Level 3 Digital Technologies 91636 44) Common Assessment Guide
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- Credits 4 Teacher introduction
- Candidate guidance for producing the report
- