低成本的桌面学习工厂,以支持人工智能教学
Eduardo Orozco1, Paulo C Cárdenas2, Jesús A López1
1Department of Automation and Electronics, Universidad Autónoma de Occidente, Cali, Colombia.
HardwareX
|December 13, 2024
概括
本研究介绍了一种负担得起的,开源的硬件和软件系统,用于使用基于问题的学习 (PBL) 教导人工智能 (AI). 该原型通过对象分类促进了人工智能和计算机视觉方面的实践学习.
科学领域:
- 工程教育 工程教育教育
- 计算机科学教育计算机科学教育
- 人工智能教育 人工智能教育
背景情况:
- 积极的教学方法,如基于问题的学习 (PBL),需要易于使用的工具.
- 整合以工作为导向的技术技能对于学生的发展至关重要.
- 现有的AI教育工具可能昂贵而复杂.
研究的目的:
- 开发一个低成本的,开源的原型教学人工智能 (AI).
- 集成硬件和软件,以实践人工智能和计算机视觉指令.
- 支持积极学习方法和发展技术技能.
主要方法:
- 利用负担得起的电子元件 (Arduino,电机,传感器) 来构建一个规模化的输送带系统.
- 实施了一个开源的图像分类程序,能够通过各种特征识别对象.
- 为复制提供了详细的构建步骤,电路和代码.
主要成果:
- 成功创建了一个用于实验人工智能教学的功能原型.
- 该系统使用机器学习范式实现对象分类.
- 演示了硬件和软件的集成,以实现实际的AI概念.
结论:
- 开发的开放式教育资源 (OER) 原型有效地促进人工智能和计算机视觉教育.
- 低成本的开源方法鼓励在教育环境中复制和更广泛地采用.
- 该系统支持通过实践经验开发实用的AI技能.
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