AI-Assisted Infographic Design for Data Storytelling: Effects on Quality, Efficiency, and Creativity in Education

Aim/Purpose: This study investigates whether an AI-assisted infographic generation tool can enhance infographic quality, support creativity, and improve efficiency in educational settings compared to conventional design tools. Background: Infographics are a powerful medium for data storytelling, but require significant design expertise and time, often creating barriers for students. This paper evaluates an AI-based infographic generation tool that automates layout and visual design, examining its effects on output quality, task efficiency, and perceived support for creativity in a university Data Visualization course. Methodology: Two controlled experiments were conducted with undergraduate and postgraduate students enrolled in a Data Visualization module. In each experiment, participants were divided into control (conventional tool) and experimental (AI tool) groups and completed a data storytelling task by creating an infographic. Outputs were evaluated using a structured rubric, while student perceptions were captured through a usability questionnaire and the Creativity Support Index (CSI). Independent samples t-tests and ANOVA were used for analysis. Contribution: This paper contributes empirical evidence to the emerging discourse on AI-assisted creativity in education. It provides a comparative evaluation of AI-generated and template-based infographics across objective quality measures, time efficiency, perceived usability, and support for creativity, highlighting both the benefits and trade-offs of automation in creative learning tasks. Findings: Infographics created using the AI tool achieved substantially higher overall quality scores than those created with the conventional design tool, improving rubric scores by 35% among undergraduates (86.8 vs. 64.5) and 26% among postgraduates (86.9 vs. 69.1). The largest gains were observed in layout, visual elements, and data visualization quality. The AI tool also reduced task completion time by 30% for undergraduates (from 113.5 to 79.1 minutes), and by 38% for postgraduates (from 86.0 to 53.6 minutes). Students in the control groups reported greater perceived usability and a greater sense of control over layout and design decisions. Postgraduate students rated the AI tool more positively for its creativity support than undergraduates did. The results indicate a trade-off between efficiency and user agency when integrating AI into creative design tasks. Recommendations for Practitioners: Educators integrating AI tools into design or visualization courses should balance automation with opportunities for learner control and customization. Providing scaffolding and training may improve perceived usability and support smoother adoption, especially among less experienced students. Recommendation for Researchers: Future research should further explore learner agency, long-term skill development, and the interaction between prior experience and AI tool acceptance. Comparative studies across disciplines and task types can deepen understanding of AI’s role in creative education. Impact on Society: By demonstrating how AI can enhance both efficiency and output quality in visual communication tasks, this study informs the responsible integration of generative tools in education. It highlights the importance of designing AI systems that augment, rather than replace, human creativity and decision-making. Future Research: Future studies should examine the longitudinal effects of AI-assisted design on students’ independent creative skills, investigate adaptive AI systems that allow adjustable levels of automation, and explore collaborative AI-supported infographic design environments.