Why don’t students use effective learning strategies?

I attended a TILE (‎@TILEnetwork) talk with the above title yesterday.

Dr Flavia Shechtman-Belham (Seneca Learning) spoke about some of the most effective learning strategies – Dual Coding, Spacing and Interleaving, and Retrieval Practice. She also discussed reasons why students don’t tend to use these  – they are perceived to be ‘hard work’, or unnecessary, (students think their current methods work), etc. The message I took away from this excellent talk was that pointing my students to effective strategies for learning is my responsibility.

Actually no, my responsibility goes further than that. The published evidence Flavia discussed suggests that students cannot easily be persuaded to use these strategies. Chatting with a colleague who made earnest efforts in this direction during a course he delivered last year reinforced that impression. A full-on campaign in one course seems likely to single out that course in students’ minds, as awkward and difficult. So my responsibility might be not only to inform – but to nudge students towards the best strategies.

Nudges have a chance of working.  I feel that an approach mixing evidence from the literature (in small doses) with some reinforcement, in occasional short practical sessions, could provide the right environment for students to decide to adopt (some of) these strategies for themselves. My idea is to intersperse such sessions in occasional 15-20 minute bursts, into ‘regular’ maths workshop hours. These will take a little planning.

Maybe this will help – but maybe I would then single out my teaching as awkward and difficult! An ideal approach would then involve a coordinated effort involving other colleagues, perhaps covering the teaching across a whole level.

What makes examples exemplary for students? – John Mason

Mathematics Division Seminar

19 February 2018

Prof Mason has been teaching university mathematics for 40 years and during this time he has extensively investigated how to teach and learn mathematics effectively. He led the Open University’s Centre for Mathematics Education for fifteen years and has published numerous useful textbooks about maths educations that have become standard texts for students and lecturers.

This talk examined many of the ways in which the examples and ‘model solutions’ we provide to students might be more or less helpful to them, perhaps not working in the way that we expect! A number of techniques for engaging students within a session were discussed and even used during the talk.

 

Using Cognitive Science to Teach Mathematics in Higher Education – Carolina Kuepper-Tetzel

Mathematics Division Seminar

16 October 2017

Abstract:

Cognitive Science has revealed a number of learning and memory
phenomena that have direct, practical implications for learning and teaching.
I will highlight the most promising strategies alongside their original research
findings and will elaborate on ways on how to implement these in large
lectures and small seminars in mathematics. The talk will conclude with an
opportunity discuss the feasibility of implementation and ways to overcome
potential obstacles.

Automatic Assessment of Reasoning by Equivalence – Chris Sangwin

Mathematics Division seminar

Monday 27 February 2017

Abstract:

Deductive reasoning and proof is one of the hallmarks of mathematics, and is an important factor in distinguishing mathematics from empirical sciences. Fluency in calculation, including symbolic manipulation in algebra and calculus, sit alongside deduction, reasoning and problem solving. “Core pure mathematics” is that essential amalgam which is universally studied by all mathematics, science and engineering students. It starts with traditional algebra, trigonometry and calculus, culminating with De Moivre’s theorem and its consequences while stopping short of real analysis. Presentations of core pure mathematics often contain little explicit “proof” beyond formulaic proof by induction, but it is where proof starts for pure mathematicians.  Core pure mathematics contains a key activity “reasoning by equivalence”. This is reasoning and is key in many of the deductions at this level, but it is very close to a calculation. Indeed, in many situations it can be treated formally as a calculation. This talk will look at the interplay between calculation and reasoning, with a focus on automatic assessment. To what extent can we automate the assessment of reasoning now, and where are the limits of automatic assessment in the future?