Thursday, July 7, 2016

How to do Adaptive Learning Right

I was fortunate enough to receive a blog-post with the above title from the educationalist and blogger Larry Cuban (

I love the title from the authors Keith Devlin and Randy Weiner.  After 20-plus years of working in classrooms worldwide, I still am no further towards discovering a “right” way, either for myself or my learners.  For me educational practice is a continual process of trial and error – more error than trial, to be honest.

Both the authors work in the edtech industry, and they describe the creation of what they term an “adaptive engine,” to supply players of their launch product, Wuzzit Trouble, with challenges adjusted to individual ability levels.  Based on research conducted by mathematics professionals, they created something that was designed to make education not a process of rote-learning, but an “experience,” one that takes a real-world mathematics problem and invites users to solve it.  Learners have to acquire two abilities as a result – they have to develop problem-solving knowledges, as well as acquiring mathematical thinking .

More importantly the engine encourages what the authors term adaptive thinking, rendering learners in full control of how to move forward and what degree of success they should accept.  Through such means they develop the 21st century skills of holistic thinking and problem solving.

A well-designed technology should not only help learners to explore problems but provide information on how their hypotheses varied from their actual experience and how they might revise their strategy accordingly.  Mathematics should be something learned through practical experience; through a method that breaks through what they term the “symbol barrier,” and provides instead a range of tools that individual learners can adapt for themselves to plot their own course of study.

I do not know enough about the edtech industry to make any comment on the efficacy of the materials discussed.   Mathematics was never my strongest subject at school; I could never get used to algebra, and differentiation and integration largely remained a closed book.

But what I would ask is this: although I am in favor of any edtech scheme that advances the cause of adaptive learning, surely we need people to ensure its successful operation?  Not just technicians and/or experts to enhance learner experience of that material, but coaches and other educators to provide support and counsel whenever necessary?  Learners can discover solutions for themselves, I grant you; but they do need to talk to someone to sustain their morale as well as offering pointers for future mathematical (or any educational) research.

Online communication offers a valuable tool – I use it frequently myself through various forms of email and social media – but I still believe that there is a place for human interaction that stand-alone technology cannot provide.  Adaptive learning is not just subject-related; it requires learners to understand something about the world around them; how people react to different situations, both verbally as well as nonverbally.  Sometimes I find that the best “classes” – if they can be described as such – take place in caf├ęs or restaurants, where educators and learners alike learn how to observe one another’s body language as well as the nuances of stress and tone in their spoken language.  We also learn to look at others, and try to infer from their body-language what they might be thinking.  Such processes are the bread and butter of all creative writers.

Our learners might not be creative writers in embryo (they might enter totally different professions), but it is essential that they learn something about the worlds they inhabit, so that they can refine their adaptive processes.  Maybe I’m old-fashioned, a product of a pre-edtech era when we did a lot of our classes sitting outside on the grass; but over the last few years or so I have come to realize the importance of looking and listening to people as the basis of all forms of learning.  We might not find any answers to our questions, but it’s worthwhile hypothesizing.

Laurence Raw

7 July 2016

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