Using a Graph DB to Customize Online Learning
A combination of graph databases, Big Data, and AI are being used to personalize online learning.
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I've written several times already about how to learn from resources online, such as how to find free AI learning materials and how to use interactive training to reinforce what you learn. My career in technology has evolved alongside the changing way that information has been presented. My very first DZone blog post was about learning C while shuttling around London on the tube network. Once the Internet made it easier to find information, there I was, downloading and reading basic documentation in .chm format, then visiting the first of the developer portals, subscribing to my favorite set of online programming blogs and, latterly, on StackOverflow, MOOCs and of course, DZone!
In short, I am always interested in the use of technology in learning because just when I think I've seen it all, something new arrives on the scene to improve it, setting me off on another quest to learn another topic in a different way.
I'm also well-known for my interest in graph databases, so I was interested to hear about an education service company based in Korea called Kyowon, which has recently launched a personalized education service for online learning. Kyowon has been in the industry for over 30 years, offering a range of learning content for major subjects including math, language, and science. Its goal with the new product is to deliver optimized educational content services by analyzing the learning data of participants and recommending a set of customized questions in real time. It identifies the areas the users need to catch up with and determines an optimal learning path just for them. The tool can also be used to visualize the participant’s knowledge so they can see their learning progress at a glance.
The tool uses AgensGraph, a graph database management solution developed by Bitnine. According to Cheolsun Kang, CEO of Bitnine, "The education sector is one of the key areas where capitalizing on Big Data and AI has been most expected. By introducing AI technology...we will be able to make a dramatic impact.”
But what makes the tool different? Conventional online learning systems provide options which allow you to adjust the difficulty level and learning progress, but the curriculum never changes. With the use of artificial intelligence to review the learning pattern, the path through the subject can be customized for every user. The graph-based knowledge system provides a conceptual framework of the school subjects and manages the students and their learning record, then performs analysis of their academic achievement. This can be used to recommend a study path and tests progress, including reinforced learning and retesting on the topics where it is needed.
As the parent of a child with dyslexia, I find this an interesting approach since it effectively provides a learning record to illustrate strengths and weaknesses. In the future, who knows, perhaps it could become part of official learning across schools worldwide and take some of the focus off of exams as the only way to determine what a child can do and what they know! Please let me know your thoughts in the comments!
I'd like to thank Bitnine for getting in touch with me to let me know about their collaboration with Kyowon and allowing me to write about it (for which I received no fee).
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