COMP7500 - Sem 2 2008 - St Lucia - Internal

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1. General Course Information

1.1 Course Details

Course Code: COMP7500 Course Title: Advanced Algorithms & Data Structures
Coordinating Unit: School of Information Technology and Electrical Engineering
Semester: Semester 2, 2008    Mode: Internal
Level: Postgraduate Coursework
Location: St Lucia
Number of Units: 2    Contact Hours Per Week: 2L1T
Pre-Requisites: COMP7505
Incompatible: COMP4500 or CS318 or 363 or 418
Course Description: Analysis of algorithms. Solution of summation & recurrence equations. Algorithm paradigms: divide-&-conquer, greedy algorithms, dynamic programming, backtracking, branch-&-bound. Advanced graph algorithms. Amortised analysis. Self-adjusting data structures. Complexity classes, NP-completeness. Approximation algorithms. Randomized algorithms.
Assumed Background: The prerequisite knowledge required for the course is: programming experience, including basic data structures and recursive procedures; familiarity with a programming language; familiarity with proofs by mathematical induction; and knowledge of calculus, including differentiation, limits, L'Hôpital's rule, and summations.

1.2 Course Introduction

On entry to this subject you have studied basic data structures and programming techniques. The objective of this subject is to build on these basic programming skills to develop an understanding of algorithm design and analysis techniques.

A number of general design paradigms, such as divide-and-conquer, play an important role in the development of algorithms. Familiarity with these paradigms can aid the programmer in the development of algorithms to solve new problems. The study of these design paradigms is an important component of this subject.

It is not enough just to derive an algorithm that solves a problem. If the algorithm is inefficient, it may be useless in practice. One can better appreciate an algorithm if one can analyse its use of resources, such as memory and computing time. Such analyses provide the basis for comparison of different algorithms to solve the same problem.

Overall, this subject can be viewed as an advanced course on programming, with an emphasis on developing both your ability to solve programming problems and to analyse your algorithms to ascertain their efficiency.


 

1.3 Course Staff

Course Coordinator: Mr Brijesh Dongol
Phone: 3365 1651     Email: brijesh@itee.uq.edu.au Homepage: www.itee.uq.edu.au/~brijesh
Campus: St Lucia Building: General Purpose South (Map)   Room: 313


1.4 Timetable

Timetables are available on mySI-net.

2. Aims, Objectives & Graduate Attributes

2.1 Course Aims

Algorithms form the core of the implementation of any programming system. This course has the aim of expanding your ability to understand, analyse and develop algorithms as well as understand and use important algorithm design paradigms and commonly used advanced algorithms and data structures.

2.2 Learning Objectives

After successfully completing this course you should be able to:

1  Analyse the time and space complexity of algorithms and data structures
2  Understand and apply algorithm design paradigms (patterns)
3  Design algorithms based on graph manipulation
4  Design programs using combinations of advanced algorithms and data structures
5  Design and analyse advanced (abstract) data structures
6  Understand algorithm complexity classes

2.3. Graduate Attributes

Successfully completing this course will contribute to the recognition of your attainment of the following UQ (Postgrad Coursework) graduate attributes:

