C&ENVENG 7063 - Computing for Geostatistics

North Terrace Campus - Winter - 2017

The purposes of this course are: (1) To teach the rudiments of Fortran 95 programming language so that students can implement their own simple programmed versions of geostatistical techniques. They may also require these skills for manipulating data in their project and coursework. (2) To teach basic R and Excel techniques for analysing and plotting data. (3) To teach numerical algorithms and computer methods commonly used in geostatistics concerning the solution to large sets of linear equations.

  • General Course Information
    Course Details
    Course Code C&ENVENG 7063
    Course Computing for Geostatistics
    Coordinating Unit School of Civil, Environmental & Mining Eng
    Term Winter
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact 38 hrs lectures, 10 hours practicals, 10 hrs tutorials
    Available for Study Abroad and Exchange N
    Assumed Knowledge basic computing skills
    Restrictions available to M.Geostatistics students only
    Assessment 100% coursework
    Course Staff

    Course Coordinator: Associate Professor Bree Bennett

    Course Timetable

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

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course students will be able to:

     
    1 demonstrate competence in using computers and information technology effectively.
    2 show competence in problem identification, formulation and solution.
    3 apply critical thinking and creative thinking to solve geostatistical problems.
    4 recognise and explain numerical issues that lie behind pre-packaged geostatistical software.
    5 use basic coding skills to solve geostatistical problems

     
    The above course learning outcomes are aligned with the Engineers Australia Stage 1 Competency Standard for the Professional Engineer.
    The course is designed to develop the following Elements of Competency: 1.1   1.2   1.3   1.5   2.1   2.2   2.3   

    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)
    2,3,4
    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
    2
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    1,4,5
  • Learning Resources
    Required Resources
    • Lecture notes are provided.
    • Students should bring a laptop for convenience of learning as all tutorials and assignments are computer based. Alternative arrangements can be made if this is not possible.


    Recommended Resources
    • Press et al. Fortran 90 edition of Numerical Recipes, online at http://www.nr.com/
    • Walker, D., Leonard, M., Metcalfe A.V. and Lambert, M.F., (2008) Engineering Modelling and Analysis, Taylor and Francis, London


    Online Learning
    Course materials available online include:
    • powerpoint slides
    • assignment handouts
    • supporting material


  • Learning & Teaching Activities
    Learning & Teaching Modes
    This is an intensive course with 7 hours teaching per day. The course covers fundamental principles of programming and how solutions to geostatistical problems are implemented. The course uses computer based tutorials (approx 3 hours  per day) to consolidate skills on realistic problems.

    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    Activity Contact Hours Private Study Hours Total
    Lectures 20 10 30
    Tutorials 15 15 30
    Assignments - 52 52
    Total 35 77 112
    Learning Activities Summary
    Full details of each assessment task will be provided through MyUni.
    Specific Course Requirements
    Students must be available for the entire week as the course is run as an intensive. Missing 1 day is the same as missing 20% of the course.

  • 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
    Assessment Task Weighting (%) Individual/ Group Formative/ Summative
    Due (week)*
    Hurdle criteria Learning outcomes
    Assignment 1 30 Individual Summative NA 1. 2. 3. 4. 5.
    Assignment 2 30 Individual Summative NA 1. 2. 3. 4. 5.
    Assignment 3 40 Individual Summative NA 1. 2. 3. 4. 5.
    Total 100
    * The specific due date for each assessment task will be available on MyUni.
     
    This assessment breakdown is registered as an exemption to the University's Assessment for Coursework Programs Policy. The exemption is related to the Procedures clause(s): 1. c.   
     
    Assessment Related Requirements
    Attendance for the entire week of lectures is compulsory.
    Assessment Detail
    Assessment Task Weighting Due Date Learning Outcomes
    Assignment 1 – Development of 3D variogram from raw data 30% Week starting 8 August 1-5
    Assignment 2 – 3D Kriging interpolation problem for a large dataset 30% Week starting 8 August 1-5
    Assignment 3 – Compare primary and dual forms of kriging equations 40% Week starting 8 August 1-5
    Submission
    Assignments should be handed in electronically to lecturer via email by 4pm on the specified date. A brief description of the program function, structure, results and validation of performance should also be provided.

    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.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

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