Publications, Presentations & News

Many college students struggle to pass remedial math. Do they need to?

Introduction to Data Science was featured on PBS NewsHour’s Making the Grade segment.

By Hari Sreenivasan, PBS NewsHour
May 14, 2019

Colleges created remedial education classes to ensure students were sufficiently prepared for more advanced material. But increasingly, there’s a sense that remedial courses are hurting the prospects of the students they are intended to help. As a result, some California colleges and high schools are rethinking their approach to teaching math — with encouraging results. These new approaches include the Introduction to Data Science class, which appears in the video at 3:40.

See the video…


IDS Lead PI, Rob Gould presents “Mobilize: A Data Science Curriculum for 16-Year-Old Students” at the International Conference for Teaching Statistics (ICOTS) in Kyoto, Japan, July 2018


A quiet revolt reshaping the pathway to college

Pamela Burdman | EdSource
April 8, 2018

They make up less than one percent of Los Angeles Unified’s high school students, but one day they may discover they helped break through a long-standing barrier to educational opportunity for students in Los Angeles and beyond.

These students, about a thousand juniors and seniors, are collecting, analyzing and interpreting sets of data from their own lives. In the process, they are learning basic statistics and computer programming, not to mention gaining insights into things like their stress levels and snacking habits. “Big data” is not just transforming the way we live and conduct business; it also offers approaches to learning math that can engage students and open doors.

The students are taking a new course, Introduction to Data Science, that UCLA researchers found is fostering critical thinking skills, data awareness and positive attitudes. The course rests at the vanguard of a quiet revolt against the dominance of algebra in the high school curriculum, a revolt that could reshape the pathway to college for years to come.

After being piloted four years ago with funding from the National Science Foundation, the course is now being offered at 21 of Los Angeles Unified’s roughly 100 comprehensive high schools. Another six southern California districts are piloting it, with eight more lining up. The exponential growth speaks to the demand for alternative courses like these.

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UCLA faculty designs data analysis curriculum for high school students

BY CONNIE ZHOU | Daily Bruin
February 27, 2018

class with charts

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.”

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Los Angeles Teachers Give Students a Jump-Start on Data Science Careers

By Katrina Schwartz| KQED
February 26, 2018

IDS video

Every time we Google something or buy a pair of shoes online, we’re creating valuable data. And people who know how to analyze that data are highly employable right now. As computing enters every part of life, high school teachers are beginning to see it as their duty to prepare students for this changing world.

The Los Angeles Unified School District has teamed up with UCLA to develop an introduction to data science course that meets University of California and California State University application requirements. Students use a blend of statistics and computer science to analyze data sets they’ve either collected or found.

“They’re learning how to think critically with data,” said Suyen Machado, who helped write the course curriculum and coordinates the program that has spread to 30 schools in six districts.

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‘Big data’ classes a big hit in California high schools

Carolyn Jones | EdSource
February 19, 2018

Data science — the study of computer-generated “big data” — is the hottest career in the U.S., according to Glassdoor. And now it’s the hottest math class at a growing number of California high schools.

About 30 high schools in California have started offering data science classes for juniors and seniors, in some cases as an alternative to Algebra 2. A hands-on blend of statistics and computer programming, data science meets the requirements of A-G coursework — the series of classes in English, math, science, foreign language, history and other core subjects necessary for admission to the University of California and California State University systems — and doesn’t require prior knowledge of computers or statistics.

Data science is the study of large sets of data, using computers to look for patterns and trends. In data science classes, students write computer programs that help sort through data and identify regularities — essentially “taking a big data set and dancing around it and getting it to tell you its secrets,” according to math education consultant Tim Erickson, who writes data science curriculum.

And it’s proven to be a popular addition to high school math departments.

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Introduction to Data Science comes to the Centinela Valley Union High School District

CVUHSD was 1 of only 5 districts awarded the UCLA California Mathematics Readiness Challenge Initiative grant.

The $1.28M grant will provide for in-depth professional learning opportunities in Mathematics for a collaborative composed of our Mathematics teachers, instructional coaches, school site GrantImage.jpgadministrators, and faculty from UCLA to support the implementation and evaluation of grade 12 experiences that are designed to prepare students for placement in college-level courses in Mathematics. Through this partnership with the UCLA Teacher Education Program, we will be introducing a new Mathematics course, Introduction to Data Science (IDS) and providing extensive professional learning for their Mathematics Teachers.


