Didactic AI: what is it and why do you need it?

Is generative positive?

Not long ago, the world fell under the spell of ChatGPT, the generative chatbot that answers all your questions. Many instructional designers (learning content developers) are heavily relying on generative AI to quickly present information in learning modules. And plenty of people are eagerly taking advantage of ChatGPT’s abilities, asking countless questions and receiving smart answers. But is this trend beneficial for the world of learning? Certainly, having easy access to vast amounts of information has its advantages. Getting instant answers to complex questions seems like a quick way to gain knowledge, right?

The learning process

Generative AI can help you gather a lot of information quickly for a learning module. Simply presenting information generated by generative AI doesn’t make the learning process itself better, smarter or faster. On the contrary. How can you ensure that a learner truly understands what they’ve read, listened to or watched? Can they remember it, reproduce it and apply it in practice months later?

The ease with which information can be obtained has made memorization less important than ever. Why bother memorizing when you can look it up in an instant? This “Google effect” 2.0 is undeniably useful. There’s no need to memorize everything. Some things you can easily look up when you need them, but some things you simply need to have top of mind. Consider critical knowledge and skills like security protocols, compliance rules, cybersecurity awareness, hygiene rules, and so on. There are skills for every job that you need to remember. Unfortunately, ChatGPT can’t help you with that. Luckily, there are AI algorithms designed to accelerate and optimize the learning process itself. This is where didactic AI comes into play.

What is didactic AI?

Didactic AI uses elements from neuroscience in an algorithm to optimize the learning process. It makes you develop knowledge and skills faster as well as maintain them better. The Drillster app does this in several ways:

• Adaptive learning . First, personalization is key. An adaptive algorithm tailors the learning path to the learning needs of each user. The level, pace, and learning content can be personalized to fit each individual’s needs perfectly. The more adaptivity, the better. Our algorithm is question-based. Participants learn by answering questions, dilemmas, situations, etc. With each answer, the algorithm learns more about that participant. Was the answer right or wrong, how many questions and question variants of this learning element have already been answered right/wrong, and how long has it been since someone answered a question on this element? Also taking into account the probability of guessing. This data is used to determine the next question, whether someone has achieved the desired level of knowledge, and when that knowledge starts to fade.
• The forgetting curve and spaced repetition. The algorithm determines the best time for the next learning session (using spaced repetition) and which parts of the learning material should be revisited. This is because knowledge and skills quickly fade away if not practised (due to the forgetting curve). The smart algorithm calculates when knowledge starts to fade and sends notifications to prompt further learning. That refresher is done in a smart way: users are asked questions specifically about the material they found difficult before or material they haven’t seen in a long time. Over time, knowledge becomes more and more embedded. The algorithm then allows more and more time between learning moments. This saves a lot of time and yet competencies are retained, even in the long run.

This technology is truly an innovation of the learning process itself. It makes learning more effective and memorable, takes less time, and increases user engagement. At the same time, it gives employees more time for important work, which they can also perform better, ultimately preventing or reducing (near) accidents and fines. By using didactic AI, everyone has the necessary competencies ready when needed.