Measuring and predicting variation in the difficulty of questions about data visualizations
Fuente:
arXiv
Salvato in:
| Autori principali: | , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866913834199941120 |
|---|---|
| author | Verma, Arnav Fan, Judith E. |
| author_facet | Verma, Arnav Fan, Judith E. |
| contents | Understanding what is communicated by data visualizations is a critical component of scientific literacy in the modern era. However, it remains unclear why some tasks involving data visualizations are more difficult than others. Here we administered a composite test composed of five widely used tests of data visualization literacy to a large sample of U.S. adults (N=503 participants).We found that items in the composite test spanned the full range of possible difficulty levels, and that our estimates of item-level difficulty were highly reliable. However, the type of data visualization shown and the type of task involved only explained a modest amount of variation in performance across items, relative to the reliability of the estimates we obtained. These results highlight the need for finer-grained ways of characterizing these items that predict the reliable variation in difficulty measured in this study, and that generalize to other tests of data visualization understanding. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_08031 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Measuring and predicting variation in the difficulty of questions about data visualizations Verma, Arnav Fan, Judith E. Human-Computer Interaction Understanding what is communicated by data visualizations is a critical component of scientific literacy in the modern era. However, it remains unclear why some tasks involving data visualizations are more difficult than others. Here we administered a composite test composed of five widely used tests of data visualization literacy to a large sample of U.S. adults (N=503 participants).We found that items in the composite test spanned the full range of possible difficulty levels, and that our estimates of item-level difficulty were highly reliable. However, the type of data visualization shown and the type of task involved only explained a modest amount of variation in performance across items, relative to the reliability of the estimates we obtained. These results highlight the need for finer-grained ways of characterizing these items that predict the reliable variation in difficulty measured in this study, and that generalize to other tests of data visualization understanding. |
| title | Measuring and predicting variation in the difficulty of questions about data visualizations |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2505.08031 |