tan_2026_stem_technology_integration
1,200 responses from 80 respondents to 15 items.
About this table
| Description | Science teachers' beliefs, attitudes and practices on technology integration in STEM (80 teachers, 15 items, 5-point Likert) |
|---|
| Licence | CC BY 4.0 |
|---|
| Source data | https://figshare.com/articles/dataset/32024295 |
|---|
Size and shape
| Responses | 1,200 |
|---|
| Respondents | 80 |
|---|
| Items | 15 |
|---|
| Response categories | 5 |
|---|
| Responses per respondent | 15 |
|---|
| Responses per item | 80 |
|---|
| Density | 1 |
|---|
| Longitudinal | FALSE |
|---|
Classification
| sample | Workplace |
|---|
| measurement tool | Survey/questionnaire |
|---|
| item format | Likert Scale/selected response |
|---|
Item text
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Science Teacher’s Belief, Attitude, and Practice of Technology Integration in STEM Education |
|---|
| Mean words per item | 12.267 |
|---|
| Mean characters per item | 73.867 |
|---|
| Mean characters per response | 2 |
|---|
| Flesch-Kincaid grade level | 10.205 |
|---|
Columns
cov_agecov_degreecov_gendercov_subjectiditemresp
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("tan_2026_stem_technology_integration")
# Python
pip install irw
import irw
df = irw.fetch("tan_2026_stem_technology_integration")
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 |
|---|