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Educational Resources on Technology, Race, Education and Justice –

LEARN:

  • What is big data?
  • Why Big Data in Education Matters?
  • How has big data impact equity and justice in education?
  • How has big data in education been used against equity and justice?

Download the DECK WATCH the lecture here:

Working Paper: Big Data in Education

Download the working paper for comprehensive content or enjoy my shorten version in my Briefly about my Brief series.

How do the values of Social Emotional Learning and Culturally Responsive Leadership Align?

More than thoughts leadership, content on how I take action.



Thought Leadership + Meditations

My thoughts on the The Missing Year Project, discussing family dynamics, Georgetown University, and sowing seeds for dreams.
 My thoughts the Radical Imagination and propelling yourself towards what lies right in front of you.

Quick Definitions in Big Data & Education

TermDefinitionsExample
Learning Management System a computer software used to deliver education sources & lesson, and organize learning information (grades, attendance, etc.) Metaphorically it’s the engine in a car. Powers the car, but is usefulness is tied a series of other machines & human beings.
Clickstream Data the process of tracking, reporting and delivery of educational courses, training programs They’re footprints you leave behind when you search (walk through) a website (room).
Big Data concretely it represents the computational analysis of extremely large datasets to uncover patterns and trends, particularly around human behavior.  When Uber pool connects you with a driver and other passengers who are going to the same general area & similar ratings
Algorithm a detailed step-by-step instruction set or formula for solving a problem or completing a task. A meal recipe is a non-math based algorithm

Citations for Policy Brief Big Data in Education – 2019

Anderson, C. 2008. “The End of Theory: The Data Deluge Makes the Scientific Method

Obsolete.” Wired. http://archive.wired.com/science/discoveries/magazine/16-07/pb_theory/.

Atila Abdulkadiroglu, Parag A. Pathak, and Alvin E. Roth, “The New York City High School

Match,” American Economic Review 95 (2) (2005): 364-–367, available at

https://seii.mit.edu/wp-content/uploads/2011/12/Paper-New-York-City-High-School-Math.pdf.

“Beyond Data Literacy: Reinventing Community Engagement and Empowerment in the Age of

Data.” Data-Pop Alliance White Paper Series. Data-Pop Alliance (Harvard Humanitarian

Initiative, MIT Media Lab and Overseas Development Institute) and Internews. September 2015

Broussard, M. (2014, July 15). Why Poor Schools Can’t Win at Standardized Testing. The

Atlantic. Retrieved June 12, 2019, from

https://www.theatlantic.com/education/archive/2014/07/why-poor-schools-cant-winat-

standardized-testing/374287/

Broussard, M. (2019). Artificial unintelligence: How computers misunderstand the world.

Cambridge, MA: The MIT Press.

Capatosto, Kelly (2017). “Foretelling the Future A Critical Perspective on the Use of Predictive

Analytics in Child Welfare.” Kirwan Institute Research Report. Retrieved from

Click to access ki-predictive-analytics.pdf

Daniel, B. K. (2015). Big Data and analytics in higher education: opportunities and

challenges. British Journal of Educational Technology, 46, 904–920. doi:10.1111/bjet.12230

Daniel, B. (2017) Big Data and data science: A critical review of issues for educational research.

Br. J. Educ. Technol. 2017.

David Gillborn, Paul Warmington & Sean Demack (2018) QuantCrit: education, policy, ‘Big Data’

and principles for a critical race theory of statistics, Race Ethnicity and Education, 21:2, 158-179,

DOI: 10.1080/13613324.2017.1377417

Dede, C., Ho, A., & Mitros, P. (2016). Big Data analysis in higher education: promises and

pitfalls. EDUCAUSE review August 2016 (pp. 8–9). Retrieved September 1, 2016,

from http://er.educause.edu/articles/2016/8/big-data-analysis-in-higher-education-promisesand-

pitfalls

Dougherty, Shaun M., Joshua Samuel Goodman, Darryl V. Hill, Erica G. Litke, and Lindsay

Coleman Page. 2014. Middle School Math Acceleration and Equitable Access to 8th Grade

Algebra: Evidence from the Wake County Public School System. HKS Faculty Research

Working Paper, Harvard University.

