Deep Learning as Constructed in Mathematics Teachers’ Written Discourses

This study explores the notion of deep learning as constructed in the discourses of practicing mathematics teachers. Analyses of data from written texts show that the teachers tend to conceptualise deep learning in terms of two broad categories: students’ deep learning and the work of teaching for deep learning. In both categories, students’ previous knowledge or background knowledge, students’ thinking and their understanding, interdisciplinarity and relations to daily life are emphasised. Related to the work of mathematics teaching for deep learning, variation in mediating tools, variation in approaches to teaching, the learning objective for a lesson and the importance of applying knowledge are emphasised. Possible implications from these findings are discussed.