Item Response Warehouse / Tables / cooper_2018_offensive_topicscooper_2018_offensive_topics
55,658 responses from 1,637 respondents to 34 items.
About this table
Description 34-item binary (0/1) checklist of topics students found offensive, from a survey on gender differences in perceptions of instructor humor Reference Cooper KM, Hendrix T, Stephens MD, et al. (2018) To be funny or not to be funny: Gender differences in student perceptions of instructor humor in college science courses. PLoS ONE. DOI 10.1371/journal.pone.0201258 Licence CC BY 4.0 Source data https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0201258.s005
Size and shape
Responses 55,658 Respondents 1,637 Items 34 Response categories 2 Responses per respondent 34 Responses per item 1,637 Density 1 Longitudinal FALSE
Classification
sample Educational measurement tool Survey/questionnaire item format Likert Scale/selected response primary language(s) eng
Item text
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
Instrument Humor survey: offensive joke subjects checklist Mean words per item 3.412 Mean characters per item 21.529 Mean characters per response 10 Flesch-Kincaid grade level 95.540
Get the data
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("cooper_2018_offensive_topics")
# Python
pip install irw
import irw
df = irw.fetch("cooper_2018_offensive_topics")
Version and provenance
IRW version v393 Redivis dataset item_response_warehouse_3 v7.0 Redivis dataset DOI 10.57761/pqqn-pm43 Manifest pin for this IRW version v7.0 Metadata source irw_meta v23.0
Part of the Item Response Warehouse , IRW v393. This page describes the table as released in item_response_warehouse_3 v7.0.