MXN423 Advanced Mathematical Modelling

Unit Outline: Semester 1 2026, Gardens Point, Internal

Overview

This unit provides a framework for you to undertake advanced level coursework in mathematical modelling and enables you to acquire advanced knowledge and skills in problem formulation, problem solving, critical thinking, and communication in an advanced mathematical modelling context. It links to studies in applied mathematics and modelling work previously undertaken in an undergraduate mathematics degree and can link forwards to the kind of mathematical modelling employed in industry and in academic research. This advanced unit is also designed to complement a research project in applied and/or computational mathematics and aims to prepare you for further research studies at Masters or PhD level or a career in industry.

Learning Outcomes

On successful completion of this unit you will be able to:

1. Formulate and develop an appropriate mathematical model for a problem under investigation, and appreciate the strengths and weaknesses of a given mathematical model.
2. Analyse and solve a given mathematical model using appropriate analytical and numerical techniques.
3. Interpret solutions to mathematical equations in terms of the original application under investigation.
4. Demonstrate independence and self-reliance in retrieving and evaluating relevant information and in advancing your learning.

Content

Learning Approaches

This unit involves a combination of lectures and reading material where theory and concepts will be presented, and where you will be exposed to the processes required to solve problems using the methods of this unit.

The teaching and learning approaches will foster both acquisition of new knowledge at an advanced level and development of your skills. The material presented will be context-based utilising examples from a range of mathematical and real-world applications. The emphasis will be on learning by doing, learning in groups and as individuals, written and oral communication, and developing skills and attitudes to promote life-long learning.

You are expected to work not only in any lecture/workshop session times allocated, but also in your own private study time. That is, you are expected to consolidate the material presented by working through a wide variety of exercises, problems and online learning activities in your own time.

Feedback on Learning and Assessment

Feedback will be provided by academic staff through summative assessment tasks and through formative feedback during timetabled classes. You will also have opportunities for peer-to-peer learning and self-reflection to support your learning and skills development.

Assessment

Unit Grading Scheme

7- point scale

Assessment Tasks

Assessment: Problem Solving Task

You will submit several small tasks that give you the opportunity to apply the mathematical modelling skills you have developed in this unit.

The use of generative artificial intelligence (GenAI) tools is prohibited during this assessment.

This assignment is eligible for the 48-hour late submission period and assignment extensions.

Assessment: Project (applied)

This authentic assessment item reflects two facets of applied mathematicians, namely; 1) the process of turning a real-world problem arising from a complex system into an adequate mathematical description; and 2) the grasp of advanced mathematical and computational techniques that enable complex systems to be modelled, simulated, and analysed with an accuracy and level of detail suited to the investigation. You will be confronted with a real-world problem and be expected to demonstrate your capability to model and solve the problem. Your approach and results will be communicated via a technical report and presentation, consistent with the style applied mathematicians deliver in research and industry.

The use of generative artificial intelligence (GenAI) tools is prohibited during this assessment.

This assignment is eligible for the 48-hour late submission period and assignment extensions.

Academic Integrity

Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.

The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.

You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.

Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.

Resources

Risk Assessment Statement

There are no extraordinary risks associated with the classroom/lecture activities in this unit.

Course Learning Outcomes

MS10 Bachelor of Mathematics (Honours)

1. Demonstrate and apply advanced knowledge and skills in mathematical sciences to critically analyse and solve complex problems within the discipline or in cross-disciplinary fields where mathematics underpins innovation
   Relates to: Problem Solving Task, Project (applied)
2. Communicate complex concepts, methods and findings in the mathematical sciences clearly and effectively to a range of audiences including mathematicians, industry professionals and the general public, using a range of academic, professional, and technical formats
   Relates to: Problem Solving Task, Project (applied)
3. Demonstrate autonomy, accountability, ethical scholarship, and effective collaboration for research and continuous learning, consistent with professional practice in the mathematical sciences
   Relates to: Project (applied)