44,999,136 responses from 1,000,000 respondents to 50 items.
The scored version of this table is enem_2023_1mil_lc.
One of 104 tables from the same source; this one measures ENEM Language Proficiency Assessment (2023). The others are listed under Related tables.
| Description | Nominal version of enem_2023_1mil_lc: text is the response option the examinee marked on the language and codes 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 | 44,999,136 |
|---|---|
| Respondents | 1,000,000 |
| Items | 50 |
| 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 Language 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_lc_nom", source = "nom")
# Python
pip install irw
import irw
df = irw.fetch("enem_2023_1mil_lc_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 |