10,857 responses from 1,551 respondents to 7 items.
| Description | Intrinsic Motivation Inventory |
|---|---|
| Reference | Perrig, S. A. C., Scharowski, N., Brühlmann, F., von Felten, N., & Aeschbach, L. F. (2024, January 24). Independent Validation of the Player Experience Inventory. https://doi.org/10.17605/OSF.IO/8XUHR |
| Licence | CC BY 4.0 |
| Source data | https://osf.io/8xuhr/ |
| Responses | 10,857 |
|---|---|
| Respondents | 1,551 |
| Items | 7 |
| Response categories | 7 |
| Responses per respondent | 7 |
| Responses per item | 1,551 |
| Density | 1 |
| Longitudinal | FALSE |
| age range | Adult (18+) |
|---|---|
| sample | Internet-based |
| construct type | Affective/mental health |
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | eng |
| construct name | Intrinsic Motivation Inventory |
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Intrinsic Motivation Inventory |
|---|---|
| Mean words per item | 9.143 |
| Mean characters per item | 47.286 |
| Mean characters per response | 6.429 |
| Flesch-Kincaid grade level | 4.201 |
iditemresp
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("FIVPEI_Perrig_2023_IMI")
# Python
pip install irw
import irw
df = irw.fetch("FIVPEI_Perrig_2023_IMI")
| IRW version | v393 |
|---|---|
| Redivis dataset | item_response_warehouse v53.0 |
| Redivis dataset DOI | 10.57761/4g08-xt41 |
| Manifest pin for this IRW version | v53.0 |
| Metadata source | irw_meta v23.0 |