Document detail
ID

oai:arXiv.org:2403.07613

Topic
Computer Science - Human-Computer ... Computer Science - Multimedia
Author
Silva, Anita Tracy, Maria Reinecke, Katharina Adar, Eytan Redi, Miriam
Category

Computer Science

Year

2024

listing date

3/20/2024

Keywords
gujia wikipedia images
Metrics

Abstract

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

Document

Open

Share

Source

Articles recommended by ES/IODE AI