Détail du document
Identifiant
oai:arXiv.org:2403.07613
Sujet
Computer Science - Human-Computer ... Computer Science - MultimediaAuteur
Silva, Anita Tracy, Maria Reinecke, Katharina Adar, Eytan Redi, MiriamCatégorie
Computer Science
Année
2024
Date de référencement
20/03/2024
Mots clés
gujia wikipedia imagesRésumé
Though images are ubiquitous across Wikipedia, it is not obvious that the image choices optimally support learning.
When well selected, images can enhance learning by dual coding, complementing, or supporting articles.
When chosen poorly, images can mislead, distract, and confuse.
We developed a large dataset containing 470 questions & answers to 94 Wikipedia articles with images on a wide range of topics.
Through an online experiment (n=704), we determined whether the images displayed alongside the text of the article are effective in helping readers understand and learn.
For certain tasks, such as learning to identify targets visually (e.g., "which of these pictures is a gujia?")
, article images significantly improve accuracy.
Images did not significantly improve general knowledge questions (e.g., "where are gujia from?")
.
Most interestingly, only some images helped with visual knowledge questions (e.g., "what shape is a gujia?")
.
Using our findings, we reflect on the implications for editors and tools to support image selection.
;Comment: 16 pages, 10 figures
Silva, Anita,Tracy, Maria,Reinecke, Katharina,Adar, Eytan,Redi, Miriam, 2024, Imagine a dragon made of seaweed: How images enhance learning in Wikipedia
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