COMP SCI 1012 - Scientific Computing
North Terrace Campus - Semester 1 - 2016
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General Course Information
Course Details
Course Code COMP SCI 1012 Course Scientific Computing Coordinating Unit Computer Science Term Semester 1 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 5 hours per week Available for Study Abroad and Exchange Y Prerequisites SACE stage 2 Mathematical Studies or equivalent Incompatible APP MTH 1000, APP MTH 2106, ENG 2002, CHEM ENG 1002 & APP MTH 2005 Assessment written exam, assignments Course Staff
Course Coordinator: Professor Tat-Jun Chin
Course Timetable
The full timetable of all activities for this course can be accessed from .
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Learning Outcomes
Course Learning Outcomes
After completing this course you will be able to:
1. Write simple Matlab program scripts.
2. Solve systems of linear equations using Matlab.
3. Find roots of of mathematical functions.
4. Numerically solve simple differential equations.
5. Find optimum solutions to numerical problems.
6. Use Monte-Carlo techniques to obtain approximate solutions.
7. Explain the mathematical basis of the above techniques.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)
1,2,3,4,5,6,7 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
1,2,3,4,5,6,7 Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
1,2,3,4,5,6,7 -
Learning Resources
Required Resources
There is no required text-book. Comprehensive lecture notes (300+ pages) will be made available online from the course website as PDF files.Recommended Resources
Essential MATLAB for Engineers and Scientists by Brian Hahn and Daniel Valentine.Online Learning
There is an online forum, managed by Moodle. A link to Moodle appears on the subject web-page. We will use the Moodle forum to announce all changes to the course, exercises, and tutorials, and to answer/address questions. You are therefore strongly advised to read all mail that comes from this source — do not ignore it! -
Learning & Teaching Activities
Learning & Teaching Modes
The course will be taught using a variation of team-based learning, with lecture/demonstration sessions possibly interspersed with quiz/question time sessions. There will also be tutorial classes, and supervised practical sessions.Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Scientific Computing is a three-unit course. We expect that you will spend between 9-12 hours each week working on the course. This will consist of:
• 3 hours of lectures per week.
• 1 tutorial in the even weeks for 3 weeks, plus 1 hour of tutorial preparation. 1 SGDE session fornightly after that, plus 1 hour of out-pf-session discussion.
• 2 hours of supervised practical work per week for 10 weeks.
• 5-7 hours a week spent completing practical assignments. The work spent on practical assignments is likely to be closely associated with an assignment deadline, rather than spread out evenly across the semester. You should allow yourself enough time to complete the assignments to a high level.Learning Activities Summary
The planned timetable of lectures can be found at the online course forum.Specific Course Requirements
You must obtain 40% of the marks in the final exam, or your overall final mark will be capped at 44F. A minimum score of 50% overall is required to pass the course.Small Group Discovery Experience
There will be three SGDE sessions, held fortnightly, in the second half of the course. -
Assessment
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.
Assessment Summary
Assessment for the course consists of three components: Weekly supervised practical exercises (35% total), SGDE sessions (5% total), and a final exam (60%).
The due date for each exercise is published on the course website, and in each practical exercise specification. You must submit your exercises by the specified deadline, or you may suffer a reduction in your final marks. If you have a very good reason for extension, apply to the lecturer. Requests must be made in advance (unless you were unconscious or incapacitated), or they may not be granted.Assessment Related Requirements
You must obtain at least 40% of the marks in the exam, or your overall final mark will be capped at 44F. A minimum score of 50% overall is required to pass the course.Assessment Detail
All practical exercises involve writing programs, either in Matlab or using Excel. You are strongly encouraged to begin the exercises early, and to test your own program thoroughly.Submission
All practical assignments must be submitted through the Scientific Computing web-page. Instruction on how to do this are in the specification for each exercise.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 .
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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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Student Support
- Academic Integrity for Students
- Academic Support with Maths
- Academic Support with writing and study skills
- Careers Services
- Library Services for Students
- LinkedIn Learning
- Student Life Counselling Support - Personal counselling for issues affecting study
- Students with a Disability - Alternative academic arrangements
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
- Academic Integrity Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs Policy
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment Policy
- Reasonable Adjustments to Learning, Teaching & Assessment for Students with a Disability Policy
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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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鈥檚 disciplinary procedures.
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