Fuzzy_PISA_Code_Submission_with_Data.zip

This zipped folder contains the source code, sample data, and instructions for reproducing the fuzzy logic-based student success prediction model presented in the manuscript titled “Fuzzy Logic-Based Analysis of PISA 2022 Process Data.”

The code implements the Fuzzy Propositional Model (FPM) and is compatible with Python 3.11. It includes all steps from data preprocessing to membership function definition, rule-based inference, and model evaluation.

Contents:

1. fuzzy_pisa_model.ipynb
   - Jupyter Notebook file with code and markdown explanations
   - Implements membership functions using scikit-fuzzy
   - Provides rule-based scoring function and model evaluation with MAE & RMSE

2. pisa_cleaned_data_sample.csv
   - A sample dataset representing the structure of PISA 2022 process data
   - Includes columns: TT, TFA, NA, NV, NSV, and actual_score

3. requirements.txt
   - Lists Python libraries: pandas, numpy, scikit-fuzzy, scikit-learn, matplotlib

4. README.md
   - Explains how to run the notebook and replicate results
   - Contains installation and execution instructions

This code repository supports open science and is intended for peer review and replication purposes.