AI In Education — Personalized Learning

Problem 1: Students are ahead of what’s being taught in the classroom and become easily bored.

Problem II: Students are behind of what’s being taught in the classroom and become discouraged to move on.

Fact: It is virtually impossible to keep a pace suitable to 30 different individuals in a class.

Solution: Personalized learning

In a personalized learning experience, the course material adapts to your unique identity, your interests, your preferred way of learning and gives you an opportunity to, in your own way, learn what is necessary to advance.

Personalized learning is probably the most common AI application in edtech today and is a sizzling hot topic in the overall educational sector. And for a good reason. For long it’s been known that different individuals learn in a different way and at a different pace, but most schools are still stuck in the same habit of the active, lecturing teacher and the passive, listening students. A seemingly persisting one-size-fit-all-solution is being applied to a wide spectrum of personalities and backgrounds.

Moving from today’s ’learning factory’-type education to a student-centered model is not an entirely new idea, interest on this notion has been present since 1889. Already then, in Pueblo, Colorado, superintendent Preston Search introduced the first ever known plan that would permit students to work in a more individual pace. However, the project was scrapped due to a lack of quality course material.

Today, emerging startups from all over the world are working to solve this problem once and for all. The hype on personalized learning is on, big time!

So, what’s all the fuss about?

The thought behind personalized learning is to create an individual lesson plan based on performance and personal trouble spots, and to put student needs in center. Different students have different needs and the best teaching practice for one student is not very likely to fit all. Variations can include learning pace, method, content, goals and of course individual interest.

By integrating artificial intelligence into the learning management software it is possible to collect data on the student and present even more customized content. For example, a student with a strong interest in racing cars could get more instructional examples featuring race cars and thus feel a stronger connection to the lesson and an understanding of how it could apply to the real world or a future profession.

The regular expression when grasping the full extent of personalized learning awesomeness.

Personalizing education means that students can learn at their own pace at their own level of ability. Faster students can charge ahead with more challenging tasks while slower students can repeat difficult parts until they are ready to move on, without having to slow down the entire class.

This feature has proven particularly useful in community colleges where there is such a large diversity of attendants. Some students have been working for 30 years and decided to make a career change, while others come directly from high school.

Essex community college in New Jersey, USA have reportedly seen a large decrease in student dropout by using a more personalized education. The Bill and Melinda Gates Foundation also reports amazing results from their deep dive in personalized learning and claims the technology could lead to dropout numbers cut in half.

As dropouts in the US still include approximately 7.000 students DAILY, striving towards a declining number is crucial to fill future employee needs. As the two most common drop out causes are due to boredom or perceived underachievement (according to a report from America’s Promise Alliance) a more personalized experience is likely to have a positive effect on these numbers.

Personalized learning makes it possible to find a compromise in the current system where students either pass requirements and move on to the next task, or fail and are forced to repeat an entire course. Now instead, students can just retake the parts where they are having trouble and not the whole course. This solution should mean less boredom and a better way of making sure students knowledge is sufficient across requirements.

Another aspect of personalized learning is the highly appreciated scheduling function. On Mondays, students fill in a small goal survey where they input how many hours they are going to study for this week, what concepts they will master and how many classes they will attend. Since the software is automatically keeping track of your metrics it is easy to see the correlation between their goal setting, and what they actually achieve on an individual level.


At the forefront of personalized learning software, Facebook CEO Mark Zuckerberg, and the Bill and Melinda Gates Foundation is leading the way together with Summit Public Schools in San Fransisco. Together they have developed a system that, so far, more than 100 schools have adopted. Feedback from schools has been overwhelmingly positive says Zuckerberg in an interview with Time Magazine.

Zuckerbergs also mentions personalized learning in an open letter, adressed to his daughter in these terms;

“Not only do students perform better on tests, but they gain the skills and confidence to learn anything they want. And this journey is just beginning. The technology and teaching will rapidly improve every year you’re in school,”

And students seems to like it too. In a study by McGraw-Hill Education Research, 85% of interviewed students says adaptive learning technology is a ’moderate or major improvement’ towards better grades. The Gates Foundation also conducted research and found that students using personalized learning software had more success in their studies over two years than a control group.

What do you think?

Is personalized learning the answer to a multitude of problems in our educational system?

Are you using personalized learning systems at your school?

What has it resulted in?


About the author: Hubert.ai is a young edtech company based in Stockholm, Sweden. We are working to disrupt teacher feedback by using AI conversational dialog with every student separately. Feedback is then analyzed and compiled down to a few recommendations on how you as a teacher can improve your skills and methods. Are you a teacher and would like to help us in development? Please sign up as a beta tester at our website :]