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A Case Study Examines How a New Content Integration Impacts Learning Outcomes with AI Experience Inputs

  • Kwan-Keung Ng,
  • Shao-Fu Li,
  • Lap-Kei Lee,
  • Louise Luk

摘要

This study analyzes the process of integrating artificial intelligence (AI) content into a computer graphics (CG) course for architecture students at a Taiwanese university. The university places a high priority on AI education, and students are required to pass an AI competency test to graduate. The CG course is well-suited for integrating AI components since it relies heavily on visualization and graphics. The study collected both quantitative and qualitative data to assess student reactions and learning outcomes with the new AI content. An end-of-course survey revealed very positive responses. 78–100% of students agreed that the course helped increase their knowledge of AI and awareness of its applications. Further insights were gathered through follow-up focus groups. Students were optimistic about AI learning and did not feel that it detracted from their core architecture studies. However, they suggested slowing down the pace of AI content delivery. While students acknowledged the potential for applying AI in areas like construction visualization, they had a limited view of its broader professional impacts. In summary, this exploratory study suggests that incorporating AI content into an existing technical course was well-received by students and may have improved engagement for struggling learners. However, careful integration is necessary to avoid overwhelming students with too much new material. The study also discusses implications for curriculum design theory and preparing students for AI's professional impacts.