GRADUATE ATTRIBUTELEARNING OBJECTIVES
A. IN-DEPTH KNOWLEDGE OF THE FIELD OF STUDY
A2. A broad understanding of the field of study, including how other disciplines relate to the field of study. 6
A3. A comprehensive and in-depth knowledge in the field of study.1, 2, 3, 4, 5
A5. An international perspective on the field of study. 
A7. An appreciation of the link between theory and practice. 
B. EFFECTIVE COMMUNICATION
B1. The ability to collect, analyse and organise information and ideas and to convey those ideas clearly and fluently, in both written and spoken forms.1, 2, 3, 4, 5, 6
B2. The ability to interact effectively with others in order to work towards a common outcome. 
B3. The ability to select and use the appropriate level, style and means of communication. 
B4. The ability to engage effectively and appropriately with information and communication technologies.1, 2, 3, 4, 5, 6
B5. The ability to practise as part of an interdisciplinary team. 
C. INDEPENDENCE AND CREATIVITY
C2. The ability to work and learn independently and effectively.1, 2, 3, 4, 5, 6
C3. The ability to generate ideas and adapt innovatively to changing environments.2, 3, 4, 5
C5. The ability to formulate and investigate problems, create solutions, innovate and improve current practices.1, 2, 3, 4, 5
C6. The abilities and skills that provide a foundation for future leadership roles. 
D. CRITICAL JUDGEMENT
D2. The ability to apply critical reasoning to issues through independent thought and informed judgement.2, 3, 4, 5
D4. The ability to process material and to critically analyse and integrate information from a wide range of sources. 
D5. The ability to evaluate opinions, make decisions and to reflect critically on the justifications for decisions using an evidence-based approach. 
E. ETHICAL AND SOCIAL UNDERSTANDING
E1. An understanding of social and civic responsibility. 
E3. An appreciation of the philosophical and social contexts of a discipline.6
E4. A knowledge and respect of ethics and ethical standards in relation to a major area of study. 
E5. A knowledge of other cultures and times and an appreciation of cultural diversity. 
E7. The ability to work effectively and sensitively across all areas of society. 
E8. An understanding of and respect for the roles and expertise of associated disciplines. 

3. Learning Resources

3.1 Required Resources

Textbook

T. Cormen, C. Leiserson, R. Rivest and C. Stein, Introduction to Algorithms, MIT Press, 2001.

The text book is an extensive compendium of algorithms, data structures, design paradigms and analysis techniques.
This book is widely regarded as a computing science classic.
This edition is preferred but the earlier edition (below) will suffice.

 
 
T. Cormen, C. Leiserson and R. Rivest, Introduction to Algorithms, MIT Press, 1990.
Earlier edition of the text book. This edition will suffice but the later edition (above) is preferred.
 
 
Course web page. COMP7500 shares the web for COMP4500. URL
 
Course news group uq.itee.comp4500 URL
 

3.2 Recommended Resources

A. V. Aho, J. E. Hopcroft, and J. D. Ullman, Data Structures and Algorithms, Addison-Wesley, 1983

 
 
R. L. Graham, D. E. Knuth, and O. Patashnik, Concrete Mathematics: a Foundation for Computer Science, Addison-Wesley, 1989 or 1994  
 

D. Harel, Algorithmics: the Spirit of Computing, Addison-Wesley, 1987

 
 

D. E. Knuth, Fundamental Algorithms, Volume 1 of The Art of Computer Programming, Addison-Wesley, 1997 third edition

 
 

D. E. Knuth, Seminumerical Algorithms, Volume 2 of The Art of Computer Programming, Addison-Wesley, 1997 third edition

 
 

D. E. Knuth, Sorting and Searching, Volume 3 of The Art of Computer Programming, Addison-Wesley, 1998 second edition

 
 

R. Sedgewick, Algorithms in C, Addison-Wesley, 1990

 
 

J. D. Smith, Design and Analysis of Algorithms, PSW-Kent, 1989

 
 

D. R. Stinson, Introduction to the Design and Analysis of Algorithms , Charles Babbage Research Institute, 1985

 
 

H. S. Wilf, Algorithms and Complexity, available at URL (1994 edition)

URL
 

3.3 University Learning Resources

Access to required and recommended resources, plus past central exam papers, is available at the UQ Library website (http://library.uq.edu.au/search/r?SEARCH=COMP7500).

The University offers a range of resources and services to support student learning. Details are available on the myServices website (https://student.my.uq.edu.au/).

3.4 School of Information Technology and Electrical Engineering Learning Resources

Students enrolled at St Lucia who wish to retain a hard copy of this profile can use the free print quota provided each semester to students enrolled in courses in the School of Information Technology & Electrical Engineering. For information on how to use this print quota, see the School Policy on Student Photocopying and Printing (St Lucia) (http://www.itee.uq.edu.au/about_ITEE/policies/copy-print.html). Students enrolled at the Ipswich campus will either be provided with a hard copy or given directions in class on how to obtain a free copy.

