Which Evaluation Strategies Help Students Spot Visual Misinformation on Social Media?

Background The rapid spread of visual misinformation online, intensified by advances in generative artificial intelligence, presents new challenges for adolescents' digital information literacy. Although students' difficulties in evaluating online information are well documented, little is known about how they assess different forms of visual misinformation on social media. Objectives This study examined the extent to which lower secondary school students can successfully identify different types of visual misinformation on social media, the evaluation strategies they use, and whether these strategies predict misinformation detection across types of visual misinformation. Methods The participants were 272 students in Grades 7–9 who evaluated social media posts containing visual misinformation, including manipulated videos, manipulated images, and AI‐generated images. Students rated each item's credibility and provided written justifications. Evaluation strategies were coded using a theoretically grounded scheme. Results Students were moderately successful in identifying manipulated images and videos, but struggled to detect AI‐generated images, which were often perceived as credible. Students relied primarily on evaluation of visual appearance and content, while source evaluation and corroboration strategies were infrequently used. Across all visual misinformation types, examination of visual features, knowledge‐based evaluation, sourcing, and corroboration strategies predicted misinformation detection. However, corroboration was the only strategy that reliably predicted identification of AI‐generated images. Conclusions Students mostly rely on first‐hand evaluation of visual appearance and content, but these strategies are inadequate for detecting realistic AI‐generated visual misinformation. Instruction should emphasize active verification strategies, particularly corroboration, and support students in coordinating multiple evaluation strategies when engaging with online visual information.