When I began working in the industry in 1994, the term ‘personalised learning’ was a buzz phrase being banded around in the education sector. The idea that education should be tailored to the individual needs of the students is not a new one and the phrase has been around since the 1960s but the fad of ‘personalised learning’ has ebbed and flowed ever since. However, can learning truly be personalised or will there always be barriers in the way?
It has always been a strong intention of mine since I began designing educational resources to personalise learning as much as possible. Even in the days when I was producing CD-Roms for whole class teaching, extra resources were provided to give teachers a toolkit to tailor the learning for their student’s individual needs.
Back in the 1990’s and 2000’s, software didn’t allow sophisticated tailoring. Although the use of scenarios did allow learners to make choices and change the direction they wanted their learning to go in. Based on their responses to specific questions, students could be directed to content more relevant to them, using ‘branching’. There was still however a limited amount of content programmed into the software and a set number of journeys the user could be taken on.
One industry where we have really seen a shift towards a more personalised experience is e-commerce. Since the emergence of the internet, products have increasingly been marketed through personalisation. Amazon and other retailers can use algorithms to tailor offers to you based on your previous purchases i.e. ‘people who bought this’ tag lines. When we enter a search term into google or look at products online, adverts for those products follow us through social media and the websites we visit to remind us to buy.
Can this be utilised more in education and training? Is it that straightforward? Can the actions of learners help optimise learning by bringing key information to their attention?
Already in education there is some ‘personalised learning’. Move forward to this decade and the emergence of dashboards such as BBC IPlayer allowing you to select content for your ‘channel’ and programmes you are interested in. This however very much still puts the learner in control. How does the learner know what is best for them?
I designed a website in 2013 for the Norfolk and Suffolk Dementia Alliance called The Learning Location. The overall aim was to provide access to training resources to people working with dementia patients, but instead of just providing a list, users could register and provide details such as their job role, qualification level and they would be shown training resources that would be relevant to them. All resources from e-learning, day workshops, academic lectures to college and university courses were ‘tagged’ with metadata such as audience, qualification level and resource type. This directed the right information to the right people.
We also provide several tools such as a Confidence Tool and a Learning & Development Needs Tool. The Confidence Tool allows users to rate their own confidence against given competency areas. They could revisit this as many times as possible, reviewing their increase in confidence as they progressed through recommended training resources.
The Learning and Development Needs tool provided 3-character video scenarios, each of them dealing with different competency areas taken from the Competence Tool. Users answer questions as they progress and their responses allow the system to mark their knowledge on competence areas, then directs them to resources specific to them. They can also ‘bookmark’ resources, and return to revisit the Confidence Tool. Further funding was later available to develop learning locations for Palliative Care, Skin Care, Falls and Continence.
These tools were very successful. Through self-assessment, participants could be directed to the right learning experience but what if the computer did the assessment. What if the learning could be tailored specifically to that person like a teacher would? Enter AI and AR.
AI, or artificial intelligence is when a digital device uses perception and then takes action for maximum success. Going back to the software where the learner’s choices led to a range of set outcomes, theoretically AI could access how a learner is doing and create a new outcome if it was in the best interested of the learner.
AR or Augmented reality is where using a headset, learners can experience a simulated environment. This has endless opportunities for learning about places and situations that are difficult to set up. Surgeons could potentially learn how to operate without opening up a human.
With the technological advancement of recent years, the opportunities are endless. It seems inevitable that AI and AR will become a key component in learning.
A buzz phrase in recent years is the term ‘agile learning’. This is where the development of educational content is focused on speed, flexibility and collaboration. AI helps deliver content in this way. The benefit for businesses is a quick, effective and well-tailored learning experience for each individual learner. Employees can therefore get back to work and put what they’ve learnt into practice in no time.
At the recent Learning Pool Live 2017 event Don Taylor while talking about agile leaning suggested:
‘Personalising learning based on the location of the user, their performance on previous learning or related activities or the expectations of their job is all the easier using AI and machine learning. The benefits to organisations that work at scale will be huge.’
How do you think AI can help with personalised learning? Comment below…
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