ITEE course websites can be found at http://www.itee.uq.edu.au/~COURSECODE. Many ITEE courses also have Usenet newsgroups, named uq.itee.COURSECODE. Instructions for accessing newsgroups are available at http://studenthelp.itee.uq.edu.au/faq/1stYearFAQ.html#accessnews.

3.5 Other Learning Resources & Information

Lecture notes, revision materials and assignments will be available from the course web pages. Some solutions will also be available from the course web pages.

 

4. Teaching & Learning Activities

4.1 Learning Activities

Date
Activity
Learning Objectives
21 Jul 08
Introduction and mathematical background (Lecture Series): Time and space complexity: the desire for an implementation independent measure; worst-case and average-case complexity.

Evaluating efficiency: rate of growth, asymptotic time complexity; notation.

Iterative algorithms: analysis of "while" and "for" loops;
summations.
Readings/Ref: CLR (Chapters 1-3); CLRS (Chapters 1-3);
1
28 Jul 08
Divide and conquer algorithms and recurrences (Lecture Series): Divide-and conquer: recursion; divide, conquer and combine.

Solving recurrences: substitution; iterating the recurrence to get a summation; recursion trees; master method.

Readings/Ref: CLR (Chapter 4); CLRS (Chapter 4);
1, 2
4 Aug 08 - 24 Aug 08
Graph Algorithms (Lecture Series): Directed and undirected graphs: vertex, edge, predecessor, successor, indegree,
outdegree, path, reachable, simple, cycle; weighted graphs.

Graph representations: adjacency list and matrix representations.

Graph algorithms: breadth-first search;
depth-first search; topological sort.
Minimal spanning tree: generic form, greedy choice strategy.
Readings/Ref: CLR (Chapters 23-27); CLRS (Chapters 22-26);
1, 2, 3, 4, 5
25 Aug 08 - 7 Sep 08
Dynamic programming (Lecture Series): optimal substructure; overlapping subproblems;
table of subproblem solutions; memoization; order of evaluation; dynamic programming.
Readings/Ref: CLR (Chapter 16); CLRS (Chapter 15);
1, 2, 4
8 Sep 08 - 21 Sep 08
Greedy algorithms (Lecture Series): Greedy method: optimal substructure; greedy choice property; comparison of dynamic programming and greedy paradigms.
Readings/Ref: CLR (Chapter 17); CLRS (Chapter 16);
1, 2, 4
22 Sep 08
Amortised analysis (Lecture Series): Efficiency analysis in terms of sequences of operations; crude analysis;
global analysis; the accounting method; the potential method.
Readings/Ref: CLR (Chapter 18); CLRS (Chapter 17);
1, 5
6 Oct 08
Advanced Data Structures (Lecture Series): Binomial heaps, Fibonacci heaps
Readings/Ref: CLR (Chapters 20-21); CLRS (Chapters 19-20);
1, 2, 3, 4, 5
13 Oct 08
Complexity classes (Lecture Series): Decision problems; tractable and intractable problems; Polynomial time; the class P; Nondeterministic Polynomial; the class NP; reducibility; NP-completeness.
Readings/Ref: CLR (Chapter 35); CLRS (Chapter 34);
1, 6
20 Oct 08
Revision (Lecture Series):
1, 2, 3, 4, 5, 6

4.2 Other Teaching and Learning Activities Information

Each week there will be lectures and most weeks a revision session.
Revision exercise sheets are provided on the course web page and should be attempted before the revision session covering the revision sheet.

5. Assessment

5.1 Assessment Summary

This is a summary of the assessment in the course. For detailed information on each assessment, see 5.5 Assessment Detail below.

Assessment Task
Due Date
Weighting
Learning Objectives
Exam - Mid Semester During Class
Mid-semester examination
5 Sep 08 10:00
20%
1, 2, 3
Assignment
Assignment 1
12 Sep 08 10:00
15%
1, 2, 3, 4
Assignment
Assignment 2
17 Oct 08 10:00
15%
1, 2, 3, 4, 5
Exam - during Exam Period (Central)
Final Examination
Examination Period
50%
1, 2, 3, 4, 5, 6

5.2 Course Grading


Grade 1, Fail: Fails to demonstrate most or all of the basic requirements of the course:
  • At least one item of work submitted or examination attempted.
  • Your final percentage mark is your composite mark.


