MATHS 1015 - Advanced Mathematical Perspectives I
North Terrace Campus - Semester 1 - 2015
General Course Information
Course Code MATHS 1015 Course Advanced Mathematical Perspectives I Coordinating Unit School of Mathematical Sciences Term Semester 1 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 3 contact hours per week Available for Study Abroad and Exchange Y Restrictions Available to BMaSc (Adv) students only Course Description The aim of this course is to develop foundational research skills in the mathematical sciences. It will be taught as three small group workshops per week and assessed through guided discovery projects. Students will be required to participate proactively in the small groups workshops and by involvement in open-ended problems, independent reading and completion of the guided discovery projects.
Course Coordinator: Associate Professor Ben BinderCourse coordinator: Ben Binder
Office: Ingkarni Wardli, room 659
Phone: 8313 3244
Administrative enquiries: School of Mathematical Sciences office, Level 6, Ingkarni Wardli
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesStudents who successfully complete the course should:
1. appreciate the way pure mathematics is built on rigorous arguments
2. appreciate the difference between discrete and continuum modelling approaches
3. appreciate the need for statistics in parameter estimation
4. be able to develop their own rigorous mathematical arguments
5. be able to develop simple mathematical models
6. be able to implement models using Matlab
7. be able to analyse experimental data
8. be able to write project reports and give an oral presentation
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. all The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 7 An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 5,6,7,8 Skills of a high order in interpersonal understanding, teamwork and communication. 8 A proficiency in the appropriate use of contemporary technologies. 6,8 A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. all
Recommended ResourcesMaterials provided by lecturers.
Online LearningThis course uses MyUni exclusively for providing electronic resources, such as lecture notes, assignment papers, sample solutions, discussion boards, etc. It is recommended that students make appropriate use of these resources. Link to MyUni login page: https://myuni.adelaide.edu.au/webapps/login/
Learning & Teaching Activities
Learning & Teaching ModesThis course is run in a workshop format. Students will work closely with academic members of staff in a small group discovery environment. Two written projects and a presentation constitute the assessment for the course.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Activity Quantity Workload hours Workshops 36 108 Projects 2 32 Presentation 1 16 Total 156
Learning Activities SummaryWorkshop Outline
1. Introduction to the course, to pure mathematics, and to the first project
2. Proofs and mathematical arguments, background material
3. LaTeX tutorial
4. Public holiday
5. Proofs and mathematical arguments, background material
6. LaTeX tutorial
Week 3 7. Seminar-style discussion of the project
8. Seminar-style discussion of the project
9. Seminar-style discussion of the project
10. Theory: Outline for mathematical modelling project: Discrete and continuous models
11. Practical: Introduction to Matlab--basic plotting, programs, populating domains
12. Practical: Implementation of cellular automata mechanism for tissue growth
Week 5 13. Theory: Development of continuum model and analytical solutions
14. Practical: Implementation of cellular automata mechanism for tissue growth
15. Practical: LaTeX session
16. Theory: Continuum paths and space-time diagrams
17. Practical: Comparison of averaged cellular automata data with continuum paths
18. Practical: Comparison of averaged cellular automata data with continuum paths
19. Theory: Probabilistic description of discrete model, probability trees
20. Practical: Implementation of other cellular automata mechanisms
21. Practical: LaTeX session
22. Theory: Uniform and negative hypergeometric distribution
23. Practical: Implementation of other cellular automata mechanisms
24. Practical: Implementation of other cellular automata mechanisms
25. Theory: Polya distribution mean and variance, comparison with continuum paths
26. Practical: Comparison of averaged cellular automata data with paths/distributions
27. Practical: LaTeX session
28. Theory: Outline of statistical analysis of experimental data, linear regression
29. Practical: Basic curve fitting in Matlab
30. Practical: Parameter estimation for discrete and continuous models
31. Theory: Derive equations for intercept and slope for least squares
32. Theory: Matrix form of linear regression. Show equivalence to least squares
33. Practical: LaTeX session
34. Theory: Non-linear regression via linearization and also numerical optimization.
35. Practical: Matlab implementation of stats theory
36. Practical: LaTeX session
Small Group Discovery ExperienceThis course aims to develop independent student learning in a small group discovery environment.
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Component Weighting Objective Assessed Project report 1 25% 1,4,8 Project report 2 60% 2,3,5,6,7,8 Presentation 15% 2,3,4,5,6,7,8
Assessment item Distributed Due Date Weighting Project 1 Week 1 Week 6 25% Project 2 Week 4 Week 12 60% Presentation Week 7 Week 11-12 15%
Submission1. The reports are to be submitted to the relevant lecturer with a signed cover sheet attached.
2. Late reports will not be accepted.
3. Reports will have a two week turn-around time for feedback to students.
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending
Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through Access Adelaide.
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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