Ipek Ensari, a postdoctoral research scientist at DSI, was recognized by the Computing Community Consortium for a paper she co-authored detailing how to educate K-12 students about data science.
The Consortium sponsored a white paper competition whose theme was CS for Social Good, or how to harness computer science (CS) to address societal challenges. Along with Schmidt Futures, Consortium officials selected three winning white papers, one of which, The Best Paper Authored by Grad Students or Postdocs, was awarded to Ensari and co-author Monica Chan, a doctoral student in the Instructional Technology & Media program at Teachers College.
In their paper “Using open-sourced data to nurture a civically engaged and computationally fluent generation,” the authors discuss making community data available and open-sourced for use in interdisciplinary K-12 data science education.
“Data science is a field growing rapidly in all industries but there is no standardized method, resource or platform to teach young students about data science,” the authors write. In the paper, the authors give practical examples of how to develop a hands-on data science curriculum for K-12 students.
To build a more civically engaged generation of young people, the authors maintain, educators need to find areas in school curricula where students can explore narratives of their neighborhoods. To facilitate this goal, the authors discuss two educational pilot studies based at Columbia. One study, called Dog Data Scientists, uses open source data and software to create hands-on data science activities for K-12 students. Led by Ensari, a team of graduate students that includes Chan built a dashboard from data about dogs whose owners live in New York City. Compiling data from NYC’s Open Data website, the dashboard prompts children to begin asking questions such as “Which dogs in NYC bite the most?” “What’s the most popular dog name?” or “Which breeds are most popular in the city?” Once the students have formulated questions like these, Ensari says, the children use the dashboard to discover answers to their questions.
“Teachers can use this project to experientially teach children a multitude of critical thinking skills about research,” she says. “The dashboard teaches them how to formulate a research question, look for trends and values in the data, derive results and conclusions, and disseminate results in a way that’s understandable not only to scientists but also the general public. Children are natural data scientists, inquisitive about data, as they’re always asking why.”
The Dog Data Scientists project was recently demonstrated at the “Data Science in the Classroom” workshop held at Teachers College (TC), which was co-organized by DSI and Hui Soo Chae, Senior Director for Research, Development and Strategy at TC. There, Ensari led a workshop for teachers, helping them learn practical strategies for introducing data science into their elementary and secondary school classrooms.
The second project discussed in the white paper, which Chan has been involved in, is a collaboration between the Snow Day Learning Lab at Teachers College and Columbia’s Lamont-Doherty Earth Observatory. This project explores how a group of NYC teachers and high school students learned data science together with mentorship from professional data scientists. It also traced how the teachers and students used data to conduct research about community challenges in their neighborhoods. Data science is inherently interdisciplinary, and as such can also easily be intertwined with high school subjects such as social studies, history and political science.
Ensari and Chan’s collaboration on the paper stemmed from their previous work on Dog Data Scientists. “I was excited when Monica asked me to join her on this white paper,” says Ensari. “Given our respective fields of study, this was an organic interdisciplinary collaboration.” The two called upon their backgrounds in technology education and cross-disciplinary applications of data science to address a question that has great relevance in educating the young: How can research in various fields of computer science, such as human-computer interaction and machine learning, help facilitate K-12 data science learning?
“Introducing data science in a hands-on approach to K-12 students can help them understand the data that infiltrates their daily lives on their cell phones and other devices,” says Ensari, “while helping them to use data to deepen their understanding of and try to solve some of the societal problems in their communities.”
— Robert Florida