{"title":"Changing the sources and usage of energy for a better and sustainable future for all: Proceedings from the 2021-2022 High School Big Data Challenge","authors":"","doi":"10.17975/sfj-2022-001","DOIUrl":null,"url":null,"abstract":"STEM Fellowship’s High School Big Data Challenge is an inquiry-driven experiential learning program that provides students an opportunity to learn and apply the fundamentals of data science – a crucial skill set for a young researcher in the digital age – through independent research projects. The COVID-19 pandemic disrupted high school education, at the same time creating a “fertile ground” for interdisciplinary, student-driven STEM education. This year, we invited students to explore issues of Affordable and Clean Energy at the Individual and Community Levels and to suggest their own evidence-based solutions, using Open Data and the principles of Open Science. Students explored many topics, ranging from Greenhouse Gas Emissions of School Buses to Legitimacy of Electric Vehicles to be the Greener Alternative We developed in-depth learning modules designed to bridge the gap between traditional high school courseware and digital reality and computational science. The students learnt a broad range of data analytics tools and programming languages which are useful for uncovering hidden patterns, trends in structured and unstructured data. Some of the tools the students learnt and used include Python, R, LaTeX, and machine learning. On behalf of the STEM Fellowship, we extend our sincere congratulations to all students who participated in the challenge, and wish them the best for their future endeavours. We want to express our appreciation to all the mentors and volunteers. This program would not be possible without patronage of CC UNESCO and generous support of our sponsors: RBC Future Launch, Let’s Talk Science, Digital Science, Infor, SCWST, CISCO Networking Academy, Canadian Science Publishing, and the University of Calgary Hunter Hub for Entrepreneurial Thinking. It has been a privilege for us to witness the analytical capabilities of the data-native generation of students first hand, and we are certain all entrants will continue to demonstrate excellence in their respective academic and professional careers.","PeriodicalId":268438,"journal":{"name":"STEM Fellowship Journal","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"STEM Fellowship Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17975/sfj-2022-001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
STEM Fellowship’s High School Big Data Challenge is an inquiry-driven experiential learning program that provides students an opportunity to learn and apply the fundamentals of data science – a crucial skill set for a young researcher in the digital age – through independent research projects. The COVID-19 pandemic disrupted high school education, at the same time creating a “fertile ground” for interdisciplinary, student-driven STEM education. This year, we invited students to explore issues of Affordable and Clean Energy at the Individual and Community Levels and to suggest their own evidence-based solutions, using Open Data and the principles of Open Science. Students explored many topics, ranging from Greenhouse Gas Emissions of School Buses to Legitimacy of Electric Vehicles to be the Greener Alternative We developed in-depth learning modules designed to bridge the gap between traditional high school courseware and digital reality and computational science. The students learnt a broad range of data analytics tools and programming languages which are useful for uncovering hidden patterns, trends in structured and unstructured data. Some of the tools the students learnt and used include Python, R, LaTeX, and machine learning. On behalf of the STEM Fellowship, we extend our sincere congratulations to all students who participated in the challenge, and wish them the best for their future endeavours. We want to express our appreciation to all the mentors and volunteers. This program would not be possible without patronage of CC UNESCO and generous support of our sponsors: RBC Future Launch, Let’s Talk Science, Digital Science, Infor, SCWST, CISCO Networking Academy, Canadian Science Publishing, and the University of Calgary Hunter Hub for Entrepreneurial Thinking. It has been a privilege for us to witness the analytical capabilities of the data-native generation of students first hand, and we are certain all entrants will continue to demonstrate excellence in their respective academic and professional careers.
STEM奖学金的高中大数据挑战赛是一个探究驱动的体验式学习项目,通过独立的研究项目,为学生提供学习和应用数据科学基础知识的机会——这是数字时代年轻研究人员的关键技能。COVID-19大流行扰乱了高中教育,同时为跨学科、学生驱动的STEM教育创造了“沃土”。今年,我们邀请学生在个人和社区层面探讨负担得起的清洁能源问题,并利用开放数据和开放科学原则,提出他们自己的基于证据的解决方案。学生们探讨了许多主题,从校车的温室气体排放到电动汽车的合法性是更环保的选择。我们开发了深入的学习模块,旨在弥合传统高中课件与数字现实和计算科学之间的差距。学生们学习了广泛的数据分析工具和编程语言,这些工具和语言对揭示结构化和非结构化数据中的隐藏模式和趋势很有用。学生们学习和使用的一些工具包括Python、R语言、LaTeX和机器学习。我们谨代表STEM奖学金向所有参与挑战的学生致以诚挚的祝贺,并祝愿他们在未来的努力中取得最好的成绩。我们要感谢所有的导师和志愿者。如果没有CC UNESCO的赞助和我们的赞助商的慷慨支持,这个项目是不可能的:RBC Future Launch, Let 's Talk Science, Digital Science, Infor, SCWST, CISCO Networking Academy, Canadian Science Publishing和University of Calgary Hunter for Entrepreneurial Thinking。我们很荣幸能够亲眼目睹数据原生一代学生的分析能力,我们相信所有参赛者都会在各自的学术和职业生涯中继续表现出色。