I had a colleague who believed that everything could and should be optimised. He had a diet Linear Program which he used to plan his meals to provide optimal nutrition. Unfortunately the Linear Program didn’t seem to have a constraint to ensure the food was palatable, and he would eat combinations like sardines, broccoli and sunflower seeds for lunch. My colleague also believed that there must be an optimal way to teach, that would maximise the learning outcome. I am doubtful that there is such a thing, bearing in mind the diversity of human experience. However I like the idea of imagining the best possible method, unconstrained by class-size, resources or instructor time and competence.
I am currently developing on-line resources to help people learn statistics, and though I do not presume to claim that they will be optimal, I’d like for them to be really, really good. On-line provision can never do some of the things that human interaction can do, but by the same token, on-line materials are infinitely patient and calm, and should always be correct.
The problem with education and learning is that it involves people. People are not all the same and what works for one person may not work with another. Circumstances change. And there is the problem of motivation. In order for students to learn, they must engage with the material for an extended length of time. This requires motivation. Some students are intrinsically motivated, and will learn for the sheer joy of it. This intrinsic motivation is not common in operations research, and even less common in statistics. Surprisingly, most of our students are not enrolled in a statistics class for the intrinsic rewards it brings and the excitement that the subject engenders.
When I was in my second year of high school there was a city-wide mathematics competition, which included a class project. I decided our class should enter and set about running a statistical survey on, of all things, sausages. My maths teacher gave me the resources I needed and ran off the questionnaires on the Banda machine (mmm methylated spirits!) (Showing my age here, I know! – at least I was a student and not the teacher in this story). We had about three or four pages of questionnaire about what types of sausages people liked, how often they ate them, what they ate them with and other questions that I can’t remember. Each girl took home some of the questionnaires and had friends and family fill them out. (No informed consent was needed in those days). My friends and I counted the responses by hand and gave the summary values to class members to draw barcharts and (I’m embarrassed to admit) pie charts. An artistic friend drew a really great illustration in the centre, and we stuck all our graphs onto a large piece of paper – about 2m square. We didn’t win a prize, but we did get an honourable mention, and I got my photo in the school magazine. I do remember learning that our way of counting up did not allow for multivariate analysis. I would have liked to look at the relationships between our variables, but it would have taken too long to recount everything.
The optimal learning method should involve small groups of learners. As people discuss ideas they develop their own understanding. There needs to be an expert around who can help them when they get stuck and point them in the right direction. This sounds like the Oxbridge model, where students meet with tutors in very small groups and then go off for a week to do their learning. A week might be a bit too long in this instance.
So my unconstrained optimal solution involves small groups of 2 or 3 students being given projects, preferably related to their personal interests. They grapple with this project, while maintaining contact with a helpful and all-knowing tutor. Resources are available for analysis and for reference. The projects are carefully selected to provide different issues to help students develop the required competencies. The students present their project results to other students. Sounds wonderful. And expensive.
We examine the aspects that make this setup ideal, and try to replicate them in other ways. In particular we can think how technology can be used to enable this kind of learning. In another post I will examine how Coursera has approached teaching statistics, and see what is done well and how that can be improved.