SayPro Data Analysis

Organize the Data

a. Quantitative Data:

• Test Scores, Grades, and Performance Metrics:
  • Organize academic data (e.g., test scores, grades, assignments) into tables or spreadsheets to track improvements or trends over time.
  • Ensure that you have both pre- and post-curriculum implementation data for comparative analysis.
• Soft Skills Data (Likert Scale Responses):
  • Organize soft skills data based on the Likert scale responses (e.g., 1-5) for both students and instructors. This will allow you to easily quantify and analyze changes in students’ soft skills development.

b. Qualitative Data:

• Open-Ended Responses:
  • Collect and categorize responses into themes. You can use manual coding or qualitative analysis software (e.g., NVivo, ATLAS.ti) to group the feedback into categories such as “teamwork,” “communication,” “problem-solving,” etc.
• Teacher Feedback:
  • Review teacher comments to extract any recurring insights about academic performance or skills development, particularly any areas that need attention or improvement.

2. Quantitative Data Analysis

a. Descriptive Statistics:

• Calculate the mean, median, and standard deviation for academic achievement metrics (e.g., grades, test scores) and soft skills ratings. This will give you a sense of central tendency (average scores) and variability (how much students’ responses differ).
  • Example: Calculate the average test score improvement from pre- to post-curriculum implementation.

b. Comparative Analysis:

• Pre- and Post-Analysis:
  • Paired T-Test or Wilcoxon Signed-Rank Test: If you have paired pre- and post-curriculum data for individual students (i.e., comparing each student’s scores before and after exposure to the SayPro Curriculum), conduct a paired t-test (for normally distributed data) or Wilcoxon signed-rank test (for non-parametric data). This will help assess if there is a statistically significant difference in academic performance.
  • Example: Compare the pre- and post-test scores to see if the SayPro curriculum significantly improved academic performance.
• Soft Skills Growth:
  • Calculate mean changes in soft skills by comparing pre- and post-survey scores on the 1-5 Likert scale for each soft skill (e.g., communication, problem-solving, teamwork).
  • Identify which soft skills show the most significant improvements.
  • Example: Calculate the average increase in “teamwork” skills from pre- to post-curriculum.

c. Correlation Analysis:

• Pearson or Spearman Correlation: Use correlation analysis to explore relationships between different data points. For instance:
  • Correlation between Academic Achievement and Soft Skills Development:
    • Run a Pearson correlation coefficient to explore if there’s a significant relationship between improvements in soft skills (e.g., teamwork, communication) and academic achievement (e.g., grades, test scores).
    • Example: Does improvement in communication skills correlate with higher grades in written assignments?
  • Example Hypothesis: Higher improvements in teamwork lead to better performance on group projects, which could positively influence overall academic grades.

3. Qualitative Data Analysis

a. Thematic Coding:

• Review the open-ended responses from both students and instructors and manually code the data to identify key themes (e.g., “improved problem-solving,” “better communication,” “confidence in exams”).
  • Example Theme: “Problem-solving skills” might be mentioned frequently as a positive outcome of the curriculum. You can then quantify how many responses referenced this theme and how students described their growth.

b. Frequency Analysis:

• Frequency of Mention: Count how often certain themes (e.g., “communication,” “teamwork,” “critical thinking”) appear across all responses. This will help identify the areas where the curriculum has had the most noticeable impact.
  • Example: If 70% of students mention an improvement in “problem-solving” skills, you can conclude that this is an area of significant positive impact from the curriculum.

c. Identify Common Patterns or Quotes:

• Look for recurring patterns or insightful quotes that could highlight important aspects of the curriculum’s effectiveness. This could include specific examples of how students applied their skills in real-world settings or challenges that need further attention.
  • Example: A student might say, “I used the critical thinking skills I learned in the SayPro curriculum to solve a real-world problem in my internship,” which could indicate the practical application of academic learning.

4. Identifying Trends and Key Insights

a. Trends in Academic Achievement:

• Look for Overall Improvements: Do students show consistent improvement in test scores and grades over time? If so, this could suggest that the SayPro Curriculum is effective in boosting academic performance.
  • Example Insight: If the majority of students demonstrate an improvement in test scores by 10%, it could suggest the curriculum’s positive effect on academic performance.
• Differential Impact by Subject: Are there particular subjects or areas of the curriculum that show stronger growth? For example, improvements in math might be more significant than in language arts.
  • Example Insight: “Students in math showed a 15% improvement in test scores compared to a 7% improvement in English, suggesting that the SayPro curriculum is more effective in STEM areas.”

b. Trends in Soft Skills Development:

• Look for Improvements in Specific Skills: Which soft skills showed the most improvement? Are there particular skills (like communication or teamwork) that have shown measurable growth over the survey period?
  • Example Insight: “The average student score for teamwork increased by 0.8 points on a 5-point scale, indicating significant growth in collaborative skills.”
• Impact on Real-World Applications: Look for feedback indicating that students are transferring these skills into real-life settings. This could include feedback from both students and teachers.
  • Example Insight: “Several students mentioned using problem-solving skills during internships or volunteer work, indicating the curriculum’s positive real-world impact.”

c. Areas for Improvement:

• Identify areas where students or instructors feel the curriculum could be strengthened. If certain skills show limited growth, the curriculum might need adjustments.
  • Example Insight: “Despite improvements in teamwork and communication, students reported struggling with time management, suggesting that additional resources or strategies could be added to address this gap.”

5. Reporting and Visualization

• Create Visualizations: Use charts, graphs, and tables to represent the data visually. Bar charts for soft skills development, line graphs for academic achievement over time, and scatter plots for correlations can make the data easier to digest.
• Comprehensive Report: Summarize key findings in a clear, structured report:
  • Executive Summary: Provide an overview of major findings and insights.
  • Quantitative Findings: Present statistical analysis of academic performance and soft skills development.
  • Qualitative Insights: Include significant themes and quotes from student and instructor feedback.
  • Recommendations: Offer actionable suggestions for improving the curriculum based on the analysis.