Jupyter notebook presenting the process of data preparation, research question formulation, data analysis, and data modeling with the goal of extracting insights from the 2018 PISA Dataset

This data analysis project is done on PISA 2018 data on Thai students' education achievement.

Analysis of the year-2018 PISA survey data in Indonesia

Investigated the 2015 and 2018 UK PISA data to assess student performance trends across the four UK nations. Conducted a comparative analysis with Estonia to identify potential educational strategies for improvement.

The dataset used for my model is the PISA 2018 assessment – the seventh since the programme’s inception, which comprises the average score in the three domains PISA 2018 assessed: reading, mathematical, and scientific literacy

PISA 2018 Analysis is my individual project during my study at Hyper Island.

An Exploratory analysis for the Israel PISA exam of 2018 & Prediction model for the Reading score of a student

Analysis of PISA score changes between 2018-2022, examining trends in mathematics, reading, and science performance across participating countries

No description available

-IRT analysis on PISA 2018 & 2022 databases

Exploratory Data Analysis of the 2018 PISA School Survey

This project involved an in-depth analysis of the Programme for International Student Assessment (PISA) 2018 dataset to evaluate global educational outcomes, with a specific focus on Greece.

Analysis of gender-based educational outcomes using OECD PISA 2018 school survey data (.sav). Data preprocessing, analysis, and classification implemented in Python.

Assessing the Impact of COVID-19 on Student Reading Performance: A Difference-in-Differences Analysis Using PISA 2018 and 2022 Data

Survey Data Analysis: Why these students are those who have a low performance in PISA reading test 2018 : A Latent Class Analysis of low-performance Typology

A cross-national comparative analysis of school bullying trends using PISA 2018 and 2022 datasets across 80 countries, focusing on post-pandemic patterns.

Raw analysis files and scripts for the study on first‑level digital divide indicators and reading achievement among U.S. 15‑year‑olds using PISA 2018 data.

This repository contains the material relative to the work presented in "Stratified Multilevel Graphical Models: Examining Gender Dynamics in Education". In particular, the following files are stored: the original OECD-PISA dataset 2018 for Italy, the pre-processing R script and the final dataset used in the analysis (data_gen.csv)