Introduction to Data Science: Thinking Critically About Data

Publications and PrePrints

  • May 2015. Gould, Johnson, Moncada-Machado, Molyneux, “Modeling with ‘Big Data’ in Secondary Schools: An exploratory study”. Research proposal presented at SRTL conference.
  • June 2015. Bridging the Gap Between Tools for Learning and for Doing Statistics. Amelia McNamara, doctoral dissertation. University of California, Los Angeles.
  • Gould, R., Bargagliotti, A., Johnson, T. (2016). “An analysis of secondary teachers’ reasoning with ‘big data'”. Submitted to Statistics Education Research Journal.
  • Gould, R., Moncada, S., Ong, C., Johnson, T., Molyneux, J., Tangmunarunkit, T., Zanontian, L. (2016). “Preparing secondary teachers to teach data science: lessons learned”.  Conference publication, IASE Roundtable 2016, Berlin, Germany.
  • Roberts, Shane,(2015). “Measuring Formative Learning Behaviors of Introductory Statistical Programming in R via Content Clustering”, unpublished Masters thesis, UCLA Dept. of Statistics.
  • Philip, T.M., Olivares-Pasillas, M. C., & Rocha, J. (in press). Becoming Racially Literate about Data and Data Literate about Race: A Case of Data Visualizations in the Classroom as a Site of Racial-Ideological Micro-Contestations. Cognition & Instruction.
  • Philip, T.M., Rocha, J., and Olivares-Pasillas, M. C. (in press). Supporting Teachers of Color as they Negotiate Classroom Pedagogies of Race: A Case Study of a Teacher’s Struggle with “Friendly-Fire” Racism. Teacher Education Quarterly.
  • H. Tangmunarunkit, C.K. Hsieh, B. Longstaff, S. Nolen, J. Jenkins, C. Ketcham, J. Selsky, F. Alquaddoomi, D. George, J. Kang, Z. Khalapyan, J. Ooms, N. Ramanathan, D. Estrin. Ohmage: a General and Extensible End-to-End Participatory Sensing Platform. ACM Transactions on Intelligent Systems and Technology (TIST), Volume 6 Issue 3, April 2015.
  • A. McNamara, J. Molyneux. Teaching R to High School Students … and Teachers. Presentation. UseR 2014.
  • S. Nolen, J. Ooms, H. Tangmunarunkit. A generalized and customizable extension to the ohmage interactive dashboard. Winner of the Education Category: Closing the US Education Gap. UCLA Code for the Mission 2014.
  • H. Tangmunarunkit, S. Nolen, J. Ooms, W. Reynolds, R. Rochio, E. Sakabu, R. Gould. ohmage: an innovative data investigation platform for developing statistical thinking in STEM. Submitted to AERA 2015, Computer and Internet Applications in Education (SIG #22).


Conferences and Presentations

  • Philip, T.M. (June, 2016). Seeing race and racialization in interaction: The affordance and constraints of video data. Symposium paper presented at the annual meeting of The Jean Piaget Society, Chicago, IL.
  • Philip, T.M. (March, 2016). Becoming Racially Literate about Data and Data Literate about Race: A Case of Data Visualizations in the Classroom as a Site of Racial-Ideological Micro-Contestations. Invited talk for the TERC Colloquium, Cambridge, MA.
  • Philip, T.M. (May, 2016). Becoming Racially Literate about Data and Data Literate about Race: A Case of Data Visualizations in the Classroom as a Site of Racial-Ideological Micro-Contestations. Invited talk for the Graduate School of Education Brown-Bag Seminar Series, UC Irvine.
  • Gould, R. (July 2015.) New Zealand Association of Mathematics Teachers Conference, Auckland, New Zealand. “Data Science in High School: The Time has Come”
  • Gould,  R., Johnson, T. ( July 2015). Statistics Research in Teaching and Learning. Paderborn, Germany. “Modeling ‘Big Data’ in Secondary Schools.”
  • Gould, R., Bray, A., (June 2015.) United States Conference on Teaching Statistics, State College, Pennsylvania. “Developing Data Science Curricula.”
  • Gould, R. (September 2015. )University of Minnesota.  “Data Science in High School: The Mobilize Project”
  • Gould, R ()July 2016.  International Association of Statistics Education Roundtable Conference ” Preparing Secondary Teachers to Teach Data Science: Lessons Learned”, Berlin, Germany.
  • Gould, R., Molyneux, J. (September 2015.) American Statistical Association, Orange County, California. “Data Science in High Schools.”




