Resources from Sessions

Abstract: The Education Endowment Foundation (EEF) published a review on cognitive science approaches in 2021, which suggests that approaches used to manage cognitive load (i.e., worked examples) are robust but dominate in mathematics and lack of enough classroom-based evidence. For this talk, I will begin to introduce human cognitive architecture, followed by discussing the example first approach and problem first approach with classroom-based evidence and their practical implications for mathematics learning. 

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Slides

Abstract: Everyone thinks problem solving is important, but what is it, and can it be taught? I will draw on my experiences at King's College London Mathematics School and Axiom Maths to attempt a definition, and use a little cognitive science sprinkled with a lot of experience to suggest ways in which we can enable undergraduates to solve mathematical problems.

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Slides:

Abstract: The problem-solving skills which mathematics graduates possess are highly sought after by employers but the didactic nature of some teaching at undergraduate level can leave graduates lacking in experiences of utilising and evidencing these skills. I will discuss how an explicit embedding approach can enable students to acknowledge this development and build confidence. I will cover my experiences bringing employers into the curriculum and what this has taught students (and employers) about the differences between solving problems in higher education and tackling novel problems in business / industry.  

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Slides:

Abstract: MATH11221 Mathematical Problem Solving is a level 1, semester 1 unit taken by all single honours maths students at the University of Manchester. In this session I will discuss the purpose of this unit, its intended learning outcomes and how the sessions are structured. I will outline the administrative and organisational challenges involved in running this group project based unit and how we are attempting to address them.

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Slides:

Abstract: We set out to create a new level 11 course for MSc students or final year UG students on an Applied Mathematics degree that introduced them to the problem-solving challenges involved in Industrial Mathematics, namely mathematical analysis and modelling together with computational methods in a real world setting. This talk will give practical details of how we delivered a course suitable for up to 50 students of mixed backgrounds, met our Learning Objectives and developed our students problem-solving skills in a real-world setting.

Recording: Click here

Slides:

Abstract: This will be an interactive session and discursive session where we will aim to pull together the ideas we have heard during the day and draw out actions that we can implement within our teaching contexts.

Image of brainstorm from the session: