Briefly about my Brief: Big Data in Education (P.1)

a peak into the national Landscape

Part 1: What is Big Data?

Since 2015, I have been exploring the connections between BIG DATA + EDUCATION + SOCIAL JUSTICE. My research primarily focuses on big data’s role in public education particularly how it impact black and brown communities.

Most recently I’ve partnered with NYU Metro Center to investigate the practical applications and limitations of big data in education today. Below are a few highlights from our early research. This will be a series of post, each addressing a key definition or lesson learned.

Citations for post

If you’re looking for a broader brief (see what I did there) download the full working paper on my portfolio page.

What is Big Data?

Big Data – While there is no one definition for big data, most authors think of it in terms of; data that is unstructured and too large to fit on a single machine, that is collected at a high velocity, and that can be used to derive statistical insights at an unprecedented rate (O’Neil, 2016)

When have I seen it?

Specifically, big data in education is a tool used to predict student outcomes, shape policy decisions, and improve learning.

In 2004, New York City became the first city to adopt algorithmic-based high school choice selection, as a way to streamline the complex high school admission process. Since adopting the system the number of students who did not receive an offer from one of their chosen schools fell drastically—from 30,000 students in 2003 to 3,000 students in 2004. (Atila Abdulkadiroglu, Parag A. Pathak, and Alvin E. Roth, 2005) Within the same year additional cities including Boston, Denver, and New Orleans have adopted similar systems with the goal of improving enrollment efficiency and fairness.

Note: In 2019 the New York City Department of Education came under fire recently after the news that only 7 black students were admitted to Stuyvesant High School (known as an elite institution), out of 895 seats. Most articles failed didn’t mention anything regarding the technology at the core of the selection process.

That has not stopped organizations like IntegrateNYC, a youth-led advocacy organization focused on racial diversity in New York City high, who are aware of the algorithmic bias in the technology and are engaging in hackathons to improve the algorithm originally built by a Nobel Prize winner.

Like hearing good news about nerds?

Great, my next post is brief brief on good work in big data! Post 2

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