Publications & Presentations

Free Lecture: “Data Science Education: Two Initiatives”

Professor Rob Gould, Director of the Center for Teaching Statistics and Vice-Chair of Undergraduate Studies at the UCLA Department of Statistics, will be offering a lecture to the Southern California chapter of the American Statistical Association (ASA) on Saturday, December 11 at 10:15 am PST.
The talk is free of charge. If you’d like to attend, please register via the link below:
The rise of data science has created renewed interest in something that the Southern California Chapter of the ASA has been involved in for decades: statistics education. In this talk, Dr. Gould will offer his take on the differences between data science education and statistics education in the context of two projects with which he’s been deeply involved: ASA DataFest, an undergraduate data science contest that has been supported by the ASA from its inception; and the Introduction to Data Science (IDS) project, a high school data science course that is the first of its kind. Both of these projects illustrate some of the key features of modern data science education: a reliance on computers and programming, highly multivariate data of some complexity, and “nontraditional” data collection methods. The national growing interest in data science education is creating new courses and curricula, often without input from data professionals. In this talk, Dr. Gould will discuss opportunities for statisticians and data scientists to get involved in the development and shaping of valid data science curricula.

Mobilize: A Data Science Curriculum for 16-Year-Old Students

Presented By Rob Gould | IDS Lead PI
International Conference for Teaching Statistics (ICOTS) in Kyoto, Japan, July 2018


  • Gould, R.,(2021),”Towards Data Scientific Thinking”. Teaching statistics, 43(S1), pp. S11-S22. teaching statistics
  • Olivares Pasillas, M. C. (2017). Toward Critical Data-Scientific Literacy: An Intersectional Analysis of the Development of Student Identities in an Introduction to Data Science Course. UCLA. ProQuest ID: OlivaresPasillas_ucla_0031D_16070. Article
  • Heinzman, Erica. Math is No Longer a Four-Letter Word: A Mixed Methods Study of Two Non-Traditional Fourth-Year Mathematics Classes [Dissertation, University of California San Diego, California State University, San Marcos] (2020) PDF
  • Gould, Robert, Anna Bargagliotti, and Terri Johnson. “An analysis of secondary teachers’ reasoning with ‘big data’.” Statistics Education Research Journal 16.2 (2017). PDF
  • Philip, Thomas M., Janet Rocha, and Maria C. Olivares-Pasillas. “Supporting teachers of color as they negotiate classroom pedagogies of race: A study of a teacher’s struggle with “friendly-fire” racism.” Teacher Education Quarterly 44.1 (2017): 59-79. PDF
  • Philip, Thomas M., Maria C. Olivares-Pasillas, and Janet Rocha. “Becoming racially literate about data and data-literate about race: Data visualizations in the classroom as a site of racial-ideological micro-contestations.” Cognition and Instruction 34.4 (2016): 361-388. PDF
  • Roberts, S. (2015). Measuring Formative Learning Behaviors of Introductory Statistical Programming in R via Content Clustering. UCLA. UCLA Electronic Theses and Dissertations PDF
  • McNamara, Amelia Ahlers. Bridging the gap between tools for learning and for doing statistics. Diss. UCLA, 2015 PDF
  • Tangmunarunkit, H. “A general and extensible end-to-end participatory sensing platform.” UCLA, Los Angeles, CA, USA, UCLA Comput. Sci. Tech. Rep 140015 (2014). PDF
  • McNamara, A., Molyneux, J. Teaching R to High School Students…and Teachers. UseR!Conference, Los Angeles, CA, 2014. PDF
  • McNamara, Amelia, and Mark Hansen. “Teaching data science to teenagers.” Proceedings of the Ninth International Conference on Teaching Statistics. 2014. PDF PDF2
  • Philip, Thomas M., and Antero Garcia. “Schooling mobile phones: Assumptions about proximal benefits, the challenges of shifting meanings, and the politics of teaching.” Educational Policy 29.4 (2015): 676-707. PDF
  • Philip, Thomas M., Sarah Schuler-Brown, and Winmar Way. “A framework for learning about big data with mobile technologies for democratic participation: Possibilities, limitations, and unanticipated obstacles.” Technology, Knowledge and Learning 18.3 (2013): 103-120. PDF
  • Philip, Thomas, and Antero Garcia. “The importance of still teaching the iGeneration: New technologies and the centrality of pedagogy.” Harvard Educational Review 83.2 (2013): 300-319. PDF
  • Margolis, Jane, Joanna Goode, and David Bernier. “The need for computer science.” Educational Leadership 68.5 (2011): 68-72. PDF


  • The National Center for Research on Evaluation, Standards, and Student Testing (CRESST) conducted studies about the impact of the IDS curriculum on student and teacher learning. Two briefs, the IDS part of technical report (chapter 2 ), as well as the full technical report are available below.
  • CRESST Brief–IDS Student Impacts
  • CRESST Brief–IDS Teacher Impacts
  • CRESST Summary of Mobilize Evaluation–IDS Extract (Chapter 2)
  • CRESST Summary of Mobilize Evaluation–Full Technical Report
  • A study conducted by Roundhouse Consulting Group evaluated the IDS course’s impact on student college and career readiness. It is available below:
  • College Access Through Data Science Evaluation Report
  • Maierhofer LOCUS Evaluation for CRESST

    Conference Presentations

    • Casillas, M., Estevez, H. (April 2019). National Council of Teachers of Mathematics Annual Meeting & Exposition. “IDS: A High Schooler’s Entryway to the World of Big Data”, San Diego, California.
    • Estevez, H., Casillas, M. (November 2018). California Mathematics Council – South, 59th Annual Mathematics Conference. “IDS: A High Schooler’s Entryway to the World of Big Data”, Palm Springs, California.
    • Gould, R., Moncada, S., Ong, C., Johnson, T., Molyneux, J., Tangmunarunkit, T., Zanontian, L. (July 2016). “Preparing secondary teachers to teach data science: lessons learned”. Conference publication, IASE Roundtable 2016, Berlin, Germany.
    • Gould, R., Johnson, T., Machado, S., Molyneux, J., and Bargagliotti, A. (July 2016). Modeling with “Big Data” in Secondary Schools: An exploratory study. Presentation at SRTL-9 (Statistical Reasoning, Thinking and Literacy), Paderborn, Germany.
    • 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. (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.
    • 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.
    • Gould, R. (September 2015). University of Minnesota.  “Data Science in High School: The Mobilize Project”
    • Gould, R., Molyneux, J. (September 2015). American Statistical Association, Orange County, California. “Data Science in High Schools.”
    • 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.”
    • H. Tangmunarunkit, S. Nolen, J. Ooms, W. Reynolds, R. Rochio, E. Sakabu, R. Gould. (April 2015). ohmage: an innovative data investigation platform for developing statistical thinking in STEM. Submitted to AERA 2015, Computer and Internet Applications in Education (SIG #22).
    • 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. Link