Big Data Analytics for K-12 Personalized Learning

KimJonesimageBy Kim Jones, CEO, Curriki

There is a rush, perhaps a gold rush, underway in efforts to leverage Big Data analytics to improve K-12 educational results.

A story from Reuters
reports that a new $100 million data warehouse has been built in the U.S. to monitor academic achievements of public school students, from kindergarten through grade 12. The article states that “The database is a joint project of the Bill & Melinda Gates Foundation, which provided most of the funding, the Carnegie Corporation of New York and school officials from several states.”


Already 9 states in the U.S. are participating to some degree, and two of these, New York and Louisiana, are planning to provide all or most of their student records into the data warehouse. The database includes students names and addresses, and other personal information.

A non-profit named inBloom, Inc. (previously called the Shared Learning Collective) has been established to operate the database, which already contains millions of student files. It is a cloud-based data warehouse for student data such as grades, test results, assessments, standards met, behavior and attendance. It is not a repository for digital content, but will contain links to content, leveraging the Learning Resource Metadata Initiative methodology. The stated goal for the data warehouse is to support more personalized learning.


Here you can watch a video that introduces inBloom’s vision for customized teaching and learning:!

A very large amount of data is gathered by school districts and states, but resides in many separate databases and is not cross-correlated or well-analyzed. This project aims to change that. See this Mindshift article:
Pulling data together in this way is intended not only to make learning more customized, but also to make it easier to track results as students move from district to district or even state to state. In addition, it will allow data analysis on student achievement to be linked to various learning resources, potentially including the 46,000+ resources on Curriki.

Educational software suppliers are excited by the opportunity to mine the database and better determine what educational products to develop, including educational games and other digital learning products, lesson plans, and reports.

The goals of the project are laudable, but not surprisingly, given the sensitive nature of the data, privacy and security concerns are being raised. inBloom states on their web site: “We recognize the sensitivity of storing student data and place the utmost importance on the privacy and security of that data.” Parents in some states are already raising concerns about potential data leakage. While the data warehouse contains essentially the same data already held in school district databases, it now becomes available to a wider audience, including educators in other states than the original source for the data. And educational content vendors are requesting access to test data, for example. Presumably this will be made anonymous when supplied. Ownership of the data is retained by the states and districts that supply it. But some organizations, including the PTA and ACLU, are already asking “What are the remedies if and when data leaks?”.

We’d be interested to hear what you think about this project. What benefits and risks to you see in amassing a well-integrated and analyzable database of K-12 student achievement? How would you want to see this data being used to improve learning outcomes? Do the benefits outweigh the risks? Please provide comments.

3 responses to “Big Data Analytics for K-12 Personalized Learning

  1. thanks a lot for sharing such an knowledgeable and useful post.

  2. Linda Boudreau

    Great information, thanks for sharing. There is a lot of great work being done with data analysis and data linkage tools for the future of education with P20 and SLDS initiatives. Linking K-12 data with college and career data will certainly have a positive, significant impact on student achievement.

    Linda Boudreau
    Data Ladder

  3. Linda Boudreau

    One more thought: a single comprehensive and timely education data standard that ensures usability is key to the success of these programs. States need to take advantage of the data analysis that is being made available, turning education data into actionable information that can change the future of our workforce.

    Linda Boudreau

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