دورية أكاديمية

Enhancing Data Literacy On-demand: LLMs as Guides for Novices in Chart Interpretation.

التفاصيل البيبلوغرافية
العنوان: Enhancing Data Literacy On-demand: LLMs as Guides for Novices in Chart Interpretation.
المؤلفون: Choe K, Lee C, Lee S, Song J, Cho A, Kim NW, Seo J
المصدر: IEEE transactions on visualization and computer graphics [IEEE Trans Vis Comput Graph] 2024 Jun 12; Vol. PP. Date of Electronic Publication: 2024 Jun 12.
Publication Model: Ahead of Print
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: IEEE Computer Society Country of Publication: United States NLM ID: 9891704 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1941-0506 (Electronic) Linking ISSN: 10772626 NLM ISO Abbreviation: IEEE Trans Vis Comput Graph Subsets: MEDLINE
أسماء مطبوعة: Original Publication: New York, NY : IEEE Computer Society, c1995-
مستخلص: With the growing complexity and volume of data, visualizations have become more intricate, often requiring advanced techniques to convey insights. These complex charts are prevalent in everyday life, and individuals who lack knowledge in data visualization may find them challenging to understand. This paper investigates using Large Language Models (LLMs) to help users with low data literacy understand complex visualizations. While previous studies focus on text interactions with users, we noticed that visual cues are also critical for interpreting charts. We introduce an LLM application that supports both text and visual interaction for guiding chart interpretation. Our study with 26 participants revealed that the in-situ support effectively assisted users in interpreting charts and enhanced learning by addressing specific chart-related questions and encouraging further exploration. Visual communication allowed participants to convey their interests straightforwardly, eliminating the need for textual descriptions. However, the LLM assistance led users to engage less with the system, resulting in fewer insights from the visualizations. This suggests that users, particularly those with lower data literacy and motivation, may have over-relied on the LLM agent. We discuss opportunities for deploying LLMs to enhance visualization literacy while emphasizing the need for a balanced approach.
تواريخ الأحداث: Date Created: 20240612 Latest Revision: 20240625
رمز التحديث: 20240626
DOI: 10.1109/TVCG.2024.3413195
PMID: 38865224
قاعدة البيانات: MEDLINE
الوصف
تدمد:1941-0506
DOI:10.1109/TVCG.2024.3413195