code and data

README.md

-# CodeWhisperer-PROGEN-AI
-

README_PROGEN_AI.md

+# 🧠 PROGEN-AI: Evaluating the Impact of Generative AI in Programming Education
+
+## 🔎 Functionality Summary
+
+This repository contains all materials and code used in an educational experiment evaluating the effectiveness of **Amazon CodeWhisperer** as a generative AI tool to support programming education. The experiment was conducted with students enrolled in the *Programming for Data Science* course of the Master's in Data Science program at Universidad Politécnica de Madrid.
+
+---
+
+## 🔬 1. Educational Experiment Analysis Module
+
+A Jupyter notebook that analyzes students’ performance in solving programming exercises **with and without** the use of generative AI (Amazon CodeWhisperer). The core of the experiment includes:
+
+- 🧪 Solving two tasks:
+  - Task 1: Without any AI assistance
+  - Task 2: With Amazon CodeWhisperer
+
+- 📊 Comparative evaluation on:
+  - Accuracy in programming tasks
+  - Quality of data visualizations
+  - Time spent
+  - Reasoning and analysis quality
+  - Influence of academic background
+
+- 📈 Result visualizations:
+  - Bar plots and distributions
+  - AI-assisted vs. manual coding comparisons
+
+Results are derived from student responses collected via Microsoft Forms and processed in the notebook `Results experiment Code Wihsperer-Copy1.ipynb`.
+
+📂 For a full description of the methodology and findings, see the notebook in the root directory.
+
+---
+
+## 🧬 2. Analysis Dataset: `Sales.csv`
+
+The experiment is based on a real-world dataset of mobile phone sales, including features such as:
+
+- Brand
+- Price
+- Storage capacity
+- Rating
+
+Students used this dataset to solve data filtering, analysis, and visualization tasks in both assignments.
+
+---
+
+## ▶️ How to Run the Experiment Analysis
+
+1. Ensure you have Python 3.8+ and Jupyter Notebook installed.
+2. Clone the repository:
+   ```bash
+   git clone https://gitlab.com/your_user/progen-ai.git
+   cd progen-ai
+   ```
+3. Create the environment with Conda:
+   ```bash
+   conda env create -f environment.yml
+   conda activate progen-ai
+   ```
+4. Launch the notebook:
+   ```bash
+   jupyter notebook
+   ```
+   Then open and run `Results experiment Code Wihsperer-Copy1.ipynb`.
+
+---
+
+## 📁 Project Structure
+
+```
+📦 progen-ai/
+├── data/
+│   └── Sales.csv                     # Mobile phone sales dataset
+├── results/
+│   └── *.csv / *.xlsx                # Form responses and analysis metrics
+├── Results experiment Code Wihsperer-Copy1.ipynb   # Main analysis notebook
+├── environment.yml                   # Conda environment definition
+└── README.md                         # This file
+```
+
+---
+
+## ⚙️ Environment Setup
+
+To install dependencies:
+
+```bash
+conda env create -f environment.yml
+conda activate progen-ai
+```
+
+---
+
+## 👩‍🔬 Authors and Credits
+
+This project was developed within an educational innovation initiative by:
+
+- **Belén Otero-Carrasco**, Laura Melgar-García, Guillermo Vigueras, Belén Ríos  
+  MEDAL · https://medal.ctb.upm.es  
+  CTB · https://ctb.upm.es