Grade 2, Fail: Demonstrates clear deficiencies in understanding and applying fundamental concepts; communicates information or ideas in ways that are frequently incomplete or confusing and give little attention to the conventions of the discipline:
  • Composite mark >= 20%.
  • Your final percentage mark is your composite mark.


Grade 3, Fail: Demonstrates superficial or partial or faulty understanding of the fundamental concepts of the field of study and limited ability to apply these concepts; presents undeveloped or inappropriate or unsupported arguments; communicates information or ideas with lack of clarity and inconsistent adherence to the conventions of the discipline:
  • Composite mark >= 45% and final examination >= 40%.
  • Your final percentage mark is the minimum of your composite mark and 49%.


Grade 4, Pass: Demonstrates adequate understanding and application of the fundamental concepts of the field of study; develops routine arguments or decisions and provides acceptable justification; communicates information and ideas adequately in terms of the conventions of the discipline:
  • Composite mark >= 50% and final examination >= 45%.
  • Your final percentage mark is the minimum of your composite mark and 64%.


Grade 5, Credit: Demonstrates substantial understanding of fundamental concepts of the field of study and ability to apply these concepts in a variety of contexts; develops or adapts convincing arguments and provides coherent justification; communicates information and ideas clearly and fluently in terms of the conventions of the discipline:
  • Composite mark >= 65% and final examination >= 60%.
  • Your final percentage mark is the minimum of your composite mark and 74%.
  • COMP7500 students must pass both assignments.


Grade 6, Distinction: As for 5, with frequent evidence of originality in defining and analysing issues or problems and in creating solutions; uses a level, style and means of communication appropriate to the discipline and the audience:
  • Composite mark >= 75% and final examination >= 70%.
  • Your final percentage mark is the minimum of your composite mark and 84%.
  • COMP7500 students must pass both assignments.


Grade 7, High Distinction: As for 6, with consistent evidence of substantial originality and insight in identifying, generating and communicating competing arguments, perspectives or problem solving approaches; critically evaluates problems, their solutions and implications:
  • Composite mark >= 85% and final examination >= 80%.
  • Your final percentage mark is your composite mark.
  • COMP7500 students must pass both assignments.


Other Requirements & Comments :
  • MS = mid-semester exam mark; A1 = assignment 1 mark; A2 = assignment 2 mark; F = final exam mark
    C1 = 0.2*MS + 0.15*A1 + 0.15*A2 + 0.5*F
    C2 = 0.15*A1 + 0.15*A2 + 0.7*F
    composite mark = max(C1, C2)
  • At the discretion of the course coordinator, final grades may be scaled upwards, but not downwards.

5.3 Late Submission

A penalty of 10% of the maximum mark for an assignment will be deducted for each day late. Assignments more than 7 days late will not be accepted without an extension having been granted.

Requests for extensions should be directed to the course co-ordinator and should be accompanied by suitable documentation, e.g., medical certificates. Personal hardware or computer failures are not grounds for extension. Assignments must be backed up on the university system.

5.4 Other Assessment Information

Assignments will be returned during class periods.

5.5 Assessment Detail


Mid-semester examination
Type: Exam - Mid Semester During Class
Learning Objectives Assessed: 1, 2, 3
Due Date:
         5 Sep 08 10:00
Weight: 20%
Perusal: 10 minutes
Duration: 90 minutes
Format: Problem solving
Task Description: The mid-semester examination will be held in the two hour lecture period.
It covers algorithm analysis, design paradigms and graph algorithms.
The examination is closed book, however, you are allowed to bring in one A4 crib sheet.
  • The crib sheet may be written on both sides.
  • Handwriting may be as small writing as you like.
  • If mechanically produced it must have a minimum font size of 10pt.
You must hand in your crib sheet when you submit your examination.
Criteria & Marking: A sample mid-semester examination is provided.

