91636 Sample Specific Assessment Guide
Level 3 Digital Technologies 91636 (3.44)
Specific Assessment Guides
Complexity and Tractability: 14
Formal Languages: 58
Graphics and Visual Computing: 912
Intelligent Systems: 1316
Network Communication Protocols: 1720
Software Engineering: 2124
Level 3 Digital Technologies 91636 (3.44) Specific Assessment Guide
(Complexity and Tractability)
TitleDemonstrate understanding of areas of computer science
Technology assessment guides have been produced to help teachers develop their own specific assessment guides. Examples of specific assessment guides, developed from the common assessment guide for each standard, have been produced as part of the external assessment resources for level 3 Technology.
The specific assessment guides also show a variety of ways (ie case study, research, practice) to produce external assessment material. The material in the candidate exemplars for each standard reflects the content and context of the specific assessment guides.
Teachers can adapt a common assessment guide and / or a specific assessment guide to suit the specific context of their course of teaching.
You will produce a report that demonstrates understanding of areas of computer science. To complete the report you will need to report on at least two of the Areas of Computer Science from explanatory note 3 in the standard.
This specific assessment guide is one of six. Each one of the specific assessment guides relate to one of the six Areas of Computer Science.
Candidate guidance for producing the report
There are some prompts and activities below that will assist you to write the part of your report on complexity and tractability. They will help you to produce a report that demonstrates the understanding expected in this assessment. The prompts also define the levels of description, explanation, and discussion that are expected at each grade.
To demonstrate understanding of areas of computer science at the Achieved level you will need to:
describe key problems that are addressed in selected areas of computer science
describe examples of practical applications of selected areas to demonstrate the use of key algorithms and/or techniques from these areas.
To demonstrate in-depth understanding of areas of computer science at the Merit level you will need to:
explain how key algorithms or techniques are applied in selected areas
explain examples of practical applications of selected areas to demonstrate the use of key algorithms and/or techniques from these areas.
To demonstrate comprehensive understanding of areas of computer science at the Excellence level you will need to:
discuss examples of practical applications of selected areas to demonstrate the use of key algorithms and/or techniques from these areas
evaluate the effectiveness of algorithms, techniques, or applications from selected areas.
The activities below are activities which generate specific content that you can use to develop your report. For example, if you were to investigate TSP (see activity 6 below) you could generate information related to several parts of the report.
1. Evaluate how much time is needed to solve the TSP, and evaluate approximate solutions (such as nearest neighbour first).
2. Investigate the graph colouring problem; a sample plan for this is at Computing Inside's Graph Colouring Activity, as well as the CS Unplugged's map colouring activity. It can be done online at http://gwydir.demon.co.uk/jo/games/puzzles/map.htm.
3. Investigate the (intractable) Travelling Rock Band problem.
4. Investigate the knapsack problem, and evaluate approximate solutions (such as decreasing order).
5. Investigate the bin-packing problem, and evaluate approximate solutions (such as the first-fit algorithm).
6. Investigate the progress researchers have made over the years finding improvements to algorithms for solving a particular problem (eg TSP, primality testing).
7. Compare different algorithms with a variety of complexities for the same problem, particularly for large values of $n$, considering issues like how well they scale and how much memory they use.
8. Compare the speed of bogosort (an exponential time algorithm) with a conventional sorting algorithm (such as quicksort).
9. Estimate the work involved for a computer to evaluate all possible timetabling options for your school.
The achievement standard governing this specific assessment guide can be found athttp://www.nzqa.govt.nz/nqfdocs/ncea-resource/specifications/2013/level3/91636-spc-2013.pdf
The assessment specifications for the Digital Technologies achievement standard can be found athttp://www.nzqa.govt.nz/nqfdocs/ncea-resource/achievements/2013/as91636.pdf
The following are concepts, algorithms, techniques, applications, and problems that students at level 3 are likely to be able to work with; it is not a list of all the key ideas in the area.
Key concepts likely to be encountered are: complexity, exponential time complexity, polynomial time complexity, tractability, asymptotic complexity, big O notation, P and NP, and NP-complete problems.
Algorithms: there are many hundreds of algorithms that illustrate these issues; suitable intractable problems include the travelling salesperson problem (TSP), Hamiltonian path, graph colouring, vertex cover, Sudoku, and longest path; contrasting tractable problems include the Eulerian path, minimal spanning tree, and shortest path. Standard sorting or searching algorithms are excellent for exploring the concept of complexity; bogosort and bozosort can be explored as (artificial) examples of intractable algorithms.
Techniques: empirical evaluation, analysis, brute force algorithm, heuristic algorithms.
Applications: these include route planning, timetabling, optimisation, games, and encryption.
Complexity and tractability is about the relationship between problems and their algorithms, and the idea that some common problems do not have tractable solutions. This falls in the area of computational complexity theory. The focus is on the inherent complexity of a problem, that is, the time needed to solve a problem, and the best known algorithms for the problem. This area includes what is widely regarded as the largest unsolved problem in computer science: the question of whether P = NP (the details of this issue are beyond high school level, but the explorations that can be performed at high school level will give an understanding of why this is such a significant problem). The demonstration of understanding in this area can be done by describing problems with known inherent complexities (both tractable and intractable) and those for which the complexity is an open question; by illustrating the issues surrounding intractable (exponential time) algorithms; by exploring the limits on what can be done with intractable problems (such as the various records that have been set for solving the TSP); by comparing heuristic solutions that give sub-optimal solutions; and by exploring the quest to find reasonable time algorithms for those that currently only have exponential time solutions, including recent discoveries about open questions in this area.
Further information can be found at http://www.techlink.org.nz.
Please read the exemplars. You can model your work on these exemplars but you may not copy the material from the exemplars. Your report must be the product of your own efforts.
AS Digital Technologies 91636 (3.44)
Demonstrate understanding of areas of computer science
Final grades will be decided using professional judgement based on a holistic examination of the evidence provided against the criteria.
Issues from the Specifications
Authentic candidate submissions will be recognisable because of specific contexts associated with the work. This does not imply that submissions will arise only from the candidates practice. However, where the candidates practice does not provide the immediate source of a specific context, one would expect to see that several sources of information relating to materials had been applied within a specific context. In both cases, the marker will be able to detect the candidates voice. In situations where information does not have some aspect of student voice, it is difficult to establish whether the candidate has actually demonstrated understanding or simply identified information.
Candidates who have simply identified information by reproducing information from sources without making use of that information have not demonstrated understanding.
Where a candidate has provided a brief answer, the answer should not be penalised because of length.
Candidate work in excess of 14 pages should not be marked.
Where work is illegible, it cannot be marked.
Digital submissions that cannot be read cannot be marked.