Mobilize’s Suyen Moncada-Machado speaks to the LAUSD School Board about IDS and the need for Computer Science instruction.

Posted by Mike Szymanski on November 4, 2015
LA School Report

At a time of high employment demand for computer experts, fewer than half of LA Unified’s 98 traditional high schools offer computer science classes.

“We could have students go through LAUSD without any access to computer science at all,” Suyen Moncada-Machado, a district instructional specialist told a district board committee yesterday as part of a discussion of the district’s computer science programs.

She is involved with Mobilize, a program created by LAUSD and UCLA that’s being replicated in other parts of the country as a math course that incorporates statistics, science and coding. Another course has students design and use computer programs to solve problems.

As the second largest school district in the country, LA Unified is planning to provide all students access to computer science from transitional kindergarten to 12th grade by 2020.
Read the article.


Data science class offers L.A. Unified students a new handle on math

Ryan Menezes | Los Angeles Times
April 27, 2015

Thomas Navas, 16, a student in the Introduction to Data Science class at Francis Polytechnic High, uses data from the Centers for Disease Control to test his theory that there is a relationship between hours of sleep per night and a person's height. (Patrick T. Fallon / For the Los Angeles Times)

Thomas Navas, 16, a student in the Introduction to Data Science class at Francis Polytechnic High, uses data from the Centers for Disease Control to test his theory that there is a relationship between hours of sleep per night and a person’s height. (Patrick T. Fallon / For the Los Angeles Times)

During first period at Francis Polytechnic High School in Sun Valley, Monica Casillas asked her students to line up in order by height so she could organize a human representation of a “box-and-whisker” plot.

As they filed into place — most boys went to one end, most girls to the other — Casillas drew the data visualization on butcher paper. The rectangle in the center showed the typical heights of the class, with straight lines called “whiskers” extended from the box to show how far away the tallest and shortest students were from the middle.

Thomas Navas, a 5-foot-2 junior, found himself at the end of a whisker, the shortest student in his Introduction to Data Science class.

Standing at the end, Navas wondered what affected his height. Could his lack of sleep — about six hours a night — keep him from growing?

Asking questions of data is the aim of the class, which is being offered at 10 Los Angeles Unified School District high schools this year. The class gives students an alternative to traditional math; its curriculum is grounded in hands-on data collection, plus lessons in computer programming so students can get answers from data, a trade highly valued in many industries.

Read the article.


Introduction to Data Science: An Authentic Approach to 21st Century Learning

David Bernier | KCET
May 21, 2015

While K-12 computer science has recently seen a growth in awareness and opportunities for learning in high schools through the efforts of programs like Exploring Computer Science and groups like, there is less public awareness and limited opportunities for learning in areas like Statistics, and in particular the burgeoning field of Data Science, which blends statistics and computing. While colleges, particularly at the graduate level, have been responding to this demand by increasing the number of courses and programs focusing on data science, the K-12 space has thus far seen very little activity that might help to introduce students to these concepts and learning experiences.

Into this mix comes Introduction to Data Science (IDS), a program funded by the National Science Foundation as part of a Math-Science Partnership grant called Mobilize, involving UCLA and LAUSD. IDS is being piloted this school year by ten LAUSD high school teachers, to roughly 365 students. The course has been approved by the University of California Office of the President as a college-prep core mathematics course.
Read the article.


Mobilize tech team wins 1st place in UCLA’s “Code for the Mission” App Competition

Education Category: Closing the US Education Gap
Code for the Mission Winning Ed Team
Generalized Ohmage Dashboard
Team: Hongsuda Tangmunarunkit, Steven Nolen, Jerom Ooms


“Degrees of Freedom: Diversifying Math Requirements for College Readiness and Graduation”

reportApril 2015
This report by Pamela Burden acknowledges the Mobilize project’s impact on changing mathematics pathways.
Read the report.