The future of learning is personal

The course was built for a world where information was hard to reach

Most of the training we grew up with was built on one idea: knowledge is hard to reach, so put as much of it as possible into people’s heads. Memorize the facts, pass the exam, and let much of it fade soon after.

That world is gone. More than 1.2 billion people now use ChatGPT every week, according to OpenAI, and anyone with a phone can ask an AI assistant to explain almost anything, in plain words, at any hour. Finding a fact is no longer the hard part.

That doesn’t mean knowledge stops mattering. The cognitive scientist Daniel Willingham showed that thinking is “intertwined with the content of thought”: you can’t reason well about a subject you know nothing about. What changes is what is worth keeping in your head: the core ideas, how things connect, and the judgment to notice when an answer is wrong. The details you can look up in seconds can live in the tool.

People now learn by asking

The way people use software is changing. Instead of clicking through menus, more and more people type or say what they want and get an answer back. They bring the same habit to learning: they expect to ask about their own situation and get a reply, not to sit through a module that answers questions they never asked.

Long, one-way content has struggled for years. In a study of 6.9 million video sessions on edX, people watched for a median of at most six minutes, however long the video was. In MIT and Harvard online courses, 3.13% of the people who signed up for a course in 2017–18 finished it.

The problem was never that people don’t want to learn. It’s that a fixed course asks everyone to learn the same thing, the same way, at the same speed.

A tutor for every learner is finally within reach

In 1984 the educational psychologist Benjamin Bloom reported that students taught one to one by a tutor scored about two standard deviations above students in a normal class: the average tutored student did better than 98% of the class. He called it the “2 sigma problem”, because no one could afford a tutor for every learner. Later reviews found a smaller gain from human tutoring, closer to 0.8 of a standard deviation, but that is still large.

Early evidence suggests AI can close part of that gap. In a randomized trial in a Harvard physics course, students who used an AI tutor built on teaching research had median learning gains more than double those of students in an active-learning class, in less time. In a World Bank trial in Nigeria, six weeks of after-school AI tutoring in English raised students’ scores by 0.31 standard deviations on a test of English, AI knowledge and digital skills (0.23 on English alone).

The design matters. In a study of nearly 1,000 high-school math students in Turkey, those who practiced with a plain chatbot did better while they had it, then scored 17% lower on exams than students who never had it, once it was taken away. A version built to give hints instead of answers largely removed that harm. An AI that does the work for you isn’t a tutor. It has to make you think.

Choice of format, not “learning styles”

You may have heard that people are visual, auditory or hands-on learners, and learn best when they are taught in their style. It’s one of the most popular ideas in education, and the evidence doesn’t support it. A major review of the research found “no adequate evidence base” for matching teaching to a person’s learning style.

What does work is different, and better for everyone. People learn better from words and pictures together than from words alone, as Richard Mayer’s research on multimedia learning shows. And offering several ways to take in the material, take part and show what you know opens learning to more people. That is the heart of Universal Design for Learning, a research-based framework from the nonprofit CAST.

So the goal isn’t to label people and lock them into one format. It’s to let every learner choose, and switch: read when they want the detail, watch when they want to see it done, listen on the way to work, talk it through with a tutor, or try it hands-on. For someone with ADHD who loses focus in a long video, or someone with dyslexia who struggles with long text, that choice can decide whether they keep going. A review of 19 randomized trials found that technology-based programs brought small but real gains in attention for school-age children with ADHD.

Skills, in small steps

Employers surveyed by the World Economic Forum expect 39% of workers’ core skills to change by 2030. A course that takes a year to build and tries to cover everything can’t keep up. People need the skill they’re missing, at the moment they need it.

That points to short pieces built around one skill each, and to doing instead of reading about doing. A meta-analysis of 225 studies found that students in traditional lectures were 1.5 times more likely to fail than students in classes built on active learning.

Two well-tested habits make small pieces last. The first is retrieval practice, recalling instead of rereading: in one study, students who tested themselves remembered 56% a week later, against 42% for those who reread the text. The second is spacing: reviewing over days beats cramming in one sitting.

What personalized learning looks like

Put together, a personal learning experience looks less like a course and more like a good coach:

Why this matters for people who run training

When learning fits the person, it stops feeling like a task to get through and starts to feel like progress. We believe that is how completion goes up: not by chasing people with reminders, but by giving each of them a path they want to finish. Learning should feel like exploring and discovering, not like a chore.

This is what we are building Classbase to do. Its course builder turns your documents into short lessons made of interactive cards. Its AI tutor answers from your own course material, gives hints before answers, and passes hard questions to an instructor. Your team decides what the AI may do. We are building toward the rest of this picture, one step at a time.

If you want to see what personal learning could look like for your team, book a demo and we’ll show you.