基于问题的生活情境问题探究--以人工智能在自然科学中的学习效果为例

King-Dow Su
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摘要

本研究以基于问题的学习(PBL)教学法为重点,设计了人脸识别系统、智能路灯、无人机等人工智能(AI)作为教学材料。在自然通识课程中融入生活情境问题教材,开发具有有效性和可靠性的学习感知问卷(LPQ),以评估学生对课程的感知。基于有效的测评工具,对56名大学生的新兴技术情境问题学习情况进行测评,评价他们的满意度、学习情况和学习效果。研究结果如下:(1)构建了人工智能在人脸识别系统、路灯和无人机情境中应用的教材;(2)开发了具有信度和效度的LPQ;(3)大多数学生对人工智能融入PBL教学表示满意;(4)大多数学生认为不同学科的跨领域学习整合有助于提高自学效果,确保持续的学习兴趣;(5)许多学生认同该课程可以提高学习效果。今后,将注重教学实践,结合易于使用的人工智能教材内容,增加互动学习的机会;此外,在研究中增加有效样本的数量,提高实验的深度和研究的广度。
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Problem-based life situational issues exploration–Taking the learning effectiveness of artificial intelligence in natural sciences
This research focuses on problem-based learning (PBL) teaching methods and designs artificial intelligence (AI) in facial recognition systems, smart streetlights, and drone as teaching materials. To integrate teaching materials of life situation issues into the natural general curriculum and develop a learning perception questionnaire (LPQ) with validity and reliability to evaluate students’ perception of the curriculum. Based on a valid assessment tool, 56 college students were assessed on their learning of emerging technology contextual issues to evaluate their satisfaction, learning situation, and learning effectiveness. The results of the study are, as follows: (1) construct teaching materials for AI application in face recognition systems, street lights, and drone situations; (2) develop an LPQ with reliability and validity; (3) most students are satisfied with the integration of AI into PBL teaching; (4) most students believe that the integration of cross-domain learning in different subjects can help improve self-learning effectiveness and ensure continuous learning interest; and (5) many students agree that this course can improve learning outcomes. In the future, the focus will be on teaching practice, incorporating easy-to-use AI textbook content, and enhancing the opportunities for interactive learning; in addition, increasing the number of effective samples in the research to improve the depth of the experiment and the breadth of research.
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