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Promoting Deep Learning in Mathematics: Opportunities for Preservice Teachers to Identify and Re-Imagine Their Beliefs
Book chapter

Promoting Deep Learning in Mathematics: Opportunities for Preservice Teachers to Identify and Re-Imagine Their Beliefs

Karen Skilling
Deep Learning and Subject Teaching: Approaches to Disciplinary Literacy, pp.90-110
Routledge, 1st
2027
DOI: https://doi.org/10.4324/9781003585022-6
Appears in  Recent Faculty of Education Publications

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Abstract

Initial teacher training courses provide opportunities for preservice teachers (PSTs) to critically examine and reflect on theoretical and pedagogical aspects of teaching to identify and potentially re-imagine their beliefs about learning and teaching. This is particularly relevant when teaching mathematics because notions of deep learning in mathematics tend to focus on relationships with content, understanding, and finding meaning, in contrast to surface approaches that tend to emphasise memorisation and the application of procedures. However, such dichotomous views can be too simplistic and tend to overlook the facilitating role of the teacher for planning and directing learning experiences. Drawing from an array of literature, six characteristics of deep learning were identified as understanding the integration of knowledge and conceptual systems, including the relationship between content; knowing how concepts can be applied meaningfully; making connections with pre-existing knowledge to form new knowledge; critical examination of the logic of an argument, including using self-regulatory skills and metacognitive processes to interrogate solutions and solutions generated by others; using dialogue and communication to reason and question; and understanding how an individual learns (cognitive and non-cognitive factors). Developing an awareness of the ways in which teachers can shape their future students' learning experiences is a crucial aspect of initial teacher education. This chapter presents examples of how PSTs identify and explain their understandings for promoting deep learning in two teaching situations. Two image-based vignettes of fictitious but realistic teaching situations were constructed to represent practice, and PSTs were asked to respond to questions about the mathematics activities, which were connected to characteristics of deep learning.

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