Give both conditions a matched popup message to isolate the effect of disclosing AI fallibility¶

Design · All designs
Evidence · 1 claim (1 for) · 1 study (1 causal), q3 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

When testing transparency cues about AI fallibility, the control condition should receive a comparable popup that omits only the fallibility disclosure. The authors explain that "the distinction focused on whether the warning message mentioned the possibility of hallucination or not, instead of, for example, giving no warning to students in the control condition," so the design isolates the disclosure effect rather than the general effect of any warning popup.

Design Implications¶

Context¶

Requirements¶

A control message matched in format and tone that differs only in mentioning potential mistakes

Constraints¶

This design tests disclosure of fallibility, not the general effect of providing popup warnings

Target Learners¶

secondary school students using AI-based tutoring systems

Learning Goals¶

critical engagement with potentially fallible system output

Claims¶

Ai Fallibility Warning Increases Help Seeking [+M]

Examples¶

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Key Sources¶

Tomohiro Nagashima, Mirella Hladký, and Vera Rief. (2026). Warning About AI Fallibility Increases Help-Seeking in an Intelligent Tutoring System. https://arxiv.org/abs/2606.03822

Page metadata

Field	Value
`type`	`design`
`id`	`matched-popup-message-isolate-fallibility-disclosure`
`title`	`Give both conditions a matched popup message to isolate the effect of disclosing AI fallibility`
`description`	`When testing transparency cues about AI fallibility, the control condition should receive a comparable popup that omits only the fallibility disclosure.`
`status`	`review`
`generated`	by `process:settle-candidates` on `2026-10-10`
`trust`	unverified — no one has confirmed this page's content
`sources`	1 — `tomohiro-nagashima-2026`

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