MATHS 1015 - Advanced Mathematical Perspectives I

North Terrace Campus - Semester 1 - 2016

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.

  • General Course Information
    Course Details
    Course Code MATHS 1015
    Course Advanced Mathematical Perspectives I
    Coordinating Unit 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 Staff

    Course Coordinator: Associate Professor Ben Binder

    Course coordinator: Ben Binder
    Email: benjamin.binder@adelaide.edu.au
    Office: Ingkarni Wardli, room 659
    Phone: 8313 3244
    Administrative enquiries: School of Mathematical Sciences office, Level 6, Ingkarni Wardli
    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    Students 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 statistical analysis of discrete data

    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 discrete 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)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    all
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    4,5,6,7,8
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    all
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    6,8
    Self-awareness and emotional intelligence
    • a capacity for self-reflection and a willingness to engage in self-appraisal
    • open to objective and constructive feedback from supervisors and peers
    • able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
    1,2,3,8
  • Learning Resources
    Required Resources
    None.
    Recommended Resources
    Materials provided by lecturers.
    Online Learning
    This 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 Modes
    This 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.
    Workload

    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 Summary
    Workshop Outline

    Week 1
    1. Theory: Outline for mathematical modelling project: Discrete and continuous models
    2. Theory: Development of continuum model and analytical solutions
    3. Theory: Continuum paths and space-time diagrams

    Week 2
    4. Practical: Introduction to Matlab—plotting of continuum paths
    5. Practical: Plotting of continuum paths
    6. Practical: LaTeX session

    Week 3
    7. Public holiday
    8. Practical: Implementation of cellular automata mechanism for tissue growth
    9. Practical: Implementation of cellular automata mechanism for tissue growth

    Week 4
    10. Practical: Implementation of cellular automata mechanism for tissue growth
    11. Practical: Statistical analysis of cellular automata data and comparison with continuum paths
    12. Practical: Statistical analysis of cellular automata data and comparison with continuum paths

    Week 5
    13. Public holiday
    14. Theory: Probabilistic description of discrete model, probability trees
    15. Theory: Uniform and negative hypergeometric distribution

    Week 6
    16. Theory: Polya distribution mean and variance, comparison with continuum paths
    17. Practical: Comparison of averaged cellular automata data with paths/distributions
    18. Practical: Preparing a Poster session

    Week 7
    19. Public holiday
    20. Practical: Preparing a Poster and Feedback on draft report
    21. Practical: Preparing a Poster and Feedback on draft report
     
    Week 8
    22. Practical: Preparing a Poster and Feedback on draft report
    23. Oral Assessment: Poster session
    24. Oral Assessment: Poster session

    Week 9
    25. Oral Assessment: Poster session
    26. Practical: Consultancy session
    27. Practical: Consultancy session
     
    Week 10
    28. A brief overview of mathematics
    29. A brief overview of pure mathematics
    30. What is good mathematics?

     Week 11
    31. Proving results in mathematics
    32. The notions of equivalence and classification
    33. More on proofs

    Week 12
    34. Surfaces and their characteristics
    35. Classification of surfaces -- the orientable case
    36. Classification of surfaces -- the non-orientable case

    Week 13
     37. End of proofs. Recapitulation of pure section
     38. Discussion, including second project




    Small Group Discovery Experience
    This course aims to develop independent student learning in a small group discovery environment.
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Component     Weighting     Objective Assessed
    Project report 1        60%           2,3,4,5,6,7,8
    Project report 2        25%           1,4,8
    Presentation        15%           2,3,4,5,6,7,8
    Assessment Detail
    Assessment item        Distributed     Due Date           Weighting
    Project 1          Week 2      Week 10         60%   
    Project 2          Week 10      Week 13         25%
    Presentation          Week 6      Week 8         15%
    Submission
    1. 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.
    Course Grading

    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.

  • Student Feedback

    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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  • Policies & Guidelines
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