Bing Ngu

Senior Lecturer in Mathematics Education

University of New England

Australia

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About

Dr. Bing Ngu is a Senior Lecturer in Mathematics Education at the University of New England, Australia. His research interests include cognitive load theory, the effectiveness of instructional approaches in learning mathematics, and enhancing problem-solving skills. Recent publications examine various aspects of mathematical proficiency, particularly in areas such as linear equations and trigonometry, while also exploring the implications for pre-service teacher education.

Articles (16)

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2021

Collaborators (2)

Antonio Granero-Gallegos

Universidad de Almería

SPAIN

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Huy Phan

Professor, Educational Psychology, Teaching and Learning

University of New England

AUSTRALIA

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Bing Ngu

Research Interests

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Articles (16)

Can Correct and Incorrect Worked Examples Supersede Worked Examples and Problem-Solving on Learning Linear Equations? An Examination from Cognitive Load and Motivation Perspectives

Enhancing Problem-Solving Skills for Word Problems: Impact of Diagram and Learner Expertise

Instructional approach and acquisition of mathematical proficiency: Theoretical insights from learning by comparison and cognitive load theory

Instructional efficiency: The role of prior knowledge and cognitive load

Differential instructional effectiveness: overcoming the challenge of learning to solve trigonometry problems that involved algebraic transformation skills

Advancing the study of levels of best practice pre-service teacher education students from Spain: Associations with both positive and negative achievement-related experiences

Is the inverse method more effective than the balance method on learning linear equations? A cross-cultural experimental study between Australia and Malaysia

Advancing the study of life and death education: Theoretical framework and research inquiries for further development

Advancing the Study of “Goals of Best Practice”: Toward Achieving Optimal Best – Educational Implications to Developments in Flow Research and Positive Optimal Psychology

Advancing the study of solving linear equations with negative pronumerals: A smarter way from a cognitive load perspective

Learning linear equations: capitalizing on cognitive load theory and learning by analogy

Empirical validation of the psychological concept of a perceived feeling of ‘energy’: Advancement into the study of positive psychology

Interrelationships Between Psychosocial, Motivational, and Psychological Processes for Effective Learning: A Structural Equation Modeling Study

A Perceived Zone of Certainty and Uncertainty: Propositions for Research Development

A Case for Cognitive Entrenchment: To Achieve Optimal Best, Taking Into Account the Importance of Perceived Optimal Efficiency and Cognitive Load Imposition

Optimization: an attempt to establish empirical evidence for theoretical and practical purposes

Collaborators (2)

Antonio Granero-Gallegos

Huy Phan

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