7,580 responses from 379 respondents to 20 items.
| Description | SDT-based English learning motivation (after Agawa & Takeuchi 2016): intrinsic motivation, identified regulation, external regulation, amotivation; 20 items; 20 items, 1-5 (strongly disagree-strongly agree); 379 Indian high-school students (Type A, B and C schools; ages 13-19); covariates: cov_gender, cov_age, cov_class, cov_english_self. |
|---|---|
| Reference | Leis, A., & Mundotia, M. (2025). The intrinsic motivation of students studying English in India. Asian Journal of English Language Teaching. https://doi.org/10.65961/ajelt-2025-1-003 |
| DOI | 10.65961/ajelt-2025-1-003 |
| Licence | CC0 1.0 |
| Source data | https://doi.org/10.7910/DVN/25QUO9 |
These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.
| Responses | 7,580 |
|---|---|
| Respondents | 379 |
| Items | 20 |
| Response categories | 5 |
| Responses per respondent | 20 |
| Responses per item | 379 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Mixed |
|---|---|
| child age (for child-focused studies) | Adolescent (12-18y) |
| sample | Educational |
| construct type | Opinion/attitude |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | English learning motivation (self-determination theory regulation types) |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | SDT-based English learning motivation questionnaire (after Agawa & Takeuchi 2016): intrinsic motivation, identified regulation, external regulation, amotivation |
|---|---|
| Mean words per item | 11.400 |
| Mean characters per item | 61.250 |
| Mean characters per response | 7.400 |
| Flesch-Kincaid grade level | 6.556 |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, leis_2025_english_motivation.py. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task). | made in the build script |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_age | Covariate | Age |
cov_class | Covariate | Class |
cov_english_self | Covariate | How good is your English? |
cov_gender | Covariate | Gender |
What item codes and covariate values stand for is in the codebook released with the source data.
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("leis_2025_english_motivation")
# Python
pip install irw
import irw
df = irw.fetch("leis_2025_english_motivation")
@article{LEIS_2025, title={The Intrinsic Motivation of Students Studying English in India}, ISSN={1026-2652}, url={http://dx.doi.org/10.65961/ajelt-2025-1-003}, DOI={10.65961/ajelt-2025-1-003}, journal={Asian Journal of English Language Teaching}, publisher={The Chinese University of Hong Kong Library}, author={LEIS, Adrian}, year={2025}, month=Jan }
| IRW version | v584 |
|---|---|
| Redivis dataset | item_response_warehouse_5 v8.5 |
| Redivis dataset DOI | 10.57761/41xy-5k56 |
| Manifest pin for this IRW version | v8.5 |
| Metadata source | irw_meta v44.0 |