• Offered by School of Computing
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Computer Science
  • Areas of interest Computer Science, Advanced Computing
  • Academic career UGRD
  • Course convener
    • Prof Jochen Renz
  • Mode of delivery In Person
  • Offered in First Semester 2022
    See Future Offerings

This course has been adjusted for remote participation in Semester 1 2021.

The course introduces students to some fundamentals of research methodology. The course comprises a series of lectures which cover the following topics: Philosophy of Science, Quantitative Research Methods, Qualitative Research Methods, Basic Machine Learning Methods, Theoretical Research Methods, How to find a Research Topic, Literature Analysis, Reading and Reviewing Papers, Research Ethics and Commercialising Research. The lectures will be complemented by a series of workshops, labs and assignments that require students to do some small research focused tasks that help them get a hands-on experience of research, both individually and in teams of students. This includes different tasks such as topic modelling, statistical analysis, applying different machine learning techniques to solve a problem in a team, proving theorems, complexity analysis, designing a research project, reviewing papers and presenting papers. Workshops cover topics such as research integrity, time management and project management, teamwork, reading strategies, report writing, and presenting research. At the end of the course, students will be confident to start working on their own research projects.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Demonstrate an ability to communicate in relation to an computing project in oral, written and graphical forms, with an an appreciation of the need to pitch any communication item appropriately for the audience. This includes demonstrated skills in the writing of abstracts and research papers.
  2. Demonstrate an improved ability to use an active approach to learning and to undertake reflective professional practice.
  3. Demonstrate an awareness of the existence of technological choices; and make appropriate choices based on a consideration of design criteria.
  4. Demonstrate an ability to undertake and manage a research project of significant size and scope.
  5. Understanding of the process of identifying and formulating research problems.
  6. Ability to carry out literature searches and some ability to critically evaluate literature.
  7. Design and conduct experiments, devise appropriate measurements, analyze and interpret data and form reliable conclusions.
  8. Demonstrate awareness of the importance of documenting all aspects of the development of an computing project of significant magnitude.

Indicative Assessment

  1. Two assignments, worth 15% each. The project assessment is worth 70% and consists of the project report (65%), a seminar (15%) and other assessment items jointly agreed on by the student and supervisor prior to project commencement (20%). (100) [LO 1,2,3,4,5,6,7,8]

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

120 hours

Inherent Requirements

Information on inherent requirements for this course are currently not available.

Requisite and Incompatibility

To enrol in this course you must be enrolled in the Bachelor of Advanced Computing (Research and Development) (Honours)

Prescribed Texts

None

Majors

Fees

Tuition fees are for the academic year indicated at the top of the page.  

Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees

Student Contribution Band:
2
Unit value:
6 units

If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
2504 21 Feb 2022 28 Feb 2022 31 Mar 2022 27 May 2022 In Person N/A

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