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UCLA faculty designs data analysis curriculum for high school students

(Jae Su and John Ingrao/Daily Bruin)

By Connie Zhou

Feb. 27, 2018 11:23 p.m.

UCLA faculty are working with local school districts to teach high school students big data analysis.

UCLA, in partnership with the Los Angeles Unified School District, received a five-year, multimillion dollar grant from the National Science Foundation in 2010 to design curricula for high school math and science classes with a strong emphasis on computational thinking. The university expanded the curriculum to six additional school districts in Southern California this academic year.

Introduction to Data Science is a yearlong high school course that serves as a prequel to introductory statistics courses, said Rob Gould, leader of the IDS curriculum design team and undergraduate vice chair of the UCLA Department of Statistics. The class teaches students data analysis and programming.

“The course is important because it makes students aware that we are living in a world of data,” he said. “We are living in an age where you really cannot afford to be ignorant about data, so we need to make sure people understand the role data is playing.”

Suyen Moncada-Machado, an instructional specialist at LAUSD, said after 2010, school districts nationwide began adopting the Common Core State Standards, a set of guidelines for consistent educational standards from K-12. She said under Common Core, high school math classes teach more statistical topics, such as how to find the mean and standard deviation of data sets.

Machado and the other teachers saw an opportunity to teach high school students about computational and statistical thinking after Common Core was adopted, and they pitched the idea of a high school-level data science course to LAUSD in 2010.

Faculty at the UCLA Department of Statistics validated the curriculum to make sure the statistical content was accurate and LAUSD educators like Machado made sure the curriculum was at the appropriate educational level for high school students, Gould said.

Students in the class use cellphones to collect data on different topics, such as stress levels and amount of time spent socializing. They then learn how to extract certain types of data and write code to analyze it, Gould said.

Gould added the class teaches R, a programming language and free software environment that is often used for data analysis.

Students enrolled in the course learn how to extract data from websites by scraping data from HTML tables on the internet and saving them to local files. Gould said the students also learn how to clean and filter their data and communicate and interpret their findings.

The class, which was initially offered in 2015, has seen increasing enrollment each year, Machado said. She added most students pass the class with a C grade or higher.

Machado said she thinks courses like IDS will help students prepare for college.

“At UCLA for example, many majors require a statistics course,” Machado said. “I think (high school) students are going to find what they learn in the course very applicable to college.”

William Sandoval, a professor at the UCLA Graduate School of Education and Information Studies, said he thinks high school classes on computation and data are important because jobs in the future will require more quantitative and data skills.

“The world is awash in data, and learning how to sift through and make sense of it is an important ability, not just for the workforce but to effectively participate as a citizen,” he said.

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Connie Zhou
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