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Dr Brad Alexander will be the primary lecturer and coordinator for the course. In addition there will some consulting support available for project work as required during the semester.

The course timetable takes place over Semester 2, 2014, with one 2-hour lecture on every Tuesday, one 1-hour Tutorial on each Friday and a 2-hour project/practical session on each Friday. The location of activities may vary depending on the week and the activity. Students are expected to read the course forum (Section 3.3) to confirm any changes to location.

In this course, you will learn about the grand challenges in the field of computing and what the six, currently defined, grand challenges are.

The learning objectives for Grand Challenges are:

1. To be able to identify, justify and discuss the grand challenge problems, giving clear examples of why these are significant to the discipline and to the population at large.
2. To develop and apply systematic and creative thinking techniques for analysis and problem solving
3. To gain experience in the application of critical thinking skills in the development of complex activities and in the provision of constructive criticism.
4. To gain experience in the application of fundamental Computer Science methods and algorithms in the analysis, summarization and presentation of large and significant data sets.
5. To develop or further refine the ability to communicate, in written, visual and verbal form, in order to convey complex information to others in a way that supports decision-making.

Required readings will be provided on the course website. There is no required textbook for this course.

There are no textbooks for this course. There are a number of reference books and additional notes will be given during class including:

1. Data Analysis with Open Source Tools P. Janert,
2. Information is Beautiful D. McCandless, Collins

The Grand Challenges course uses a Moodle forum to provide online resources to students:

The course aims to introduce students to a wide range of concepts and techniques. The course will be taught using the following class activities:

• Lectures, tutorials and practical/project activities Students are expected to attend all classes. 

The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
This information is provided as a guide to assist students in engaging appropriately with the course requirements. Grand Challenges is a 3 unit course. The expectation is that students will devote at least 156 hours to a 3 unit course, including contact hours. It is important to note that, given that the exam weighting is significantly smaller than is usual for Computer Science, it is expected that additional work time will be allocated to the assignments.

Lecture Topics  

• Grand Challenges: Intro and the 6 Challenges
• Advanced Computational Methods and Algorithms, Data and Visualisation
• High Performance Computing; Software Infrastructure
• Education, training and workforce; Grand Challenge Communities
• Current Research: School research group leaders - grand challenge focus
• Supporting research with evidence: statistics.
• Thinking about thinking: fallacies, philosophical foundations and a world of effects.
• Dynamic visualisation in industry and research
• Blue sky thinking: research leaders discuss their wish list.
• How are we doing?
• Defined grand challenges versus achievement: 1945- 2012
• Ethical issues in Community Science: where are we going?

Tutorials
Topics are selected according to project. Topics may include: Project and Practical Activities 

• Project 1: Preparation
• Project 1: Pitch of Candidates. Group feedback.
• Project 1: First cut 
• Project 1: Feedback
• Project 1: Revised version, rebuttal.
• Project 2: Second Project iteration
• Project 2: Pitch and feedback
• Project 2: Progress report.
• Project 2: First demonstration and feedback.
• Project 2: Final demonstration.
• Project 2: Presentations: to School of CS.

None

Grand Challenges will examine relevant research literature and contains a project component but is not formally part of the small group discovery experience.

The assessment for this course consists of the following weightings:
Exam – 20%
Project 1 – 20%
Project 2 – 40%
Written report on an existing challenge – 10%
Course Improvement Reports (1 and 2): 10% (5% each)

In order to pass, students must achieve an overall passing grade and not 
score less than 40% in all of the Exam, Project 1 and Project 2. The Course Improvement Reports are not part of the minimum performance requirement.

The projects are weighted as above, with the following breakdown of marks within the projects (based on the weights as listed in 5.1).

• Project 1 Pitch: Formative, 10%, learning objective 1,2,3,4,5
• Project 1 First cut demo: Formative, 20%, learning objectives 3,4,5
• Project 1 Feedback Report: Formative, 20%, learning objective 1,3,5.
• Project 1 Final Submission: Summative, 25%, learning objective 1,2,3,4,5
• Project 1 Final Report: Summative, 25%, learning objective 1,3,5

• Project 2 Pitch: Formative, 10%, learning objective 1,2,3,4,5
• Project 2 Progress Report: Formative, 0%, learning objective 1,3,5
• Project 2 First cut demo: Formative, 25%, learning objectives 3,4,5
• Project 2 Feedback Report: Summative, 10%, learning objective 1,3,5
• Project 2 Final Submission: Summative, 30%, learning objective 1,2,3,4,5
• Project 2 Final Report: Summative, 25%, learning objective 1,3,5
• Course Improvement Report 1: Summative, learning objective 1,2,3,4,5
• Course Improvement Report 2: Summative, learning objective 1,2,3,4,5

Due Dates: The assignment due dates will be made available on the course website.

All programming assignments will be submitted via the school's Web Submission gateway, available from the school web page (http://www.cs.adelaide.edu.au). Other materials may be submitted to the school's Moodle forums (http://forums.cs.adelaide.edu.au).
Both electronic systems provide cover sheets for submitted work. No physical submissions of work will be accepted unless specifically requested by the lecturer - all other submissions will be electronic. Students are strongly advised to keep copies of any electronic work that they submit, if they are entering text into fields without a receipted copy.

The School of Computer Science observes a strict lateness policy. Your mark is capped by an additional 25% for each day late. 1 day late and your maximum mark can now only be 75%. 2 days late, 50%, 3 days late, 75%. Any submission beyond this point attracts no marks. Days are calculated from the time of hand-in, hence, if a hand-in is due at midnight, 12:01am is 1 day late. 
Extensions may be requested in advance for medical or compassionate reasons but (1) all requests must be accompanied by documentation, (2) extensions awarded will be proportional to any days missed due to illness (sick for 1 day WITH a medical certificate will only get you a 1 day extension), (3) no extensions will be granted on the final day unless the issue is both severe and unforeseen, and (4) extensions are never granted because you have been busy, have managed your time poorly or are over-committed.
Extensions are only available for issues that are beyond your control or where you have carefully planned your time where you have a known conflict and, well enough in advance, discussed the matter and arranged an extension.
You will receive ongoing feedback on other matters throughout the course. Any written assignments will be marked and returned, where possible, within a two week period. Where your work is of a standard that would put you at risk of hitting the minimum performance criterion, we will attempt to identify you as an at-risk student early on and, if you have been putting in sufficient effort elsewhere, you may be given a chance to resubmit some work that will have the possibility of removing the MP block, although it will not improve your mark. Students who demonstrate a late hand-in pattern, or have intermittent hand- in completions, will be contacted and encouraged to change their planning patterns to achieve better results.
Obviously, students may choose to continue with their current patterns, with no other penalty than continuing the behaviour that has led to them achieving low marks. Students who achieve a final mark in the range of 45-49 will be automatically granted academic supplementary examinations if they have completed all required coursework. Students who achieve a final mark of 40-44 may be offered academic supplementary examinations, academic supplementary coursework or a combination of these but the offer is at the discretion of the academic staff. Students who have done very well in the exam but have completed little to no coursework will not be given an opportunity for redemption.