Item Response Warehouse / Tables / hua_2023_efl_course_experiencehua_2023_efl_course_experience
15,072 responses from 942 respondents to 16 items.
About this table
Description 16-item course-experience scale (1-5 Likert), same Chinese university EFL sample as hua_2023_efl_academic_self_concept, n=942 Reference Hua Y, et al (2023). The relationship between Chinese university students' learning preparation and learning achievement within the EFL blended teaching context in COVID-19 post-epidemic era: The mediating effect of learning methods. PLOS ONE. DOI 10.1371/journal.pone.0280919 Licence CC BY 4.0 Source data https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0280919
Size and shape
Responses 15,072 Respondents 942 Items 16 Response categories 5 Responses per respondent 16 Responses per item 942 Density 1 Longitudinal FALSE
Classification
sample Educational measurement tool Survey/questionnaire item format Likert Scale/selected response primary language(s) chi
Item text
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
Instrument EFL Course Experience Questionnaire (EFL-CEQ), adapted from the Course Experience Questionnaire (CEQ) Mean words per item 11.312 Mean characters per item 68.812 Mean characters per response 3.800 Flesch-Kincaid grade level 7.908
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("hua_2023_efl_course_experience")
# Python
pip install irw
import irw
df = irw.fetch("hua_2023_efl_course_experience")
Version and provenance
IRW version v393 Redivis dataset item_response_warehouse_4 v7.0 Redivis dataset DOI 10.57761/cpj5-vm97 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_4 v7.0.