Introduction
Welcome to Pearl Data Assistant, your comprehensive tool for educational data analysis. This guide will help you understand and utilize all features effectively.
Key Features
- Student performance analysis
- Grade distribution visualization
- Growth tracking over time
- Equity analysis across demographics
- Item analysis for assessments
- Attendance pattern analysis
Getting Started
System Requirements
- Modern web browser (Chrome, Firefox, Safari, or Edge)
- Internet connection
- CSV or Excel files containing your educational data
Pro Tip: Before starting, ensure your data is clean and properly formatted. This will save time and prevent errors during analysis.
Analysis Types
Student Performance Analysis
Track and analyze individual and group academic performance.
Features:- Test score analysis
- Assignment average calculations
- Performance trend identification
Grade Distribution Analysis
Understand the spread of grades across your class.
Features:- Grade frequency visualization
- Percentile calculations
- Statistical measures
Growth Analysis
Track student progress over time.
Features:- Learning gains measurement
- Progress rate calculations
- Trend identification
Data Requirements
File Formats
The application accepts:
- CSV (Comma Separated Values)
- Excel (.xlsx, .xls)
Sample Data Format
Student_ID,Subject,Score,Date
1001,Math,85,2024-01-15
1002,Math,92,2024-01-15
1003,Math,78,2024-01-15
Important: Ensure your column headers match exactly with the template format. The system is case-sensitive.
Using Templates
Downloading Templates
- Find the analysis type you want to perform
- Click the download icon (↓) next to the analysis card
- Save the template to your computer
Tip: Use the templates as a guide for formatting your own data. The column names and order are important for proper analysis.
Performing Analysis
Step-by-Step Process
- Select your analysis type from the main dashboard
- Upload your prepared data file
- Configure any additional parameters
- Review and interpret the results
Note: Always verify your data has been uploaded correctly before proceeding with analysis.
Interpreting Results
Common Metrics
Performance Metrics
- Mean Score: Average performance
- Median Score: Middle value
- Standard Deviation: Spread of scores
Growth Metrics
- Absolute Growth: Raw score changes
- Relative Growth: Percentage improvements
- Growth Rate: Speed of progress
Troubleshooting
Common Issues
- File Upload Errors: Check file format and size
- Data Format Problems: Verify column headers and data types
- Analysis Errors: Ensure all required fields are filled
Need Help? Contact our support team at support@pearldataassistant.com
Best Practices
Data Preparation
- Clean your data before uploading
- Use consistent naming conventions
- Verify data accuracy
- Remove sensitive information
Analysis Tips
- Start with broad analyses
- Drill down into specific areas of interest
- Compare multiple metrics
- Document your findings