This is introduced exclusively as a pilot study to trial the initial design of a new VCE Higher Ed study that Monash/Melbourne/VCAA are co-designing for introduction in 2015. For administrative reasons on the VCAA side, this trial needs to take place as part of an extension program in Semester 1. From 2015, the new study will be equivalent to a VCE Level 3/4 and stand by itself (i.e. not be an extension unit). It will comprise four full terms. FIT1042 is intended to trial materials from all four terms, i.e. a "horizontal cross section". The unit is intended to be offered once only (2014, Semester 1).

Corrected date of introduction to semester 1, 2014.

30/11/2017 - Unit disestablished at FEC 5/17 Item 7.3.

See reasons for introduction. The unit is closely related to FIT1029. It provides an introduction to Algorithmic Thinking but will not span the full breadth of algorithmic design patterns covered in FIT1029. Instead it will focus on graph/network algorithms and emphasize how algorithms are fundamental to solving real world problems.

Outcomes

At the completion of this unit students will have -

A knowledge and understanding of:

Developed the skills to:

Developed attitudes that enable them to:

Demonstrated the communication skills necessary to:

020109

Algorithms, recipes for solving a problem, are fundamental to computer science. While these are the formal foundation of computer programming they also exist independently of computers as systematic problem-solving procedures. This unit introduces algorithmics, the study of algorithms. It is not about programming and coding but rather about the design of systematic problem-solving procedures. The unit will not require any knowledge of a programming language and is very hands-on. Students will develop algorithms to solve a wide variety of different problems, working individually as well as together in groups and as a class.

Topics include: what is a computational problem and what is an algorithm; basic algorithmic structures; abstract data types; modular algorithm structure; recursion; problem-solving strategies for algorithm development; arguing correctness of an algorithm; arguing termination of an algorithm; understanding the efficiency of an algorithm; the algorithmic approach to intelligent problem solving and machine intelligence, limitations of algorithms, and alternative models of computation.

under discussion; most likely synchronous online delivery via the facilities of the Virtual Science School with teachers in the role of tutors in the remote classrooms

Examination (3 hours): 60%; In-semester assessment: 40%

2 hrs lectures/wk, 2 hrs tutorials/wk

Tutorials must follow lectures.

FIT; external: Melbourne University; selected Pilot Schools

This unit is only available to external students enrolled into an extension program. It cannot be taken as part of any Monash course.