Professionals

Investigating Income Inequality in the U.S.: Module Overview and Sample Lessons

The Investigating Income Inequality in the U.S. module focuses on describing, comparing, and making sense of quantitative variables. Students deepen their understanding of this content by investigating questions such as: How have incomes for higher- and lower-income individuals in the U.S. changed over time? How much income inequality exists between males and females in the U.S.? Does education explain the wage gap between males and females?

Building Statistical Thinking with Social Justice Investigations and Social Science Data

This poster provides an overview of the Strengthening Data Literacy across the Curriculum (SDLC) project, which is developing and studying curriculum modules for non-AP high school statistics classes to promote interest and skills in statistical thinking and data science among diverse high school populations. This early-stage design and development project aims to engage students with data investigations that focus on issues of social justice, using large-scale socioeconomic data from the U.S. Census Bureau and student-friendly online data visualization tools.

Webinar Recording & Slides: Tools for Building Big Data Career Pathways at Community Colleges

On July 8, we presented our Tools for Building Big Data Career Pathways at Community Colleges in an AMATYC webinar. Our presenters shared how they used the tools developed by our NSF-funded project Creating Pathways for Big Data Careers at their institutions to create data courses and programs.

Presenters:

Big Data Stackable Credentials Report

This report describes the efforts of four community colleges, Bunker Hill CC (MA), Johnson County CC (KS), Normandale CC (MN) and Sinclair CC (OH), who partnered with EDC on Creating Pathways to Big Data Careers, a project funded by the National Science Foundation’s Advanced Technological Education Program (DUE-1501927) to design and implement programs leading to middle skills data careers.

Data Practitioner Performance Based Rubrics & Glossary

This rubrics and glossary can be used to assess competence and proficiency in the skills identified in the Profile of the Data Practioner. The rubrics provide examples of what the work responsibilities of a Data Practitioner (middle-skilled data worker) “look like” when performed at four different levels of proficiency.

Lessons from Hurricane Katrina

By lboghossian on February 04, 2019

The Exploring Urban Mobility: Using Data to Solve Problems of the Future is creating data-intensive lessons for high school students to think about issues of urban mobility. Hear from one of the curriculum authors about the focus of one of the lessons: Hurricane Katrina.

The Two-Year College Data Science Summit

This final report, from the Two-Year College Data Science Summit, summarizing the summit, current state of data science/analytics programs at two-year colleges, recommendations, recommended program outcomes, and challenges. Learn more about the summit.

Ocean Tracks – A Journey Through the Ocean: A Modern Approach to Science Education

Research in the sciences is currently undergoing a massive transformation, as technological advancements shift big data into the forefront of investigative tools, and early education is looking for solutions to keep up. The Ocean Tracks program offers a structured learning tool that supports both students and teachers in tackling big data in the classroom.

Are There White Sharks Swimming Among Us?

By rKochevar on March 05, 2018

The company Strava was in the news recently for its ability to display highly accurate maps using position data from personal fitness devices (e.g., Fitbit, Apple Watch, etc.). Not only are GPS fitness devices tracking a person’s mileage on land, many also track water activities, such as swimming, to within a few meters.

Where Science Meets Science Fiction

By rKochevar on February 13, 2018

I’ve spent a lot of time recently thinking about how we can better teach science using data. I believe that 21st Century science is increasingly data-intensive, and that in order to teach science as it is actually being practiced, it should be possible to identify datasets and data stories relevant to most, if not all, topics in modern science to use in the classroom.

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