enem_2024_1mil_cn_nom

43,995,909 responses from 999,917 respondents to 44 items.

The scored version of this table is enem_2024_1mil_cn.

One of 104 tables from the same source; this one measures ENEM Natural Sciences Proficiency Assessment (2024). The others are listed under Related tables.

About this table

DescriptionNominal version of enem_2024_1mil_cn: text is the response option the examinee marked on the natural sciences portion of the 2024 Brazilian ENEM. resp is retained as the scored 0/1.
ReferenceMartins, D. M. (2021). Estado da arte das pesquisas sobre ENEM no Brasil: State of the art of research on ENEM in Brazil. Latin American Journal of Development, 3(5), 2898-2907.
DOI10.46814/lajdv3n5-018
LicenceCC BY 4.0
Source datahttps://www.gov.br/inep/pt-br/acesso-a-informacao/dados-abertos/microdados/enem

Notes

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Responses43,995,909
Respondents999,917
Items44
Response categories7
Responses per respondent44.000

Classification

age rangeChild (<18y)
child age (for child-focused studies)Adolescent (12-18y)
sampleRepresentative
construct typeCognitive/educational
measurement toolTest
item formatLikert Scale/selected response
primary language(s)por
construct nameENEM Natural Sciences Proficiency Assessment (2024)

Columns

bookletiditempositionresptext

id, item, resp are defined in the IRW data standard and mean the same in every table. For the other columns, including what item codes and covariate values stand for, see the source’s codebook, DicionĂ¡rio_Microdados_Enem_2024.xlsx (inside microdados_enem_2024.zip, 526 MB).

Get the data

Browse on Redivissign in to download

This table is larger than Redivis serves without a login, so download it with one of the packages below or while signed in to Redivis.

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("enem_2024_1mil_cn_nom", source = "nom")
# Python
pip install irw

import irw
df = irw.fetch("enem_2024_1mil_cn_nom", source="nom")

How to cite

@article{Martins_2021, title={Estado da arte das pesquisas sobre ENEM no Brasil: State of the art of research on ENEM in Brazil}, volume={3}, ISSN={2674-9297}, url={http://dx.doi.org/10.46814/lajdv3n5-018}, DOI={10.46814/lajdv3n5-018}, number={5}, journal={Latin American Journal of Development}, publisher={South Florida Publishing LLC}, author={Martins, Dayse Marinho}, year={2021}, month=Sept, pages={2898–2907} }

Version and provenance

IRW versionv569
Redivis datasetirw_nominal v4.1
Redivis dataset DOI10.57761/9hzd-dc70
Manifest pin for this IRW versionv4.1
Metadata sourceirw_meta v43.0