Student Program Dataset Generator | EvalCommunity

Student Program Dataset Generator

Access the practice dataset for the EvalCommunity AI Project Exercise

Generate and download the simulated student dataset to practice AI analysis with ChatGPT

About This Dataset

This tool provides the student_program_data.csv file referenced in the EvalCommunity "Set Up Your First AI Project" practical exercise. The dataset contains simulated data for 500 students, designed specifically for learning AI analysis in education programs.

Use this dataset to practice predicting student dropout risk using ChatGPT's Advanced Data Analysis feature, as outlined in the lesson.

Dataset Details

The student_program_data.csv contains:

500 Student Records

Simulated data representing a diverse student population for realistic analysis practice.

8 Predictive Variables

Age, Gender, Prior Education, Attendance Rate, Test Scores, Family Income, Distance to School, and Parent Engagement.

Outcome Variable

"Completed Program" column (Yes/No) indicating whether each student successfully finished the program.

Note: This is simulated data for training purposes only. In real practice, you should use your own program's anonymized data.

Generate Your Dataset

Download student_program_data.csv

Click the button below to generate and download the complete dataset in CSV format, ready for use with ChatGPT or any data analysis tool.

How to Use This Dataset with ChatGPT

Step 1: Download the Dataset

Use the download button above to get the student_program_data.csv file. The dataset will be saved to your computer.

Step 2: Access ChatGPT Advanced Data Analysis

Go to chat.openai.com and ensure you have a ChatGPT Plus account with "Advanced Data Analysis" enabled in your settings.

Step 3: Upload and Analyze

Start a new chat, click the paperclip icon (📎), and upload the CSV file. Then ask ChatGPT to analyze the data for dropout patterns.

Example ChatGPT Prompt

Try this prompt after uploading your dataset:

User:

I've uploaded a dataset of 500 students in an education program. The dataset includes demographic information, academic metrics, and whether they completed the program. Can you analyze which factors are most strongly associated with program completion? Specifically, I'd like to know which students are at risk of dropping out based on these variables.

ChatGPT Response:

I'll analyze the student_program_data.csv file. Based on initial examination, I can see the dataset includes Age, Gender, Prior Education, Attendance Rate, Test Scores, Family Income, Distance to School, Parent Engagement, and Completed Program status. I'll perform statistical analysis to identify correlations and build a predictive model for dropout risk...

Dataset Variables Explained

Variable	Description	Example Values	Importance for Analysis
Age	Student's age in years	16-25	Younger students may have different risk factors
Gender	Student's gender	Male, Female, Other	Identify any gender-based disparities
Prior Education	Highest education level before program	High School, Some College, Bachelor's	Baseline academic preparation
Attendance Rate	Percentage of classes attended	65%-100%	Strong predictor of engagement and success
Test Scores	Average score on program assessments	50-100	Academic performance indicator
Family Income	Annual household income bracket	Low, Medium, High	Socioeconomic factors affecting retention
Distance to School	Commute distance in kilometers	0.5-50 km	Logistical barrier to participation
Parent Engagement	Level of parental involvement	Low, Medium, High	Support system influence
Completed Program	Whether student finished the program	Yes, No	Target variable for prediction

Additional Resources

EvalCommunity Courses

Explore our full curriculum on AI for education program evaluation and monitoring.

Data Preparation Guide

Learn how to prepare your own program data for AI analysis.

AI Tools for Education

Discover other AI applications for educational program management.