Dr Bing Ngu
Senior Lecturer, Mathematics Education - Faculty of Humanities, Arts, Social Sciences and Education; School of Education
Phone: +61 2 6773 2328
Dr. Bing H. NGU teaches both undergraduate and postgraduate pre-service Mathematics Education units. Her research interests and expertise include cognition and instruction-based on cognitive load theory, analogical learning, effective and ineffective instructional designs for mathematics learning, and human optimisation. A number of her articles, published in high impact journals, have included complex methodological designs to develop contrasting instructional approaches to improve mathematics learning.
PhD in Education. University of New South Wales, Australia
BSc (Hons) Chemistry with Management Science. Imperial College of Science and Technology, London, UK
International Education Research
Applied Cognitive Psychology
Mathematics Education Research Group Australasia (MERGA)
The Mathematical Association of New South Wales
EDME394 and EDME395: Senior Secondary Mathematics Education
EDME393: Junior Mathematics Education
EDME358: Primary Mathematics Education
Cognitive load theory and mathematics instructions
Analogical learning and mathematics instructions
Instructional designs, optimal best and optimised functioning
Chapter in a Scholarly Book
Ngu, B. H., & Phan, H. P. (2018). Achievement Bests framework, cognitive load theory, and equation solving. In O. B. Cavero (Ed.), New pedagogical challenges in the 21st Century (pp. 287-306). Rijeka, Croatia: InTech Open Science| Open Minds.
Ngu, B. H., & Phan, H. P. (2017). Solving linear equations: Will this post a challenge to elementary pre-service teachers? In K. Patterson (Ed.), Focus on mathematics education research (pp. 117-148). New York, NY: Nova Science Publishers, Inc.
Hine, G., Reaburn, R., Anderson, J., Carmichael, C., Galligan, L., Cavanagh, M., Ngu, B. H., & White, B. (2016). Teaching secondary mathematics (pp. 213-247): Port Melbourne, Cambridge University Press.
Kadir, M. S., Ngu, B. H., & Yeung, A. S. (2015). Element interactivity in secondary school mathematics and science education. In R. V. Nata (Ed.), Progress in education (Vol. 34, pp. 71-98). New York, NY: Nova Science. Invitation.
Refereed Article in a Scholarly Journal
Phan, H. P., Ngu, B. H., & Alrashidi, O. (2018). Contextualised self-beliefs in totality: an integrated framework from a longitudinal perspective. Educational Psychology, 38(4), 411-434. doi: 10.1080/01443410.2017.1356446
Ngu, B. H., Phan, H. P., Yeung, A. S., & Chung, S. F. (2018). Managing element interactivity in equation solving. Educational Psychology Review, 30(1), 255-272. doi: 10.1007/s10648-016-9397-8
Ngu, B. H. (2018). Solution representations of percentage change problems: the pre-service primary teachers’ mathematical thinking and reasoning. International Journal of Mathematical Education in Science and Technology, 1-17. doi: 10.1080/0020739X.2018.1494860
Ngu, B. H., Yeung, A. S., Phan, H. P., Hong, K. S., & Usop, H. (2018). Learning to solve challenging percentage-change problems: A cross-cultural study from a cognitive load perspective. The Journal of Experimental Education, 86(3), 362-385. doi: 10.1080/00220973.2017.1347774
Phan, H. P., Ngu, B. H., & Yeung, A. S. (2017). Achieving optimal best: Instructional efficiency and the use of cognitive load theory in mathematical problem solving. Educational Psychology Review, 29(4), 667-692. doi: 10.1007/s10648-016-9373-3
Ngu, B. H., & Phan, H. P. (2017). Will learning to solve one-step equations pose a challenge to 8th grade students? International Journal of Mathematical Education in Science and Technology, 48(6), 876-894. doi: 10.1080/0020739X.2017.1293856
Ngu, B. H., & Phan, H. P. (2016). Unpacking the complexity of linear equations from a cognitive load theory perspective. Educational Psychology Review, 28, 95-118. doi: 10.1007/s10648-015-9298-2.
Ngu, B. H., Phan, H. P., Hong, K. S., & Usop, H. (2016). Reducing intrinsic cognitive load in percentage change problems: The equation approach. Learning and Individual Differences, 51, 81-90. doi: https://doi.org/10.1016/j.lindif.2016.08.029
Ngu, B. H., & Phan, H. P. (2016). Comparing balance and inverse methods on learning conceptual and procedural knowledge in equation solving: A cognitive load perspective. Pedagogies: An International Journal, 11(1), 63-83. doi: 10.1080/1554480X.2015.1047836
Ngu, B. H., Yeung, S. A., & Phan, H. P (2015). Constructing a coherent problem model to facilitate algebra problem solving in a chemistry context. International Journal of Mathematical Education in Science and Technology, 46(3), 388-403. doi:10.1080/0020739X.2014.979899
Ngu, B. H., Chung, S. F., & Yeung, A. S. (2015). Cognitive load in algebra: element interactivity in solving equations. Educational Psychology, 35(3), 271-293. doi: 10.1080/01443410.2013.878019
Ngu, B., Yeung, A., & Tobias, S. (2014). Cognitive load in percentage change problems: unitary, pictorial, and equation approaches to instruction. Instructional Science, 42(5), 685-713. doi: 10.1007/s11251-014-9309-6
Ngu, B. H., & Yeung, A. S. (2013). Algebra word problem solving approaches in a chemistry context: Equation worked examples versus text editing. The Journal of Mathematical Behavior, 32(2), 197-208. doi: http://dx.doi.org/10.1016/j.jmathb.2013.02.003
Ngu, B. H., & Yeung, A. S. (2012). Fostering analogical transfer: The multiple components approach to algebra word problem solving in a chemistry context. Contemporary Educational Psychology, 37, 14- 32 doi:http://dx.doi.org/10.1016/j.cedpsych.2011.09.001
Ngu, B. H., Mit, E., Shahbodin, F., & Tuovinen, J. E. (2009). Chemistry problem solving instruction: A comparison of three computer-based formats for learning from hierarchical network problem representation. Instructional Science, 37, 21-42. doi: 10.1007/s11251-008-9072-7
Ngu, B. H., Low, R., & Sweller, J. (2002). Text editing in chemistry instruction. Instructional Science, 30, 379-402. doi: 10.1023/a:1019833014623
Research Supervision Experience
Instructional design and cognitive load theory
Academic and non-academic aspects of students’ well-being