MATHS 1015 - Advanced Mathematical Perspectives I

North Terrace Campus - Semester 1 - 2022

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
    Assessment Ongoing assessment
    Course Staff

    Course Coordinator: Associate Professor Ben Binder

    Ben Binder
    Office: Ingkarni Wardli, room 6.59

    Sue Barwick
    Office: Ingkgarni Wardli, room 6.36

    Administrative enquiries: Faculty Office, 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 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 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)

    Attribute 1: Deep discipline knowledge and intellectual breadth

    Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.


    Attribute 2: Creative and critical thinking, and problem solving

    Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.


    Attribute 3: Teamwork and communication skills

    Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.


    Attribute 4: Professionalism and leadership readiness

    Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.


    Attribute 8: Self-awareness and emotional intelligence

    Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.

  • Learning Resources
    Required Resources
    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:
  • Learning & Teaching Activities
    Learning & Teaching Modes
    This course is run largely 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 Summary

    Each week will consist of a combination of formal presentations of material, practicals, tutorials and workshops, though the mix in each week may vary depending on topic.

    Week 1: Introduction, Reading and writing mathematics, Latex

    Week 2: Problem solving and proof techniques.

    Week 3: Problem solving and proof techniques.

    Week 4: Introduction to applied mathematics & statistics project: models and statistical analysis of experimental data.

    Week 5: Continuum model and analysis

    Week 6: Discrete model and statistical analysis

    Week 7: Derivation of probablity function for discrete model

    Week 8: Comparison and relationship between continuum and discrete models

    Week 9: Application of models to understand the physical problem

    Week 10: Project

    Week 11: Project

    Week 12: Project

  • 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 (pure)        25%           2,3,4,5,6,7,8
    Project report (applied)        60%           1,4,8
    Presentation (applied)        15%           2,3,4,5,6,7,8

    Assessment Detail
    Assessment item        Distributed     Due Date           Weighting
    Project report (pure)          Week 1      Week 5         25%   
    Project report (applied)          Week 4      Week 13         60%
    Presentation (applied)          Week 4      Week 13         15%
    Milestones may be required as part of assessment of projects before the final due date. See MyUni for details.
    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 ( 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.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

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