blum_2018_imak_bin
7,291 responses from 317 respondents to 23 items.
About this table
| Description | Binary Correctness Scoring of Analogical Reasoning Items |
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| Reference | Blum D and Holling H (2018) Automatic Generation of Figural Analogies With the IMak Package. Front. Psychol. 9:1286. doi: 10.3389/fpsyg.2018.01286 |
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| DOI | 10.3389/fpsyg.2018.01286 |
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| Licence | CC BY 4.0 |
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| Source data | https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2018.01286/full |
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Size and shape
| Responses | 7,291 |
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| Respondents | 317 |
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| Items | 23 |
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| Response categories | 2 |
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| Responses per respondent | 23 |
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| Responses per item | 317 |
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| Density | 1 |
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| Longitudinal | FALSE |
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Classification
| age range | Mixed |
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| child age (for child-focused studies) | Early (<6y), Adolescent (12-18y) |
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| sample | General/non-specific, Internet-based |
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| construct type | Cognitive/educational |
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| measurement tool | Test |
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| item format | Likert Scale/selected response |
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| primary language(s) | ger, eng, spa |
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| construct name | Binary Correctness Scoring of Analogical Reasoning Items |
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Columns
cov_agecov_countrycov_gendercov_languagecov_secondaryiditemresprt
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("blum_2018_imak_bin")
# Python
pip install irw
import irw
df = irw.fetch("blum_2018_imak_bin")
Version and provenance
| IRW version | v393 |
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| Redivis dataset | item_response_warehouse_2 v19.0 |
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| Redivis dataset DOI | 10.57761/qtx5-4m80 |
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| Manifest pin for this IRW version | v19.0 |
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| Metadata source | irw_meta v23.0 |
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