What We Learned At The AWS Summit: Using Machine Learning in EdTech

The machines are taking over!

AWS Summit 2018

Machine Learning is no longer the subject of a dystopian sci-fi movie, it’s now our reality. As we saw at the AWS Summit in New York City, Machine Learning (ML) is the talk of the tech industry, especially when it comes to big data. Amazon unveiled a new component to its natural language processing (NLP) service -- Amazon Comprehend Syntax Identification -- that interprets text-based data’s nouns and adjectives and extracts insights from it. This service can be connected to social media and other text based services (i.e. blogs, comments, emails, etc.) By using it, companies could extract valuable insights from customers by analyzing keywords, understanding customers’ sentiments, personalizing content, and categorizing content.

While this hasn’t expanded to edtech use cases just yet, we predict this type of technology could bring exciting changes to the classroom. In the same way that innovative educators took to Twitter to connect and teach digital literacy in the classroom, we believe it’s only a matter of time for Machine Learning insights to be invaluable to districts and educators.

 Photo by  rawpixel  on  Unsplash

Photo by rawpixel on Unsplash

For edtech innovators looking for the next challenge, here are some ways Amazon Comprehend could potentially be developed to be used by educators and parents:

1. Nipping cyberbullying in the bud before it get outs of hand.

Social media has made us more connected than ever. However, the dark side of this hyperconnectivity has led to bullying outside of school hours. According to DoSomething.org, only 1 in 10 victims report cyberbullying to a parent or trusted adult, yet 70% of teenagers frequently see bullying online. Since social media is saturated with an endless feed of content, a lot of this harmful activity can slip under the radar.

By using Amazon’s services that can mass-analyze adjectives and sentiment, there could potentially be a way for parents or guardians to quickly flag negative comments, nipping cyberbullying in the bud.

2. Districts may efficiently interpret qualitative data from schools and parents.
 

For a student to have a well-rounded education, there’s constant back-and-forth from parents, from teachers, from administrators, from the district...and so on. Qualitative data like this is often the hardest to analyze and sift through, especially navigating the already-complex space of education. We believe, with a service such as Amazon Comprehend, administrators could efficiently go through text-based feedback and better understand the needs of the schools, parents, teachers, and students.
 

3. Teaching digital literacy in the age of fake news

Fake news is currently the top headline of, well, the news. How can an educator effectively teach students digital literacy, when even some adults can’t even tell the difference? According to the keynote from the AWS Summit, developers can build their own models within Amazon Comprehend. If digital literacy is, in fact, a lesson plan within an educator’s curriculum, this could be used to help students understand how there are certain keywords or sentiments that should alert them to dig deeper into a headline and ask questions about the reliability of its sources.

Even outside of education, this could be helpful for everyone to analyze their social media feeds and see just how truthful the content really is.


Machine Learning in education is truly an exciting opportunity to explore. Of course, there are always concerns for privacy and efficacy of the results it may produce. These concerns are valid, but there is no doubt that the machines are about to take an even bigger role (and give educators and parents some much needed help)! Like any new technology, there will be a lot of trial and error, but that is exactly why edtech innovators love what they do.

 

Where do you see Machine Learning in edtech? We’d love to hear your ideas and help you with your edtech needs. Message us or give us a shout on Twitter @_ProjectEd!