Associate Professor Bing Ngu

Associate Professor in Mathematics Education , Mathematics education - Faculty of Humanities, Arts, Social Sciences and Education; School of Education

Bing Ngu

Phone: +61 2 6773 2328

Email: bngu@une.edu.au

Building: E011, 115

Biography

Dr. Ngu has extensive experience teaching secondary mathematics and science both in Australia and internationally. Over the course of her career, she has identified key challenges in mathematics education, with a particular emphasis on algebra instruction. This focus has shaped her current research, which explores instructional design informed by cognitive load theory, learning by analogy, and learning by comparison. Her work aims to improve students' understanding of linear equations, percentage problems, and trigonometry, particularly in relation to algebraic transformation skills.

A key aspect of her research is its cross-cultural dimension, as she explores cognitive processes and mathematics instruction in diverse educational settings. She collaborates with scholars from Australia, China, Malaysia, Singapore and Taiwan to develop a theoretical understanding of effective student learning, including cognitive processes, motivation, subjective well-being, and psychological factors that optimize learning outcomes.

Dr. Ngu is committed to translating her findings into practical applications for educators. She has shared her research with local teachers in Armidale as well as with international educators, such as those in Malaysia, as part of their professional development. Her research has also played a crucial role in the development of high-quality undergraduate and postgraduate pre-service teacher education programs as well as Master of Neuroscience and Education program at the University of New England (UNE), further demonstrating her dedication to advancing the field of mathematics education and educational psychology.

In addition to focusing on cognitive load theory and optimal best practices (e.g., Ngu, Phan, Hasbee, & Usop, 2023), recently,  Dr Ngu has collaborated extensively with Professor Huy P. Phan on research in the area of life and death education. Our work in this field explores critical themes surrounding existential understanding and personal philosophization, as reflected in recent publications (e.g., Phan, Ngu, Hsu, & Chen, 2023, 2024a, 2024b).

Dr Ngu’s teaching and research contributions, both individually and in collaboration with Professor Huy P. Phan and others, have elevated UNE’s ERA profile in Educational Psychology to an internationally recognized level of excellence (e.g., ERA 4), comparable to leading institutions. Moreover, Dr Ngu’s leadership in teaching and research, demonstrated through single-author and lead-author publications in high-quality journals, has allowed her to provide valuable mentorship to early career researchers and students from diverse regions, including Bhutan, China, Indonesia, Malaysia, Saudi Arabia, Singapore and Taiwan.

Qualifications

BSc (Chemistry with Management Science) (Hons) (Imperial College of Science and Technology, UK)

Ph.D. in Education (University of New South Wales, Australia)

Teaching Areas

Dr Ngu teaches a range of mathematics education units, including those for junior and senior secondary levels, as well as master level on educational psychology.

  • EDME392 (Junior Secondary Mathematics Education)
  • EDME393 (Junior Secondary Mathematics Education)
  • EDME394 (Senior Secondary Mathematics Education)
  • EDME395 (Senior Secondary Mathematics Education)
  • EDLT516 (Instructional Designs and Cognitive Load Theories of Learning)

Research Interests

  • Building on John Sweller’s cognitive load theory, Dr Ngu has developed my own theoretical framework for understanding 'element interactivity', which not only addresses the complexity of learning materials but also evaluates the relative efficiency of instructional approaches.
  • Developing new conceptual insights to enhance mathematics education and improve student learning experiences, particularly through the lens of element interactivity to assess cognitive load during the learning process.
  • Comparing instructional approaches informed by the principles of cognitive load theory, learning by analogy, and learning by comparison, with a focus on their effectiveness from an element interactivity perspective.
  • Contributing to new theories in educational psychology, such as the theory of human optimization, which seeks to explain students' experiences of ‘optimal best’ learning in mathematics.
  • Investigating instructional efficiency, cognitive load, prior knowledge, learner expertise, and beliefs about optimal learning practices.
  • Examining the relationship between cognitive load, element interactivity, instructional strategies, and cross-cultural mathematics education.
  • Exploring the alignment between varying levels of instructional effectiveness (cognitive dimension) and motivational beliefs (non-cognitive dimension), and how this impacts student learning.
  • Research in the area of life and death education.
  • Expertise in quantitative research methodologies, including randomized experimental studies conducted in intact classroom settings.

