AI in learning: An introduction
The conversations about Artificial Intelligence (AI) in learning and development grows. Let us just clarify some words used by the experts.
AI is an ecosystem. That is a biological community interacting with a complex network or interconnected system. Basically you, a learner and a computer. AI, that is having intelligent machines, with intelligent computer programs that do things that require intelligence when done by humans.
Like the things you do to help people learn. The key element is adaptive learning. Adaptive learning is where AI presents learning material according to the learner's needs. Analytics predict where action can be taken to better support a person, and where personalisation will be most effective.
Analytics is the discovery, interpretation, and communication of meaningful patterns in data.
Organisations may apply analytics to business data to describe, predict, and improve business performance. In this case, learning. Personalisation consists of tailoring a service or a product to accommodate specific individuals, helping them learn information and skills.
Adaptive learning is where AI presents learning material according to the learner's needs. Analytics predict where action can be taken to better support a person, and where personalisation will be most effective.
One of the real problems with AI is the use of words as you have just experienced.
People are a centre of the AI system. People inform the technology of what they do or know. How would you know if a person does or does not know something? So how will the designers tell a machine? The machine does what you do; it asks questions.
The learner answers. It follows that AI is complex, it is difficult to build a technology which adapts to what a person knows or can do and wants to know or do but it is being done, and it does work.
The recommendations the learner receives are based on what they know and can do already and what they want to learn or do. So, the information given to the learner is specifically structured for them, so it is adaptive and personalised.
Learning is complex and only now in the 21st century are we getting near the roots of it. Thus, algorithms are hard to build. Oops: Algorithm, a process or set of rules to be followed in problem-solving operations, especially by a computer.
Hold on. This is what you do to facilitate learning.
In the past people would walk from A to B. Now they can drive. That means a road, a car and the skill to drive the car. Perhaps you can’t build the road or a car but given those resources you can drive from A to B.
Yes, we have done this learning stuff successfully before. Now the machine is complex, but people are the same, and we have already learned much, and this is just a tool to do the job. Yes, “Give us the tools, and we can finish the job.” Winston Churchill. (9th February 1941).
Why do we need AI? With the Fourth Industrial Revolution engulfing us, learning is crucial, and each advance creates another advance requiring new learning.
However fast things are changing, you still need to build the skills of your workforce, says Jack Allen.
Dr Parves Khan on the importance of vocational education and training.
It's not just about transformation, it's about digital dexterity, says Agata Nowakowska.