本研究發展一個人工智慧影像辨識課程，適合無運算思維及人工智慧基礎之大學生，培養學生運算思維能力與認識人工智慧，使用準實驗研究方法，對於大學生使用經驗學習環進行人工智慧影像辨識課程之學習成效進行研究。研究結果顯示採用不同的教學方式皆可以增加學生的運算思維與人工智慧概念，經驗學習環較適合初始具有較低運算思維能力與較低自我效能的學生，因為經驗學習環具有反思、抽象化及主動驗證歷程，能夠讓學生產生討論、合作與直接操作的行為，這些行為的出現能夠提升初始運算思維能力與自我效能較低的學生運算思維能力與自我效能程度。而主題式導向學習較適合初始具有一定運算思維能力及高自我效能的學生，因為其過去的學習經驗已經習慣講述式的示範教學方法，延續習慣的且表現不錯的學習方法較能夠維持良好的運算思維感知程度。

This research develops an artificial intelligence image recognition course, which is suitable for college students without computational thinking and artificial intelligence （AI） foundation. This course cultivates the computational thinking ability of students and their recognition of AI knowledge. This research uses quasi-experimental research methods to study learning effects. The research results show that different teaching methods can increase students' computational thinking and artificial intelligence concepts. The experiential learning cycle is more suitable for students who initially have lower computational thinking ability and lower self-efficacy. The stage of reflection, abstraction and operation can enable students to generate discussion, cooperation, and direct manipulation behaviors. These behavior patterns can enhance the computational thinking ability and self-efficacy. The subject-based learning is more suitable for students who have certain computational thinking ability and high self-efficacy initially. Their past learning experience has become accustomed to the lecture teaching method. Lecture continues the habit is better for them able to learn.

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