Your help could further MMSA’s vision of a brighter STEM future for the State of Maine and the nation. Today, I ask you to support MMSA and become a part of the movement to support exciting new ways for our youth to learn about science, technology, engineering, and math.
Where and how do kids learn about data science and big data? Not much about this new field is currently addressed in schools. Yet hundreds of thousands of workers need to know how to wrangle and make sense of existing data sets. Everyone from staff who map crime data for the Portland Police Department to workers who manage the inventory at LL Bean need to know how to work with messy on-line data sets.
The Data Clubs project is designing and testing a model for materials that integrate accessible computer tools into data analysis to provide middle school students with a low-floor, high-ceiling and high-interest introduction to data science. The NSF-funded project, which is jointly led by MMSA and TERC (a STEM education organization in Cambridge MA), introduces 6th-8th graders to data science in out-of-school programs and summer camps. Three data modules (each consisting of 10 hours of work) will be developed and tested with 120 youth in rural and urban areas of Maine and Massachusetts.
Youth will engage with data that is accessible, useful, meaningful, and have a range of interesting variables that prompt productive inquiry. For example, we may examine data sets involving the animals at rescue shelters to determine where the animals come from, what kind of animals are sheltered, how long they stay, and who adopts them. Or we may look at flood data to determine what areas of the country are most exposed to rapid water rise, and what events precipitate flooding. Youth will have an opportunity to conduct their own data investigations and ask their own questions, using computer tools to explore existing data sets.
Because data science is such a new field, it is important to study how youth learn about it and engage in the processes of working with data. In the course of the project, we will develop and use two assessment tools: an interview measure of data skills and statistical reasoning, and a survey measure of attitudes and dispositions towards data science.