EPJ Data Sci. (2014) 3: 36
https://doi.org/10.1140/epjds/s13688-014-0034-9

Regular article

Complex network analysis of teaching practices

¹ Interdisciplinary Graduate School, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
² Complexity Institute, Nanyang Technological University, 60 Nanyang View, Singapore, 639673, Singapore
³ Office of Education Research, National Institute of Education, 1 Nanyang Walk, Singapore, 637616, Singapore
⁴ School of Education, Faculty of Humanities and Social Sciences, University of Queensland, Brisbane, QLD, 4072, Australia
⁵ School of Physical & Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore, 637371, Singapore

^* e-mail: gohw0047@ntu.edu.sg

Received: 31 July 2014
Accepted: 10 December 2014
Published online: 30 December 2014

Abstract

The application of functional analysis to infer networks in large datasets is potentially helpful to experimenters in various fields. In this paper, we develop a technique to construct networks of statistically significant transitions between variable pairs from a high-dimensional and multiscale dataset of teaching practices observed in Grade 5 and Grade 9 Mathematics classes obtained by the National Institute of Education in Singapore. From the Minimum Spanning Trees (MST) and Planar Maximally Filtered Graphs (PMFG) of the transition networks, we establish that teaching knowledge as truth and teacher-dominated talking serve as hubs for teaching practices in Singapore. These practices reflect a transmissionist model of teaching and learning. We also identify complex teacher-student-teacher-student interaction sequences of teaching practices that are over-represented in the data.