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Lots of blogs are declaring the ‘new’ trends in e-learning for 2022. There is nothing truly new in most of these. The difficulty with trends is they frequently draw from the ‘thought-osphere’, rate than from emergent practice. One of these trends predicted for 2022 is ‘adaptive learning’.

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This ‘trend’ has been around for well over a decade and still cannot gain significant traction. Few would disagree that learning should be personalised to the largest degree possible to ensure motivation and relevance for the learner. Adaptive learning is the notion that we can tailor learning for the individual based on past performance and the ultimate direction. A little like the way an intelligent GPS navigation system for your car can suggest alternative routes when you take a wrong turn.

Educators have long implemented adaptive learning strategies in face-to-face contexts, usually as differentiated teaching practices. Teachers will tell you that for this strategy to be effective, class sizes need to be small and that you need to know your students at a human level. Knowing not just that they struggle with numerical concepts, but also that they enjoy music, or sports, so that we can pose exemplars as problems in a language that is meaningful to that learner. Differentiated teaching is highly personalised.

In contrast, adaptive learning systems, which are based on the interactions individuals have with computer based learning activities, simply cannot consider the societal influences, the personal likes and dislikes, of the individual. Sophisticated adaptive systems allow the learner to be presented with alternative phrasing of a problem if they appear to misunderstand instructions, or to be presented them with simpler versions of tasks if the initial one appears to be too difficult.

Adaptive systems are limited to the domain of knowledge acquisition, learning stuff, and some lower cognitive skill development. Essentially, adaptive learning is an old-style computer-based training (CBT) course on steroids. Facts and cognitive processes are important, and delivering up examples that are appropriately positioned to stretch the learner is a good thing. We should all understand, however, that the technology lags way behind the aspirations of teachers. It is a far cry from personalising learning.

Personalised learning is best enabled by situating learning experiences within the social context in which the learner lives and works. Allowing the learner to design their own responses to assessment tasks, to generate personalised evidence of their learning and relate their learning to their real lives. True personalised learning is essential for four domains of educational objectives, affective, psychomotor, interpersonal and the intrapersonal (meta-cognitive), for the factual knowledge ‘stuff’ and some cognitive skills there are, or may be, adaptive learning systems.

Unfortunately for budget-holders and institutional leaders, personalised learning requires a staff-student ratio that defies current budgets and, my particular interest, carefully crafted curriculum, programme and course design. For some, it appears to be worth investing in ‘automated’ learning systems, sold on the promise of responding directly to the student’s needs. Systems hyped by the vendors frequently underrepresented the investment needed in designing alternative branching scenarios and associated questions. Most vendors promise banks of questions based on relatively simple algorithms. Until computing power is significantly increased, answers and questions can be truly automated through AI systems, and systems can draw accurate student profiles based on social media and shared data (a worrying possibility for many) adaptive systems will remain a limited tool for specific contexts.

These contexts include mathematics and most ‘hard’ sciences. Where there is a required base of factual knowledge that is widely regarded as uncontested, adaptive learning systems can provide a marginally more engaging version of rote learning. It may even provide some ability to prompt the learner to transfer knowledge from one context to another beyond pure memorisation. I contest its applicability is still limited to the cognitive domain.

Still, the hyping of adaptive systems continues and they remain on most 2022 trends list. Clearly, one trend that I confidently predict for 2022 is that technological determinism, the concept that technology is intimately related to our social development, will continue to feature in the ‘trends’ blogosphere.

Photo by Ishan @seefromthesky on Unsplash

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