Interactive learning meets AI: elevating student experiences in fashion and culture education

Abstract

This study investigates the integration of artificial intelligence (AI) with interactive learning pedagogies to enhance student experiences in fashion and culture education. By incorporating AI-driven tools and interactive methods, a dynamic learning environment was developed that promotes engagement, peer communication, and a deeper understanding of the subject matter. The study employed a mixed-method approach, combining a one-group pretest-posttest quasi-experiment and qualitative interviews to gather feedback on learning habits and experiences from two cohorts of students participating in an AI-integrated fashion and culture course within the general education curriculum at a university. The pretest-posttest survey assessed student participants’ perspectives on AI literacy and their use of AI in learning using a 5-point Likert scale. The students were not provided with specific details of how AI would be used in the course to avoid biasing their responses. The posttest survey was conducted after the integration. Data were analysed to assess the enhancement of students’ AI literacy and understanding and use of AI in the course. From the survey results, it shows that students have a clearer understanding of the technology, enhanced AI literacy, and how it could support their learning. A text-to-image generation tool was used in the course to support storytelling and idea exchange of cultural context from students’ perspectives. Qualitative interviews were conducted after the integration to collect insights from students on how they experienced AI technology integration in the course, the interaction in class, and their feedback. The findings reveal that AI-integrated interactive learning not only fosters deeper engagement but also encourages unique insights into the historical, cultural, and creative dimensions of fashion among students. Students highlighted the benefits of interaction with instructors and peers, as well as real-time feedback facilitated by AI technologies. Despite the promising outcomes, the study acknowledges challenges such as the need for adequate training and the importance of addressing ethical considerations and transparency related to AI use in education. Students were asked to provide proper citation with the use of AI tools together with their prompts to ensure acknowledgment and academic honesty. Additionally, the study shares pedagogical strategies combining passive lectures, discussion sessions, peer interaction, student-centered idea exchange forums, and interactive gamification, which aim to provide a more enjoyable experience and fulfil students’ needs for autonomy and belonging, providing insights into best practices for integrating AI in fashion and culture education. In conclusion, this study demonstrates the potential of AI-powered interactive learning to transform educational experiences and outcomes in the fashion education field. By prioritizing student-centric approaches and the use of AI, educators can create enriching learning environments that prepare students for the complexities of the modern world. Future research should continue to explore the long-term impacts of AI-driven interactive learning and develop strategies to overcome existing challenges and enhance adaptability to technological advancements, ensuring that all students can benefit from these innovative educational practices across disciplines.