Research Experiences for Teachers in Machine Learning

Kristen Jaskie, Jean S. Larson, Milton Johnson, Kathy Turner, M. O'Donnell, J. Christen, Sunil Rao, A. Spanias
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引用次数: 1

Abstract

Machine learning and Artificial Intelligence (AI) are national priority areas for research, education and workforce development. This work in progress paper describes a Research Experiences for Teachers program in sensors and machine learning launched in the summer of 2020. Motivated by national AI workforce needs, we designed a program that engaged high school teachers from STEM fields in machine learning research. In 2020, the program focused on AI algorithms for solar energy systems. Because of the COVID-19 conditions, the research experience was virtual and ran with a smaller teacher group than originally planned. The program included development of training content, algorithm and software training, research in solar energy monitoring, development of research reports and lesson plans, research presentations, and assessment. The assessment of the program included surveys, interviews, presentation observations, and follow-up in high school content delivery.
机器学习教师的研究经验
机器学习和人工智能(AI)是国家研究、教育和劳动力发展的优先领域。这份正在进行的论文描述了2020年夏天启动的传感器和机器学习领域的教师研究经验项目。受国家人工智能劳动力需求的推动,我们设计了一个项目,邀请来自STEM领域的高中教师参与机器学习研究。2020年,该项目专注于太阳能系统的人工智能算法。由于COVID-19的情况,研究经验是虚拟的,并且与最初计划的教师小组一起运行。该项目包括培训内容的开发、算法和软件的培训、太阳能监测的研究、研究报告和教案的编写、研究报告和评估。该计划的评估包括调查、访谈、演讲观察和对高中内容交付的跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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