ArticleJournal of microbiology & biology education2026
Bad AI-generated images can be good for teaching visual literacy in biology.
Article in Journal of microbiology & biology education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Practical and positive uses of AI in STEM education: taming the AI tiger.Journal of microbiology & biology education · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has rapidly improved in its ability to produce polished and realistic visual representations of biological structures and processes, yet most AI-generated images still contain factual inaccuracies, inconsistencies, or errors. These types of errors that often make AI images "bad" representations of biology can make AI images powerful pedagogical tools for teaching visual literacy. As biology education relies on diagrams to model structures, processes, and systems that cannot be directly observed, students need to develop skills interpreting, evaluating, and critiquing the visual representations of the unobservable phenomena they encounter in their biology courses. The error-prone and uncanny qualities of AI-generated images can provide rich opportunities for active learning in which students identify inaccuracies, articulate why AI images are incorrect, and refine their understanding of the visual conventions in biology diagrams. The flaws and inaccuracies that make AI-generated biology diagrams "bad" can make them quite good for fostering critical thinking and deep conceptual understanding in biology learners. This perspective outlines practical strategies for incorporating AI images into active learning and assessments in biology courses and offers guidance for generating AI images to use as teaching tools.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.