Is the process of learning a marathon or a sprint?
Professor Barry Hymer, the Chessable Science Consultant, today follows up his original blog post on Chess and the Science of Learning with a new instalment.
Professor Hymer shares with us his thoughts on the art of successful learning. Is it akin to a marathon or a sprint? He backs up the nuts and bolts of his ideas with numerous real-life cases.
Over to you, Professor Hymer…
Success at an Advanced Age
In my previous blog post I asked the question: What do Grandmasters Jonathan Hawkins, Joe Gallagher, and Ye Jiangchuan have in common, and how could the late, great researcher Graham Nuthall have explained this?
As many of you correctly observed, all three of these expert and highly successful chess players achieved their Grandmaster titles at a relatively advanced age. Indeed, as they were in their late 20s or early 30s, this was virtually their dotage compared to the Prags, Gukeshes and Karjakins of this world, after only modest early progress or a late start in the case of Ye Jiangchuan, China’s second GM, who learned chess at 17.
Jonathan’s book details an important part of his learning methods
The late researcher of learning, Graham Nuthall wouldn’t have been surprised by this at all. His research over several decades led him to have profound respect for the slow and incremental processes of learning. This involves frequent opportunities for revisiting newly acquired skills and concepts and close monitoring of understanding and retention. In the well-worn metaphor, learning is a marathon, not a sprint.
Sure there are Bolts aplenty in the chess world. Like maths and music and a small number of other ‘closed systems’, chess rewards an intense early focus and unlike most other
domains of achievement doesn’t need years of accumulated broader life experience for these rewards to reveal themselves. But there are also, sadly, plenty of ‘shot-bolts’ in the chess world. Youngsters with immense early promise who left the game at the point that prodigious early achievement came into contact with the implacable force of consistently high quality opposition.
It’s at that point that Mo Farah-like endurance comes into its own. Additionally, the deep truth of the old Aesop fable reveals itself – slow and steady wins the race. Or to be more accurate, hard work beats talent when talent doesn’t work hard. (When talent works hard, great things can happen.)
So where does this take us in the Chessable world? I would suggest two things.
First, as pioneers in harnessing learning science to the yoke of chess improvement through such processes as the MoveTrainer™ technology and its associated functions, we need to keep on the alert for expanding the reach and zeroing in on the efficiencies of skill acquisition and retention. These are imperatives located in the ‘hard sciences’ of cognitive psychology – and include such valuable, elusive, and related processes as near transfer, meta-cognition, elaboration and self-regulation.
Our friends at the University of Sydney are exploring some rich terrain in this area. We will be supporting them in this research.
Second, we mustn’t rely only on streaks and rubies to keep us keeping on in pursuit of
improvement. We neglect the intrinsic drivers at our peril, and must find ways of valuing the teachings of the ‘soft science’ of the field of ‘positive psychology’ too, and seek to operationalise in chess terms such character strengths and virtues as wise judgement, open-mindedness, perspective, bravery, honesty, diligence etc. We are liaising with a creative researcher, clinical psychologist, and chess enthusiast at the University of California in this area. I will be writing about these qualities in future blog posts too.
Mind the Gap!
As something I’d like to advance as a challenge for the Chessable community and which in many ways bridges both the priorities mentioned above, I will finish this post with the concept of learning demand. See, for example, the work of the educational researchers Leach and Scott: this draws on the idea that there is demonstrably great value (in terms of learning) to be found in analysing what a student already knows before a new unit is taught. Then we compare that knowledge with the knowledge embodied in the intended outcomes of that unit. Learning demand is therefore the identified gap between the student’s prior knowledge and the intended outcomes.
Tied in to this is careful and constant monitoring of new skills, ideas and understandings as the unit (think Chessable course) develops. This will be through such active ingredients as questions, quizzes, tests etc. I would suggest that at Chessable we’re already exceptionally strong at the second part – close and personalised monitoring and review.
However, beyond providing very broad descriptions of who a particular course is pitched at (e.g. beginners, Elo 1800-2000, etc), I’m not sure we’re all that good yet at establishing learning demand prior to beginning work on a new course. I suspect that this would be more pertinent for some courses than others. Courses on openings might be less suited than courses on tactics or strategy development, for instance. I have a hunch there’d be strong payoffs for your learning if we got better at this. Watch this space.
Feedback is Always Welcome
As always, I’d welcome members’ contact with thoughts, ideas and feedback on these posts: email [email protected].
Thank you, Professor Hymer, for your fascinating thoughts on whether learning is a marathon or a sprint. I am sure it will all come as good news to Chessable users of a certain age.
We are looking forward to your next blog post.
A reminder to all readers: Chess Improvement by Barry Hymer and Peter Wells is essential reading.