teacher Turnover Rate (%) vs. School-Wide Test Score Average

64. Parent Volunteer Hours vs. School Climate Survey Score

65. Safety Incidents per 100 Students vs. Student Attendance Rate

66. Mean SAT/ACT Score vs. Free/Reduced Lunch Rate (%)

67. Library Book Count vs. Average Reading Level of Graduates

68. Facility Age (Years) vs. Standardized Test Scores

69. Per-Pupil Expenditure on Tech vs. Computer Science Course Enrollment

70. Average Class Size (School A) vs. Average Class Size (School B) (Color-coded by subject)

B. Equity and Demographic Analysis

71. Socioeconomic Status (SES) Index vs. Math Proficiency Rate (Color-coded by Ethnicity)

72. Gender vs. Science Exam Scores

73. English Learner Status vs. Overall GPA

74. Student Disability Category vs. Grade Level Proficiency

75. Enrollment in AP Courses (%) vs. Minority Enrollment (%)

76. Distance from Home to School vs. Tardiness Rate

77. Student Birth Month vs. Grade Level Performance (Relative Age Effect)

78. First-Generation College-Bound Student % vs. Guidance Counselor Meeting Count

79. Homelessness Status vs. Standardized Test Score

80. Rural/Urban/Suburban Setting vs. Average Art/Music Class Enrollment

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📊 IV. Advanced Visualization & User Interaction (81-100)

These ideas focus on features, filters, and enhancements for the scatter plot within the app itself.

A. Interactive Features

81. Dynamic Trendline Adjustment: Allow users to switch between linear, quadratic, and exponential trendlines.

82. Confidence Interval Shading: Display the confidence band around the trendline to show prediction reliability.

83. Outlier Flagging/Annotation: Automatically highlight points $2\sigma$ or $3\sigma$ from the mean with an explainer note.

84. Zoom and Pan Functionality: Seamlessly explore dense clusters of data points.

85. Quadrants (4-Square Analysis): Automatically divide the plot into four quadrants (e.g., High Effort/Low Achievement, Low Effort/High Achievement).

86. Bubble Chart Overlay (3rd Variable): Use dot size to represent a third variable (e.g., Attendance vs. Final Grade, where dot size is Number of Tutoring Sessions).

87. Color-Coded 4th Variable: Use dot color to represent a fourth, categorical variable (e.g., Pre-test vs. Post-test, colored by Teacher).

88. Temporal Playback: Animate the plot to show how the correlation changes over time (e.g., Week 1 to Week 16).

89. Data Point Hover Details: On hover, show all underlying data for that student/class (Name, ID, all grades, etc.).

90. Regression Equation Display: Clearly show the equation of the line of best fit ($y = mx + b$).

B. Filtering and Customization

91. Filter by Demographic: Instantly filter points by Gender, Ethnicity, Special Needs status, etc.

92. Filter by Grade/Score Range: Only display students within a certain grade range (e.g., A- to B+).

93. Comparison Group Highlighting: Select two sub-groups (e.g., Students who used the app vs. those who didn't) and highlight their points in different colors.

94. Custom X/Y Axis Selection: Allow users to choose any two available data points for comparison.

95. Benchmark Reference Lines: Add vertical/horizontal lines for school/district benchmarks (e.g., $70\%$ passing score).

96. "What-If" Analysis: Allow users to drag a data point to see the predicted change in the dependent variable based on the trendline.

97. Save and Share View: Ability to save the current plot configuration and share a link with a colleague/parent.

98. Custom Data Upload: Allow teachers to upload their own small datasets (e.g., a unique classroom experiment) and visualize it instantly.

99. Density Plot Overlay: Use a heatmap or shading to indicate the density of points where data is heavily clustered (useful for large datasets).

100. Confidence in Mastery vs. Time: Plot the student's own calculated "Confidence in Mastery" (x-axis) against the actual "Time Spent Studying" (y-axis) for a subject.

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Would you like me to elaborate on a specific category, or do you want to explore the features of one of the advanced visualization ideas?