Just Seeing Can Be Deceiving: GenAI-Supported Design Case for Critical Visual Literacy

Generative AI (GenAI) poses a pedagogical challenge to data visualization education by enabling the rapid creation of persuasive, misleading visuals. This design case presents a three-phase learning experience designed for a graduate course to foster critical AI-visual literacy. The design inverts the typical use of AI by tasking students with using GenAI as a ‘cognitive partner’ to intentionally create a misleading version of their own honest data visualization. The activity guides students through establishing an ethical baseline, creating the misleading visual, and engaging in peer critique, supported by scaffolds like a prompting guide and reflection templates. Analysis of student work shows the design effectively fostered critical AI literacy.

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Publication Details

Journal
International Journal of Designs for Learning
Published
2025-12-11
DOI
https://doi.org/10.14434/ijdl.v16i2.41987
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

Just Seeing Can Be Deceiving: GenAI-Supported Design Case for Critical Visual Literacy

Jihyun Rho, Jihyun Yu
International Journal of Designs for Learning
Data Visualization and Analytics
article

Just Seeing Can Be Deceiving: GenAI-Supported Design Case for Critical Visual Literacy

Jihyun Rho, Jihyun Yu
article en

Abstract

Generative AI (GenAI) poses a pedagogical challenge to data visualization education by enabling the rapid creation of persuasive, misleading visuals. This design case presents a three-phase learning experience designed for a graduate course to foster critical AI-visual literacy. The design inverts the typical use of AI by tasking students with using GenAI as a ‘cognitive partner’ to intentionally create a misleading version of their own honest data visualization. The activity guides students through establishing an ethical baseline, creating the misleading visual, and engaging in peer critique, supported by scaffolds like a prompting guide and reflection templates. Analysis of student work shows the design effectively fostered critical AI literacy.

International Journal of Designs for LearningVol. 16(2)
University of North Texas (US), University of Florida (US)
Openalex Percentile: Top 57%
Data Visualization and Analytics
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