44,986,496 responses from 999,722 respondents to 45 items.
The scored version of this table is enem_2023_1mil_cn.
One of 104 tables from the same source; this one measures ENEM Natural Sciences Proficiency Assessment (2023). The others are listed under Related tables.
| Description | Nominal version of enem_2023_1mil_cn: text is the response option the examinee marked on the natural sciences portion of the 2023 Brazilian ENEM. resp is retained as the scored 0/1. |
|---|---|
| Reference | Martins, 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. |
| DOI | 10.46814/lajdv3n5-018 |
| Licence | CC BY 4.0 |
| Source data | https://www.gov.br/inep/pt-br/acesso-a-informacao/dados-abertos/microdados/enem |
| Responses | 44,986,496 |
|---|---|
| Respondents | 999,722 |
| Items | 45 |
| Response categories | 7 |
| Responses per respondent | 44.999 |
| age range | Child (<18y) |
|---|---|
| child age (for child-focused studies) | Adolescent (12-18y) |
| sample | Representative |
| construct type | Cognitive/educational |
| measurement tool | Test |
| item format | Likert Scale/selected response |
| primary language(s) | por |
| construct name | ENEM Natural Sciences Proficiency Assessment (2023) |
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, Dicionário_Microdados_Enem_2023.xlsx (inside microdados_enem_2023.zip, 550 MB).
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_2023_1mil_cn_nom", source = "nom")
# Python
pip install irw
import irw
df = irw.fetch("enem_2023_1mil_cn_nom", source="nom")
@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} }
| IRW version | v566 |
|---|---|
| Redivis dataset | irw_nominal v4.1 |
| Redivis dataset DOI | 10.57761/9hzd-dc70 |
| Manifest pin for this IRW version | v4.1 |
| Metadata source | irw_meta v43.0 |