Ria Symonds
Associate Professor, Faculty of Science
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Biography
Dr Ria Symonds is assistant professor at the University of Nottingham. By background, Ria is a specialist in Mathematics Education and, although a mathematician by trade, she is primarily interested in supporting the teaching and learning of mathematics to non-specialist students. Ria was an Area Coordinator for the Advanced Mathematics Support Programme (AMSP) for 11 years whereby she was involved with teaching, professional development and organisation of large enrichment events for KS4 and KS5 Mathematics. Her involvement with the AMSP has been influential in increasing the uptake of Mathematics at A-level and University level as well as aiding the transition from school to university mathematics courses. More recently, in 2021, Ria was awarded a team Lord Dearing award for her contribution to teaching and learning with the development and roll out of a successful MOOC (massive online open course) to help students prepare for university mathematics. Ria has further developed her skills and knowledge in curriculum planning and development during the 2017 redesign of the A-level curriculum (via AMSP involvement) and, more currently, with the design and implementation of the Data Science Degree Apprenticeship. Ria is an advocate for creating authentic learning and assessment to encourage learner autonomy and, thus, ensuring that the skills and knowledge attained is directly transferable to the workplace.
Teaching Summary
I am interested in teaching mathematics to non-maths specialist students. My past teaching roles have involved teaching on the Engineering/Science Foundation and Natural Sciences courses as well as… read more
I am interested in teaching mathematics to non-maths specialist students. My past teaching roles have involved teaching on the Engineering/Science Foundation and Natural Sciences courses as well as teaching Core Mathematics module content for 1st year Mathematics undergraduates. Since 2021 I have solely spent my time creating and delivering the mathematical taught and assessed content for the Data Science degree apprenticeship.