Publications, Presentations & News

Introduction to Data Science Luncheon

Join us at UCLA on November 29 to learn about the Mobilize Introduction to Data Science course.

November 29, 2016 12pm – 2pm
UCLA Faculty Center

RSVP by 11/1/16 at: http://tinyurl.com/ids-luncheon.

Introduction to Data Science Save the Date

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. http://escholarship.org/uc/item/1mm9303x
  • 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 “Measuring Formative Learning Behaviors of Introductory Statistical Programming in R via Content Clustering”, unpublished Masters thesis, UCLA Dept.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. http://escholarship.org/uc/item/62m217kx
  • 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.”

 

News

 

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

Group_IDS
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 Code.org, 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
https://codeforthemission.ucla.edu/mission/node/213

 

“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.