Assignment 1
Type: Assignment
Learning Objectives Assessed: 1, 2, 3, 4
Due Date:
         12 Sep 08 10:00
Weight: 15%
Task Description: Details of the assignment will be provided via the course web page.
The assignment covers algorithm analysis, divide-and-conquer algorithms, recurrences and graph algorithms.
COMP7500 students must pass both assignments to obtain a 5 or above.
Criteria & Marking: Detailed assessment criteria will be provided with the assignment.
Submission: Assignments must be submitted electronically via the the course web page. Your assignment submission must be accompanied by a declaration that your submission is your original work.

Assignment 2
Type: Assignment
Learning Objectives Assessed: 1, 2, 3, 4, 5
Due Date:
         17 Oct 08 10:00
Weight: 15%
Task Description: Details of the assignment will be provided via the course web page.
The assignment covers algorithm analysis, and algorithm design paradigms.
COMP7500 students must pass both assignments to obtain a 5 or above.
Criteria & Marking: Detailed assessment criteria will be provided with the assignment.
Submission: Assignments must be submitted electronically via the the course web page. Your assignment submission must be accompanied by a declaration that your submission is your original work.

Final Examination
Type: Exam - during Exam Period (Central)
Learning Objectives Assessed: 1, 2, 3, 4, 5, 6
Due Date:
         Examination Period
Weight: 50%
Perusal: 10 minutes
Duration: 120 minutes
Format: Problem solving
Task Description: The final examination is compulsory and covers the entire course.
More details on the final examination will be provided on the course web page.
The examination is closed book, however, you are allowed to bring in one A4 crib sheet.
  • The crib sheet may be written on both sides.
  • Handwriting may be as small writing as you like.
  • If mechanically produced it must have a minimum font size of 10pt.
You must hand in your crib sheet when you submit your examination.
Criteria & Marking: Previous final examinations will be available.

6. Policies & Guidelines

 
This section contains the details of and links to the most relevant policies and course guidelines. For further details on University Policies please visit myAdvisor and the University Handbook of Policies and Procedures.

6.1 Assessment Related Policies and Guidelines

University Policies & Guidelines

An overview of the University’s assessment-related policies can be found on myAdvisor (http://www.uq.edu.au/myadvisor/index.html?page=2910).

Academic Integrity
It is the University's task to encourage ethical scholarship and to inform students and staff about the institutional standards of academic behaviour expected of them in learning, teaching and research. Students have a responsibility to maintain the highest standards of academic integrity in their work. Students must not cheat in examinations or other forms of assessment and must ensure they do not plagiarise.

Plagiarism
The University has adopted the following definition of plagiarism:

Plagiarism is the act of misrepresenting as one's own original work the ideas, interpretations, words or creative works of another. These include published and unpublished documents, designs, music, sounds, images, photographs, computer codes and ideas gained through working in a group. These ideas, interpretations, words or works may be found in print and/or electronic media.

Students are encouraged to read the UQ Academic Integrity and Plagiarism policy (http://www.uq.edu.au/hupp/index.html?page=25128) which makes a comprehensive statement about the University's approach to plagiarism, including the approved use of plagiarism detection software, the consequences of plagiarism and the principles associated with preventing plagiarism.

Feedback on Assessment
Feedback is essential to effective learning and students can expect to receive appropriate and timely feedback on all assessment. For a detailed explanation of the feedback you are entitled to, you should consult the policy on Student Access to Feedback on Assessment. (http://www.uq.edu.au/hupp/index.html?page=25109)

As a student you have a responsibility to incorporate feedback into your learning; make use of the assessment criteria that you are given; be aware of the rules, policies and other documents related to assessment; and provide teachers with feedback on their assessment practices.

There are certain steps you can take if you feel your result does not reflect your performance. Please refer to the myAdvisor web site. (http://www.uq.edu.au/myadvisor/index.html?page=2953)

Feedback in this Course

Students may provide anonymous feedback to the course coordinator via the course web page.

