Our World
in Data
Oxford Martin School logoUniversity of Oxford logoGlobal Change Data Lab logo
Data

Average academic performance of 15-year-olds

by subject and gender
See all data and research on:
Global Education
Configure the data
Average academic performance of 15-year-olds

Interactive visualization requires JavaScript.

What you should know about this indicator

  • The Programme for International Student Assessment (PISA) is an international survey that assesses the skills and knowledge of 15-year-old students. It provides a snapshot of how well education systems around the world are preparing young people for adult life.
  • PISA is run every three years and tests students in reading, mathematics, and science. It doesn't just assess what students know — it focuses on how well they can use this knowledge to solve problems they might encounter in the real world. For example, can they interpret a bus timetable, reason through a scientific scenario, or compare prices to make a budget?
  • Each student sits a two-hour computer-based test. Results are summarised as average scores for each country, and are designed to be comparable over time.
  • The scores are standardized to make comparisons easier: across OECD countries, the average score was set to 500 in the first year each subject was assessed (reading in 2000, mathematics in 2003, science in 2006). Most countries score somewhere between 300 and 600, although scores outside this range are possible.
  • Higher scores indicate better performance — but comparing countries should be done carefully. Many factors affect student performance, including income, teacher quality, classroom time, and parental education. Cultural differences can also play a role in how students approach the test.
  • PISA gives policymakers, researchers, and educators a way to evaluate their education systems and learn from others. But as with all such comparisons, it's important to consider the wider context behind the numbers.

How is this data described by its producer?

Average score of 15-year-old students on the PISA mathematics scale. Initially, the average PISA score across subjects and all OECD countries was at 500 with a standard deviation of 100, so that most students scored between 400 and 600. Scores in later cycles were calibrated to remain comparable to this baseline.

Average performance of 15-year-old students in mathematics
Assessed through the PISA mathematics scale, which measures how well someone can use math to solve everyday problems and understand the role of math in the real world.
Source
OECD (2023) – with minor processing by Our World in Data
Last updated
December 6, 2023
Next expected update
May 2026
Date range
2003–2022
Unit
score

Related research and writing

A dark blue background with a lighter blue world map superimposed over it. Yellow text that says Economic Inequality by Gender by Our World in Data

Economic Inequality by Gender

Esteban Ortiz-Ospina, Joe Hasell, and Max Roser

Sources and processing

This data is based on the following sources

OECD – PISA Database

The Programme for International Student Assessment (PISA) by OECD provides a comprehensive and rigorous international assessment of the knowledge and skills of 15-year-old students around the world. The assessment covers areas such as mathematics, science, and reading. PISA aims to provide comparable data that will enable countries to improve their education policies and outcomes. Data is collected every three years from a globally diverse cohort of students.

The dataset contains scores, demographic information, and various indicators related to education systems of participating countries.

Retrieved on
December 6, 2023
Retrieved from
https://www.oecd.org/pisa/data/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
OECD Programme for International Student Assessment (PISA) (2023), https://www.oecd.org/pisa/data/, accessed on 6th December 2023.

The Programme for International Student Assessment (PISA) by OECD provides a comprehensive and rigorous international assessment of the knowledge and skills of 15-year-old students around the world. The assessment covers areas such as mathematics, science, and reading. PISA aims to provide comparable data that will enable countries to improve their education policies and outcomes. Data is collected every three years from a globally diverse cohort of students.

The dataset contains scores, demographic information, and various indicators related to education systems of participating countries.

Retrieved on
December 6, 2023
Retrieved from
https://www.oecd.org/pisa/data/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
OECD Programme for International Student Assessment (PISA) (2023), https://www.oecd.org/pisa/data/, accessed on 6th December 2023.

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Average performance of 15-year-old students in mathematics”, part of the following publication: Hannah Ritchie, Veronika Samborska, Esteban Ortiz-Ospina, and Max Roser (2023) - “Global Education”. Data adapted from OECD. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/academic-performance.html [online resource] (archived on March 4, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

OECD (2023) – with minor processing by Our World in Data

Full citation

OECD (2023) – with minor processing by Our World in Data. “Average performance of 15-year-old students in mathematics” [dataset]. OECD, “PISA Database” [original data]. Retrieved April 9, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/academic-performance.html (archived on March 4, 2026).

Download

Quick download

Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

Download full data

Includes all entities and time points

Download displayed data

Includes only the entities and time points currently visible in the chart

Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/academic-performance.csv?v=1&csvType=full&useColumnShortNames=false&sex=both&subject=mathematics
Metadata URL (JSON format)
https://ourworldindata.org/grapher/academic-performance.metadata.json?v=1&csvType=full&useColumnShortNames=false&sex=both&subject=mathematics

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/academic-performance.csv?v=1&csvType=full&useColumnShortNames=false&sex=both&subject=mathematics")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/academic-performance.csv?v=1&csvType=full&useColumnShortNames=false&sex=both&subject=mathematics", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/academic-performance.metadata.json?v=1&csvType=full&useColumnShortNames=false&sex=both&subject=mathematics").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/academic-performance.csv?v=1&csvType=full&useColumnShortNames=false&sex=both&subject=mathematics")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/academic-performance.metadata.json?v=1&csvType=full&useColumnShortNames=false&sex=both&subject=mathematics")
Stata
import delimited "https://ourworldindata.org/grapher/academic-performance.csv?v=1&csvType=full&useColumnShortNames=false&sex=both&subject=mathematics", encoding("utf-8") clear