STEM Leadership and Training for Trailblazing Students in an Immersive Research Environment
STEM Leadership and Training for Trailblazing Students in an Immersive Research Environment
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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
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
William Gray
中科院分区：
文献类型：
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作者：
Marisel Villafañe;E. C. Johnson;Marisa Hughes;Martha Cervantes;William Gray
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彻底改变医疗保健和精准医疗、自主系统和机器人技术以及神经科学等领域的进展。数据科学和人工智能的技能在工业研发中需求很高，但我们不认为工业中的传统招聘和培训模式（例如，实习、继续教育）正在满足不同学生群体的需要，这些学生将被要求在这些领域进行革命。我们的计划，基于队列的本科生创新和开拓性综合研究社区（cohort），目标是开拓性的，高成就的学生，他们在实现目标和成为数据科学，机器学习和人工智能研究的领导者方面面临障碍。传统的招聘做法往往会错过这些来自非传统背景的雄心勃勃和有才华的学生，这些学生不坚持研究生涯的风险更高。在EMBA课程中，我们全面招聘，根据学生的承诺，潜力和需求选择学生。我们为我们的实习设计了一个培训和支持模型。该模型包括压缩数据科学和机器学习课程，一系列专业开发培训研讨会以及基于团队的机器人挑战赛。这些活动培养了这些开拓性的学生所需的技能，为未来充满活力的、以团队为基础的工程团队做出贡献。
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.