School of Information Technology and Electrical Engineering Assessment Guidelines

Misconduct
 

Further to the statement on academic integrity and plagiarism above, students are required to read and understand the ITEE policy on Student Misconduct (http://www.itee.uq.edu.au/about_ITEE/policies/student-misconduct.html).

 

Late Arrival or Non-attendance at Examinations

 

The policy and procedure for late arrival or non-attendance at centrally controlled examinations is set out in the University's Examinations policy (HUPP 3.30.5), sections 8 and 10.2.

 

The way in which late arrival at a School-controlled examination is dealt with will be at the discretion of the course coordinator, who may be guided by the policy for centrally controlled exams.

 

In the case that a student requests a special exam for a School-controlled exam, the request will be considered and, if allowed, the timing shall be determined by the course coordinator, in consultation with the School's Chief Examiner where necessary, and in accordance with HUPP 3.30.5. Unless otherwise indicated in the Course Profile, applications must be made in writing to the Head of School no later than one week after the exam. Late applications will not be accepted.

 
Examination Feedback
 
In addition to the advice above, students wishing to view examination answer scripts and/or question papers should consult with the School office (Room 217, General Purpose South Building [78], St Lucia; Room 218, Building 1, Ipswich) regarding arrangements. The ITEE policy on exam script viewing is available at http://study.itee.uq.edu.au/current_students/exam_script_viewing.html.

Supplementary Assessment

If you fail this course you may be eligible for supplementary assessment - see the general award rules and/or your program rules for details. You should note that even though you may be eligible for supplementary assessment under these rules, in some circumstances there may be no practical assessment that can be offered to allow you to meet the minimum passing requirements. These circumstances may include failure based on:
  • group or team based assessment;
  • attendance or class participation requirements;
  • laboratory-based assessment, where laboratories can't practically be made available after classes have finished;
  • project or thesis-based assessment, where a significant period of time would be required to undertake supplementary assessment;
  • progressive assessment, where subsequent assessment items build on earlier assessment items; or
  • multiple assessment items, where it is impractical to offer multiple supplementary assessment items.
If the course coordinator determines that there is no practical supplementary assessment that can be offered to allow you to improve your grade, then you will not be offered supplementary assessment and your grade will remain unchanged.

6.2 Other Policies and Guidelines

University Policies and Guidelines

Placement Courses
Students on a placement course – also known as a work placement, internship, industry study, industry experience, clinical practice, clinical placement, practical work, practicum, fieldwork, teaching practice – should refer to the University policy, Placement Courses (http://www.uq.edu.au/hupp/index.html?page=25120) for detailed information.
 
Working with Children
Students whose studies include a professional/work placement, internship, clinical practice, teaching practice or other similar activity which involves them in regular contact with children should refer to the University policy, Working with Children Check - "blue card" (http://www.uq.edu.au/hupp/index.html?page=25004) to find out how to apply for a ‘blue card’.
 
Students with a Disability
Any student with a disability who may require alternative academic arrangements, including assessment, in the course/program is encouraged to seek advice at the commencement of the semester from a Disability Adviser at Student Support Services. Refer to the University policy, Students with a Disability (Disability Action Plan) (http://www.uq.edu.au/hupp/index.html?page=25122) and to the policy on Special Arrangements for Examinations for Students with a Disability (http://www.uq.edu.au/hupp/index.html?page=25111

Where an adjustment is made to an accredited program, it is the responsibility of the relevant Faculty to liaise with professional and registration bodies regarding the acceptability of the change/s.  

Occupational Health and Safety
Undergraduate Students (http://www.uq.edu.au/hupp/index.html?page=25055) and Postgraduate Students (http://www.uq.edu.au/hupp/index.html?page=25057) should be familiar with the University policies on occupational health and safety in the laboratory.

Other School of Information Technology and Electrical Engineering Guidelines

Ethical Clearance
If your course involves assignment or project work involving human subjects or human-related materials, you must investigate the need for ethical clearance and obtain it when required. Information on ethical clearance can be found at http://www.uq.edu.au/research/orps/index.html?page=5064&pid=5256.

