Data Science Meets Science Teaching
Science Teacher
; 89(3):64-69, 2022.
Article
in English
| ProQuest Central | ID: covidwho-1824386
ABSTRACT
The use of large, open-source data sets is ubiquitous in scientific research. Scientists--ranging from meteorologists to chemists to epidemiologists--are researching and investigating critical questions using data that they have not themselves collected. To contribute to the growing effort to bring data science into classrooms, the authors have been implementing the NSF-funded "Data Clubs" project to examine using data sets on topics such as ticks and Lyme disease, COVID-19, and sports and leisure injuries. Much of this work takes place with youth in out-of-school settings. In addition to developing modules for youth, the authors worked with a group of 18 high school science and computer science teachers from Maine, New Hampshire, and Massachusetts who participated in a virtual 15-hour workshop series on data science education over the summer of 2020. The goal of the workshop was to introduce teachers to real and complex data sets, models for scaffolding learning, and tools for working with those data sets. In this article the authors share some of the key findings from this effort.
ERIC, Current Index to Journals in Education (CIJE); High Schools; Secondary Education; Teacher Workshops; Pandemics; Science Instruction; Maine; High School Teachers; Diseases; COVID-19; Faculty Development; Open Source Technology; Science Teachers; Computer Science Education; Scaffolding (Teaching Technique); Computer Simulation; Massachusetts; New Hampshire; Data Analysis; Clubs; Injuries
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Collection:
Databases of international organizations
Database:
ProQuest Central
Language:
English
Journal:
Science Teacher
Year:
2022
Document Type:
Article
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