Herold, B. (2014, May 2). InBloom’s Collapse Shines Spotlight on Data-Sharing Challenges.

Retrieved June 9, 2019, from https://www.studentprivacymatters.org/newsclips/inbloomspecific-

newsclips/

Kalil, T. (2012, March 29). Big Data is a Big Deal. Retrieved June 11, 2019, from

https://obamawhitehouse.archives.gov/blog/2012/03/29/big-data-big-deal

IMPROVING OUTCOMES FOR KIDS & FAMILIES Beyond Predictive Analytics & Data Sharing

Policy Brief by IN EQUALITY / Stop the Cradle to Prison Algorithm Coalition KEY, 2019.

KSTP. (2019, January 28). St. Paul, Ramsey County, school officials dissolve joint powers

agreement. ABC Eye Witness News 5. Retrieved June 10, 2019, from https://kstp.com/news/stpaul-

ramsey-county-school-officials-dissolve-joint-powers-agreement/5225446/

Linda Darling-Hammond (2007) Race, inequality and educational accountability: the irony of ‘No

Child Left Behind’,Race Ethnicity and Education, 10:3, 245-

260, DOI: 10.1080/13613320701503207

Mayer-Schonberger, V., and K. Cukier. 2013. Big Data: A Revolution That Will Transform How

We Live, Work and Think. London: Hodder & Stoughton. Kindle Edition

McNeel, B. (2018, December 11). Dallas Hits on Successful School Turnaround Model With ACE,

but It Comes at a Steep Price. Could a Wider Expansion Across Texas Now Be Its Best Bet to

Survive? The 74. Retrieved June 8, 2019, from https://www.the74million.org/article/dallas-hitson-

successful-school-turnaround-model-with-ace-but-it-comes-at-a-steep-price-could-a-widerexpansion-

across-texas-now-be-its-best-bet-to-survive/

Melisizwe, T. (2019, January 29). Coalition to Stop the Cradle to Prison Algorithm Celebrates

Hard-Won Victory with the Dissolution of Problematic Data-Sharing Agreement. Retrieved June

9, 2019, from https://dignityinschools.org/coalition-to-stop-the-cradle-to-prison-algorithmcelebrates-

hard-won-victory-with-the-dissolution-of-problematic-data-sharing-agreement/

Naughton, J. (2016, June 26). Even algorithms are biased against black men. The Guardian.

Retrieved June 11, 2019, from

https://www.theguardian.com/commentisfree/2016/jun/26/algorithms-racial-bias-offendersflorida

ONeil, C. (2018). Weapons of math destruction: How big data increases inequality and threatens

democracy. London: Penguin Books. doi:https://doi.org/10.1111/newe.12047

Office of Transformation and Innovation: Courtney Rogers Contributors: Angie Gaylord &

Cecilia Oakeley 2018

Press Office City of New York (2018, May). Mayor de Blasio Announces First-In-Nation Task

Force To Examine Automated Decision Systems Used By The City. Retrieved July 28, 2019, from

https://www1.nyc.gov/office-of-the-mayor/news/251-18/mayor-de-blasio-first-in-nation-taskforce-

examine-automated-decision-systems-used-by

Saunders, J., Hunt, P., & Hollywood, J. S. (2016). Predictions put into practice: A quasiexperimental

evaluation of Chicago’s predictive policing pilot. Journal of Experimental

Criminology, 12(3), 347-371. doi:10.1007/s11292-016-9272-0

Tullis, T. (2014, December). How Game Theory Helped Improve New York City’s High School

Application Process. The New York Times. Retrieved August 1, 2019, from

https://www.nytimes.com/2014/12/07/nyregion/how-game-theory-helped-improve-new-yorkcity-

high-school-application-process.html

Wang, Y. (2016). Big Opportunities and Big Concerns

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