Research and Practice on Artificial Intelligence-Assisted Teaching Models in Interior Design Education That Integrate Hand-drawn Design Techniques

Abstract

As digital design trends continue to advance, hand-drawing instruction in interior design faces numerous challenges, including insufficient creativity stimulation, suboptimal skill development, and inadequate personalized guidance—factors that significantly diminish the effectiveness of traditional teaching methods. Artificial intelligence assistance, leveraging its strengths in rapid rendering, style transformation, and intelligent feedback, brings new momentum to hand-drawing education and holds promise for reshaping students' learning patterns. This paper presents an in-depth study of a three-stage integrated teaching model: foundational training, stylistic integration, and practical project application. By analyzing the diversity of creative expression in students’ hand-drawn works and incorporating student feedback, the research demonstrates that this approach significantly enhances students’ drawing proficiency and creative output while optimizing resource allocation. The seamless integration of AI and hand-drawing effectively overcomes long-standing limitations of conventional teaching, paving innovative pathways for cultivating interior design talent. Nevertheless, further work is needed to explore the adaptability of AI tools and to establish more comprehensive mechanisms for collaboration between teachers and students.