722 rated or chosen profiles from 140 respondents, in up to 12 tasks of 1 profile varying on 5 attributes.
| Description | Dutch secondary-school teachers (n = 140, convenience sample, 2025) each evaluated up to 6 of 32 hypothetical-student vignettes (full 2^5 factorial: gender, SES, ethnicity, work effort, class type), giving a transfer recommendation (lowest/highest track) and a 1-5 expectation of graduating at the highest track. |
|---|---|
| Reference | Drent, N., Timmermans, A. C., & Strijbos, J. W. (2026). Dataset: Beyond achievement: A vignette experiment on how intersecting student characteristics shape teachers' expectations and recommendations [Data set]. DANS Data Station Social Sciences and Humanities. |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.17026/SS/KGD30Q |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Respondents | 140 |
|---|---|
| Rows (one per respondent, task and profile) | 722 |
| Tasks per respondent (most) | 12 |
| Profiles per task | 1 |
| Attributes | 5 |
| Topic | other |
|---|---|
| A profile represents | person |
| Country | NL |
| Language shown | nl |
| Language of stored levels | en |
| Task order | inferred from row order |
| Profile position | recorded in the deposit |
Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.
Outcomes:
| rating_expectation | How likely do you think it is that this student will graduate from the highest attainble track? (translated) [rating, 1 (Unlikely) to 5 (Highly likely)] |
|---|---|
| rating_recommendation | Transfer recommendation (paraphrase) [rating, 0 (Lowest track) to 1 (Highest track)] |
attr_class_typeattr_ethnicityattr_genderattr_sesattr_work_effortcov_progressidprofilerating_expectationrating_recommendationtask
The layout (one row per respondent, task and profile; choice/rating outcomes; attr_ columns holding each attribute level as displayed) is defined in the IRW conjoint standard. What the outcomes asked is under Design above.
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("drent_2026_teacher_expectations", source = "conj")
# Python
pip install irw
import irw
df = irw.fetch("drent_2026_teacher_expectations", source="conj")
@misc{https://doi.org/10.17026/ss/kgd30q,
doi = {10.17026/SS/KGD30Q},
url = {https://ssh.datastations.nl/citation?persistentId=doi:10.17026/SS/KGD30Q},
author = {Drent, N. and Timmermans, A. C. and Strijbos, J.},
keywords = {Social Sciences, Teacher expectations, Transfer recommendations, Vignette experiment, Intersectionality, Secondary education, Socioeconomic status, Ethnic background, Gender, Work effort},
title = {Dataset: Beyond Achievement: A Vignette Experiment on How Intersecting Student Characteristics Shape Teachers' Expectations and Recommendations},
publisher = {DANS Data Station Social Sciences and Humanities},
year = {2026}
}
| IRW version | v584 |
|---|---|
| Redivis dataset | irw_conjoint v4.2 |
| Redivis dataset DOI | 10.57761/qkye-q530 |
| Manifest pin for this IRW version | v4.2 |
| Metadata source | irw_meta v44.0 |