STEM Leadership and Training for Trailblazing Students in an Immersive Research Environment

Marisel Villafañe-Delgado, E. C. Johnson, Marisa Hughes, Martha Cervantes, William Gray-Roncal
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引用次数: 2

Abstract

Educating the workforce of tomorrow is an increasingly critical challenge for areas such as data science, machine learning, and artificial intelligence. These core skills may revolutionize progress in areas such as health care and precision medicine, autonomous systems and robotics, and neuroscience. Skills in data science and artificial intelligence are in high demand in industrial research and development, but we do not believe that traditional recruiting and training models in industry (e.g., internships, continuing education) are serving the needs of the diverse populations of students who will be required to revolutionize these fields. Our program, the Cohort-based Integrated Research Community for Undergraduate Innovation and Trailblazing (CIRCUIT), targets trailblazing, high-achieving students who face barriers in achieving their goals and becoming leaders in data science, machine learning, and artificial intelligence research. Traditional recruitment practices often miss these ambitious and talented students from nontraditional backgrounds, and these students are at a higher risk of not persisting in research careers. In the CIRCUIT program we recruit holistically, selecting students on the basis of their commitment, potential, and need. We designed a training and support model for our internship. This model consists of a compressed data science and machine learning curriculum, a series of professional development training workshops, and a team-based robotics challenge. These activities develop the skills these trailblazing students will need to contribute to the dynamic, team-based engineering teams of the future.
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在沉浸式研究环境中为开拓性学生提供STEM领导力和培训
教育未来的劳动力是数据科学、机器学习和人工智能等领域日益严峻的挑战。这些核心技能可能会在医疗保健和精准医疗、自主系统和机器人以及神经科学等领域带来革命性的进步。工业研发对数据科学和人工智能技能的需求很高,但我们认为,传统的工业招聘和培训模式(如实习、继续教育)无法满足不同群体的学生的需求,而这些学生将需要彻底改变这些领域。我们的项目,基于队列的本科生创新和开拓综合研究社区(CIRCUIT),针对在实现目标和成为数据科学、机器学习和人工智能研究领域的领导者方面面临障碍的开拓性高成就学生。传统的招聘方式往往会错过这些来自非传统背景的雄心勃勃、才华横溢的学生,而这些学生不坚持从事研究工作的风险更高。在CIRCUIT项目中,我们全面招收学生,根据他们的承诺、潜力和需求来选择学生。我们为我们的实习设计了一个培训和支持模式。该模型由压缩的数据科学和机器学习课程、一系列专业发展培训研讨会和基于团队的机器人挑战组成。这些活动培养了这些开拓性学生的技能,为未来充满活力、以团队为基础的工程团队做出贡献。
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