Learning Summary

 

Below is a table showing the relationship between the learning objectives for this course and the broader graduate attributes developed, the learning activities used to develop each objective and the assessment task used to assess each objective.

Learning Objectives

After successfully completing this course you should be able to:

1  Analyse the time and space complexity of algorithms and data structures
2  Understand and apply algorithm design paradigms (patterns)
3  Design algorithms based on graph manipulation
4  Design programs using combinations of advanced algorithms and data structures
5  Design and analyse advanced (abstract) data structures
6  Understand algorithm complexity classes


Assessment & Learning Activities

  Learning Objectives
  1 2 3 4 5 6
Learning Activities
Introduction and mathematical background (Lecture Series)
selected
         
Divide and conquer algorithms and recurrences (Lecture Series)
selected
selected
       
Graph Algorithms (Lecture Series)
selected
selected
selected
selected
selected
 
Dynamic programming (Lecture Series)
selected
selected
 
selected
   
Greedy algorithms (Lecture Series)
selected
selected
 
selected
   
Amortised analysis (Lecture Series)
selected
     
selected
 
Advanced Data Structures (Lecture Series)
selected
selected
selected
selected
selected
 
Complexity classes (Lecture Series)
selected
       
selected
Revision (Lecture Series)
selected
selected
selected
selected
selected
selected
Assessment Tasks
Mid-semester examination
selected
selected
selected
     
Assignment 1
selected
selected
selected
selected
   
Assignment 2
selected
selected
selected
selected
selected
 
Final Examination
selected
selected
selected
selected
selected
selected

Graduate Attributes

Successfully completing this course will contribute to the recognition of your attainment of the following UQ (Postgrad Coursework) graduate attributes:

  Learning Objectives
  1 2 3 4 5 6
Graduate Attributes
A IN-DEPTH KNOWLEDGE OF THE FIELD OF STUDY
A2. A broad understanding of the field of study, including how other disciplines relate to the field of study.          
selected
A3. A comprehensive and in-depth knowledge in the field of study.
selected
selected
selected
selected
selected
 
A5. An international perspective on the field of study.            
A7. An appreciation of the link between theory and practice.            
B EFFECTIVE COMMUNICATION
B1. The ability to collect, analyse and organise information and ideas and to convey those ideas clearly and fluently, in both written and spoken forms.
selected
selected
selected
selected
selected
selected
B2. The ability to interact effectively with others in order to work towards a common outcome.            
B3. The ability to select and use the appropriate level, style and means of communication.            
B4. The ability to engage effectively and appropriately with information and communication technologies.
selected
selected
selected
selected
selected
selected
B5. The ability to practise as part of an interdisciplinary team.            
C INDEPENDENCE AND CREATIVITY
C2. The ability to work and learn independently and effectively.
selected
selected
selected
selected
selected
selected
C3. The ability to generate ideas and adapt innovatively to changing environments.  
selected
selected
selected
selected
 
C5. The ability to formulate and investigate problems, create solutions, innovate and improve current practices.
selected
selected
selected
selected
selected
 
C6. The abilities and skills that provide a foundation for future leadership roles.            
D CRITICAL JUDGEMENT
D2. The ability to apply critical reasoning to issues through independent thought and informed judgement.  
selected
selected
selected
selected
 
D4. The ability to process material and to critically analyse and integrate information from a wide range of sources.            
D5. The ability to evaluate opinions, make decisions and to reflect critically on the justifications for decisions using an evidence-based approach.            
E ETHICAL AND SOCIAL UNDERSTANDING
E1. An understanding of social and civic responsibility.            
E3. An appreciation of the philosophical and social contexts of a discipline.          
selected
E4. A knowledge and respect of ethics and ethical standards in relation to a major area of study.            
E5. A knowledge of other cultures and times and an appreciation of cultural diversity.            
E7. The ability to work effectively and sensitively across all areas of society.            
E8. An understanding of and respect for the roles and expertise of associated disciplines.