Exploring the impact of multimodal generative artificial intelligence on CT dispositions in inquiry-based academic writing: a quasi-experimental analysis in higher education

A quasi-experimental study, grounded in the Cognitive Theory of Multimedia Learning, is being conducted in higher education to evaluate the impact of multimodal generative AI on critical thinking (CT) dispositions and academic writing quality. It compares the effectiveness of multimodal GenAI (processing text, images, and visual representations) against text-based GenAI and a control group without GenAI support for undergraduate students engaged in inquiry-based writing.

Why it matters

This research is critical for understanding the pedagogical utility and potential risks of advanced AI tools in educational and professional development contexts. Insights gained will inform strategy regarding the integration of multimodal AI to enhance critical thinking and communication skills, which are vital for innovation and problem-solving across all sectors.

Key insights

• Generative AI presents new opportunities for scaffolding inquiry-based writing.
• The impact of generative AI on critical thinking dispositions is empirically under-explored, particularly concerning interaction modality.
• The study investigates whether multimodal GenAI cultivates CT dispositions and improves academic writing quality more effectively than text-based GenAI or no GenAI support.
• A quasi-experimental pretest-posttest design with three conditions (multimodal GenAI, text-based GenAI, and no GenAI control) is being implemented with 165 undergraduate students.

Source

Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1926173