COMP SCI 7099A - Master Computer Science Research Project - Part A
North Terrace Campus - Semester 1 - 2017
General Course Information
Course Code COMP SCI 7099A Course Master Computer Science Research Project - Part A Coordinating Unit School of Computer Science Term Semester 1 Level Postgraduate Coursework Location/s North Terrace Campus Units 9 Available for Study Abroad and Exchange N Prerequisites COMP SCI 7007 Restrictions Available to M Comp Sci students only Course Description The project is an advanced research project conducted individually under the guidance of an academic supervisor. It continues over two semesters and gives students the chance to investigate and contribute to an area at the cutting edge of computer science. Project topics vary from year to year depending on staff availability and research focus.
Course Coordinator: Dr Javen Shi
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesOn successful completion of this course students will be able to:
1 Gain exposure to research in an area of computer science. 2 Learn to interpret and assess literature related to a current area of research. 3 Learn how to experiment with algorithms whose properties are not known in advance. 4 Learn how to experiment with algorithms whose properties are not known in advance. 5 Learn to work and plan independently.
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 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
2,3,5 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
4 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 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, diffuse conflict and engage positively in purposeful debate
Recommended ResourcesResources are recommended on an individual basis by project supervisors. A dedicated computer laboratory is available at room 4.61, Ingkarni Wardli Building. Specialised computing requirements should be arranged through the project supervisor.
Online LearningA Moodle forum (“Honours and Master Computer Science Project”) is available for announcements and discussion about the MCS project:
Learning & Teaching Activities
Learning & Teaching ModesThe MCS project is intended to provide an introduction to computer science research in the area chosen by the student. Students learn by a combination of reading research papers, discussing problems with their supervisor and peers, writing experimental programs and presenting their work both orally and in a written report.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.A MCS student is expected to spend 30 hours per week on his/her project for the 9 unit component in addtion to attending meetings with supervisors.
Learning Activities SummaryThe MCS Project consists of several stages, including:
1. Proposal and literature review,
2. Initial implementation and testing,
3. Progress presentation and report writing.
The specific content of each step is highly project dependent, and should be discussed with the project supervisor.
Specific Course RequirementsN/A
Small Group Discovery ExperienceThe Master Computer Science project typically involves one student and one (or more) academic staff.
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 SummaryThe project Part A has two main assessement components:
1) Project proposal (5% of the overall assessment) [CBOK Areas: 1,2,3,7,8,9,10]
2) Progress presentation (5% of the overall assessment) [CBOK Areas: 1,2,3,4,5,6,7,8,9,10,11]
3) Progress report (20% of the overall assessment) [CBOK Areas: 1,2,3,4,5,6,7,8,9,10,11]
6.History & Status of the Discipline
7.Hardware & Software
8.Data & Information
10.Human Computer Interfaces
Assessment Related RequirementsA mark of 50% or greater is required to pass this course.
Assessment DetailThe MCS Project is assessed primarily on the final report written by the student. The report is marked by two examiners and verified by all academic staff.
SubmissionProject submission are made through the Moodle forum provided for the course.
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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