THE WORK OF TEACHING AND THE CHALLENGE OF TEACHER EDUCATION

Biosketch: Deborah Loewenberg Ball is the William H. Payne Collegiate Professor of education at the University of Michigan, an Arthur F. Thurnau Professor, a research professor in the Institute for Social Research, and the director of TeachingWorks. She taught elementary school for over 15 years and continues teaching children every summer. Ball’s research focuses on the practice of teaching, using elementary mathematics as a critical context for investigating the challenges of building relationships with children and helping children develop agency and understanding, and on leveraging the power of teaching to disrupt racism, marginalization, and inequity. Ball is an expert on teacher education, and her current work centres on ways to improve the quality of beginning teaching to advance justice. Ball has authored more than 150 publications, and her research has been recognized with several awards and honours. She served as president of the American Educational Research Association from 2017 to 2018, as a member of the National Science Board from 2013 to 2018, and as dean of the University of Michigan School of Education from 2005 to 2016.

BRAIN NETWORKS AND GRAPH THEORY

Abstract: The last two decades have witnessed a new theme in neuroscience where neural assemblies in the brain are visualized as a network. They are mathematically conceptualized as a directed graph with the nodes being either neurons or regions of the brain and the edge connectivity matrix representing communication pathways between them.  This visualization has proved remarkably useful in both localization and distribution of neuronal signal generation and transmission within the brain when studied with tools such as neuroimaging and electroencephalography.

In recent joint work with neuroscientist A.N. Prasad, we have introduced the Markov matrix P (different from the adjacency matrix) of the brain network and related the spectral theory of the matrix P to the functional connectivity of this network.  In this way, we have given a method to identify  “brain hubs” that are often implicated in various brain disorders such as epilepsy.  This talk will give an introduction to this new and exciting application of graph theory to neuroscience and is targeted at a general mathematical audience.No deep knowledge of graph theory or neuroscience will be assumed.

Biosketch: M Ram Murty is an Indo-Canadian mathematician at Queen’s University, where he holds a Queen’s Research Chair in mathematics. He received his PhD in 1980 from the Massachusetts Institute of Technology and was a faculty member at McGill’s University, Montreal, from 1982 to 1996, prior to joining Queen’s University. Ram Murty is a number theorist who works on modular forms, elliptic curves and sieve theory. He is the author of 12 textbooks and research monographs in mathematics and one on Indian Philosophy. Murty received the Coxeter-James Prize in 1988. He was elected a Fellow of the Royal Society of Canada in 1990, was elected to the Indian National Science Academy (INSA) in 2008 and became a fellow of the American
Mathematical Society in 2012.

Speaker: Weng Kin Ho
National Institute of Education, Nanyang Technological University, Singapore

COMPUTATION AS A BIG IDEA IN MATHEMATICS

Abstract: Randall Charles defines a Big Idea in Mathematics as “a statement of an idea central to the learning of mathematics, one that links numerous mathematical understandings into a coherent whole”. Therein, Charles listed a total of 21 Big Ideas – acknowledging the impossibility that all mathematicians and mathematics educators can agree on these – with the hope that they can be a starting point to initiate conversations. In this talk, we propose that ‘Computation’ can be added to this list of big ideas in mathematics and give compelling reasons to support our proposal. Additionally, we describe some implications of such inclusion with particular emphasis on teaching and learning of mathematics in schools.

Biosketch: Weng Kin Ho received his PhD in Computer Science from The University of Birmingham (UK) in 2006. His doctoral thesis proposed an operational domain theory for sequential, functional programming languages. His research interests include domain theory, general topology, programming language semantics, exact real arithmetic, category theory, algebra, real analysis and applications of topology in computation theory.  Notably, he solved the open problem that questions the existence of a purely operationally-based proof for the well-known minimal invariance theorem of nested recursive types in Fixed Point Calculus and disproved the famous Ho-Zhao conjecture.  He also has a keen interest in mathematics education, particularly in the area of computational thinking, use of technology in mathematics education, video technology and problem-solving.  He has recently published in several education journals on leveraging computational thinking in teaching and learning mathematics.

Panel discussion on

Recovery and Resumption of Mathematics Learning in a Post- Pandemic Classroom

The absence of the offline classroom due to the pandemic and the resulting lockdown affected teaching-learning adversely during the last two years (March 2022 to February 2022). As we move back to the offline classroom, both students and teachers seem to be struggling , not only to recover from the learning loss during the lockdown period, but also in resuming the vibrant interactive learning in the classroom. The pandemic did not just cause a loss in content coverage, it has perhaps had a serious impact on students’ ability to negotiate a regular classroom. In this session, we aim to deliberate on the following issues:

• Challenges of offline classes after a long period in online mode
• Effective mechanisms that will help students and teachers cope with the challenges
• Resources that will help the teachers to ensure equitable access for learners
• Role of digital technology as we resume offline instruction

Panel discussion on

Change in the Education Policy Landscape

The 2020 annual conference of the MTA(I) included a panel discussion on the then recently-released National Education Policy and its implications for mathematics education at both school and university levels. In the two years since then, several initiatives based on NEP have been implemented or drafted in detail, such as the Academic Bank of Credit, the Four Year Undergraduate Programme, the Higher Education Qualifications Framework and the Common University Entrance Test. In 2022, we aim to take stock of how these developments impact teachers and teaching, in general as well as specifically for mathematics, in school and in university.