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Modelling the Real World (EVSC20007)
Undergraduate level 2Points: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Overview
Availability | Semester 1 |
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Fees | Look up fees |
The ability to model natural and human phenomena is key to understanding physical, biological and human environments. Models can be conceptual, logical, mathematical and software based; this subject explores how models of varying complexity can be used for modelling systems in the real world depending on resolution needed and information available.
Population growth, disease propagation, traffic flows, pollution dispersion, earthquake impacts, climate and energy prediction models are widely used to plan for the sustainable use of resources and management of the natural and built environment. Using real-world examples drawn from physics, chemistry, biology and earth sciences, this subject introduces students to framing these, sometimes complex, systems firstly as conceptual models, then as logical and mathematical models. These logical and mathematical models are then brought to life using tools such as software representations and simulations for the system of interest.
These real world models are used to test hypotheses and observables. Visualisation tools along with the ability to formulate and simulate natural and human systems are skills readily transferrable to many science, engineering, business and medical professions.
Intended learning outcomes
Upon completion of this subject, students should be able to:
- Formulate natural and human phenomena in a conceptual framework.
- Translate a conceptual model of an observed system into a mathematical and logical model representation.
- Design a software model based upon a mathematical and logical representation of a system.
- Visualise and predict the temporal and spatial evolution of a system using software tools.
- Evaluate hypotheses and the various models with observational data.
Generic skills
- Think critically: organise observations of complex systems into alternative frameworks
- Problem-solving skills: the ability to engage with unfamiliar problems and identify relevant solution strategies
- Modelling skills: to design simple computer programs to solve models and test hypotheses
- Time-management skills: the ability to meet regular deadlines while balancing competing commitments
Last updated: 15 February 2024
Eligibility and requirements
Prerequisites
A score of 29 VCE - 3/4 Specialist Mathematics or
Code | Name | Teaching period | Credit Points |
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MAST10005 | Calculus 1 |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
At least 12.5 points completed from BIOL, CHEM, COMP, ERTH, EVSC, GEOG, PHYC
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 15 February 2024
Assessment
Additional details
- A 1-hour mid-semester test (20%) in week 6.
- Four laboratory exercises completed during practice classes, held at regular intervals during semester due in weeks 4, 8, 10, 12 (10% for each exercise).
- A 2-hour written examination in the examination period (40%).
Last updated: 15 February 2024
Dates & times
- Semester 1
Principal coordinator Robyn Schofield Mode of delivery On Campus (Parkville) Contact hours 48 hours: 24 x one-hour lectures (2 per week), 12 x two-hour practice classes (1 per week) Total time commitment 170 hours Teaching period 4 March 2019 to 2 June 2019 Last self-enrol date 15 March 2019 Census date 31 March 2019 Last date to withdraw without fail 10 May 2019 Assessment period ends 28 June 2019 Semester 1 contact information
Last updated: 15 February 2024
Further information
- Texts
- Related Handbook entries
This subject contributes to the following:
Type Name Informal specialisation Science-credited subjects - new generation B-SCI - Breadth options
This subject is available as breadth in the following courses:
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 15 February 2024