Research Supervision Experience

  • Instructional Design and Cognitive Load Theory
  • Academic and Non-Academic Aspects of Student Well-being
  • Developmental Psychology
  • Quantitative Research Methodologies
  • Mathematics Education and the Achievement of Optimal Best Practice

Publications

Selected publications

Dr Ngu’s full list of publications: https://rune.une.edu.au/web/simple-search?location=researcherprofiles&query=Bing+Ngu&rpp=50&sort_by=score&order=desc

Book Chapters

  1. Ngu, B. H., & Phan, H. P. (2020). An Examination of pre-Service teachers’ content knowledge on linear equations: A cross-cultural study. In R. V. Nata (Ed.), Progress in education (Vol. 64, pp. 1-34). Nova Science Publishers, Inc..
  2. Ngu, B., Phan, H., Wang, H.-W., Shih, J.-H., Shi, S.-Y., & Lin, R.-Y. (2019). Best practice in mathematics learning: A theoretical-conceptual discussion for consideration. In R. V. Nata (Ed.), Progress in Education (Vol. 55, pp. 79 -112). New York, NY: Nova Science Publishers, Inc.
  3. 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.

Journal Articles

  1. Ngu, B. H., Phan, H. P., Usop, H., & Anding, P. N. (2024). Enhancing problem-solving skills for word problems: Impact of diagram and learner expertise. The Journal of Experimental Education, 1-18. https://doi.org/10.1080/00220973.2024.2394956. https://doi.org/10.1080/00220973.2024.2394956
  2. Ngu, B. H., & Phan, H. P. (2024). Instructional approach and acquisition of mathematical proficiency: Theoretical insights from learning by comparison and cognitive load theory. Asian Journal for Mathematics Education. https://doi.org/10.1177/27527263241266765
  3. Ngu, B. H., & Phan, H. P. (2023). Differential instructional effectiveness: overcoming the challenge of learning to solve trigonometry problems that involved algebraic transformation skills. European journal of psychology of education, 38(4), 1505-1525. https://doi.org/10.1007/s10212-02.
  4. Ngu, B. H., Phan, H. P., Usop, H., & Hong, K. S. (2023). Instructional efficiency: The role of prior knowledge and cognitive load. Applied Cognitive Psychology, 37(6), 1223-1237. https://doi.org/10.1002/acp.4117.
  5. Ngu, B. H., & Phan, H. P. (2022). Advancing the study of solving linear equations with negative pronumerals: A smarter way from a cognitive load perspective. PLOS One, 17(3), e0265547.
  6. Ngu, B. H., & Phan, H. P. (2022). Developing problem-solving expertise for word problems. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.725280
  7. Ngu, B. H., & Phan, H. P. (2021). Learning linear equations: capitalizing on cognitive load theory and learning by analogy. International Journal of Mathematical Education in Science and Technology, 1-17. https://doi.org/10.1080/0020739X.2021.1902007
  8. Ngu, B. H., & Phan, H. P. (2020). Learning to solve trigonometry problems that involve algebraic transformation skills via learning by analogy and learning by comparison. Frontiers in Psychology, 11(2590). https://doi.org/10.3389/fpsyg.2020.558773
  9. Phan, H. P., Ngu, B. H., & Yeung, A. S. (2019). Optimization: In-depth examination and proposition. Frontiers in Psychology, 10(1398). doi:10.3389/fpsyg.2019.01398
  10. 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. doi: 10.1080/0020973.2017.134774
  11. Ngu, B. H., Phan, H. P., Yeung, A. S., & Chung, S. F. (2018). Managing element interactivity in equation solving. Educational Psychology Review, 1-18. doi: 10.1007/s10648-016-9397-8.
  12. 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
  13. Ngu, B. H. and H. P. Phan (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

Books

  1. Phan, H. P., & Ngu, B. H. (2019). Teaching, Learning and Psychology. Docklands, Melbourne: Oxford University Press.
  2. Hine, G., et al. (2021). Teaching Secondary Mathematics, Port Melbourne, Cambridge University Press.

Memberships

Editorial Board member for PloS One, which is a multidisciplinary journal.

Consultancy Interests

  • Learning theories, instructional designs and mathematics education
  • Appropriate instructional designs and optimal best achievement