September: Leveraging Authentic Data Across STEM Curricula

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As the demand for data grows across disciplines and industries, the skills required to work with data are becoming more important for jobs of all levels. And beyond preparing students for the future workforce, understanding data will help students grapple with complex issues such as the COVID-19 pandemic, climate change, and even their own health. This month, we will be discussing the opportunities and challenges in incorporating authentic data into STEM classrooms. This Theme of the Month is a collaboration between the STEM for All Multiplex and the CADRE Resource Center. Read Blog Post

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Expert Panel

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Leveraging Authentic Data Across STEM Curricula

 

Description: This month's panel explores the opportunities and challenges in incorporating authentic data into STEM classrooms.

 

This Theme of the Month Panel is a collaboration between the STEM for All Multiplex and the CADRE Resource Center.

 

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Discussion

The Discussion related to Leveraging Authentic Data Across STEM Curricula is now live! Introduce yourself and let us know your interest in exploring this theme. This discussion will continue through October.
Public Discussion
  • Icon for: Traci Higgins

    Traci Higgins

    Senior Research Associate
    September 2, 2020 | 12:31 p.m.

    Hi all. This is Traci Higgins, affiliated with TERC (in Cambridge, MA), where I have been working with Andee Rubin and team on the Data Clubs project. I'm particularly interested in the question of how students approach and use data especially when interacting with big messy data or multivariate datasets that have been collected and made available by others. What are students initially drawn to in these data sets, what sorts of questions do they think can be answered by data, how do their ideas change as they gain experience using technology to explore such data?

     
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  • Icon for: Josephine Louie

    Josephine Louie

    Senior Research Scientist
    September 16, 2020 | 12:28 p.m.

    Hi all -- This is an exciting topic and theme for the month. I'm Jo Louie, at EDC, leading two projects to promote students' statistical reasoning and data practices. In one project, Strengthening Data Literacy across the Curriculum (SDLC), we're targeting students in non-AP math/statistics classes with data investigations that explore social justice topics using American Community Survey and U.S. Census data. We have an explicit goal to promote multivariable thinking in this project, which we define as the ability to attend to interaction effects (and awareness of Simpson's paradox) when dealing with more than two variables. We've found that when high school students are thinking about data with a meaningful and relatable context, multivariable thinking seems to come up quite naturally. For example, one of our topics is income inequality and the male-female wage gap. They naturally generate ideas of other variables that might explain the gap (e.g., part-time vs. full-time work, marital status, type of occupations entered). Tools that Bill Finzer has created in CODAP (such as a third variable "splitting function") allow students to explore interaction effects visually, which really helps.

    In our other project, WeatherX, we are working with rural middle school students and examining extreme weather events using NOAA data and data collected by the Mount Washington Observatory in NH. Storms and extreme weather events are highly multivariable, and the relationships among variables are very complex. We are in the early stages of this project, and working with a slightly younger group of students, so it remains to be seen how far we can go in having students make meaning from associations of data with complex interrelationships, and with variables that may be a little more abstract (e.g., air pressure, wind speed).

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  • Icon for: CADRE Team

    CADRE Team

    Researcher
    September 2, 2020 | 05:22 p.m.

    Thanks Traci. Those are great questions. We at CADRE, a network for a PreK-12 research funding program at National Science Foundation, were excited to organize September’s Theme of the Month around Leveraging Authentic Data Across STEM Curricula. We have seen a growing number of NSF-funded projects focused on developing students’ data skills across disciplines and think this is a timely topic. We have a few additional questions for our different audiences. Educators: How are you incorporating data into your classrooms? Researchers: What are some of the challenges you’ve faced in integrating data into curriculum and professional development? Where have you seen the most exciting successes? All: What questions do you have for our webinar’s expert panel?

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  • Icon for: Jacob Sagrans

    Jacob Sagrans

    Researcher
    September 18, 2020 | 05:52 p.m.

    I just watched the recording of this great panel from yesterday. Thank you!

    Since I wasn't able to attend live yesterday to ask questions in the live chat, I'll post here.

    I work with Traci and Andee on the Data Clubs project. We've recently begun having middle school youth explore COVID-19 data and have incorporated discussion about how to do this into our teacher professional development work. We've used CODAP a lot in Data Clubs. I think is a really great tool for getting youth exploring data, because it's intuitive, accessible, customizable, and interactive.

    One thing I'm thinking about now, though, that I hadn't been thinking about as much before the pandemic is how to explore data on maps. The spread of a disease like COVID-19 has a geographical component. I would love to get youth and teachers exploring COVID-19 data on maps, ideally in a way that also is highly accessible and interactive, like CODAP is when it comes to making tables and graphs (a lot of the COVID maps I've seen so far have been static images, or not very accessible).

    I'm curious if any of the panelists or other people who attended or are watching the recording now have experience with guiding youth in exploring data on maps. What have you done? What worked well? What tools/maps/data sets have you used? Have any of you done this with COVID-19 data?

    Thanks!

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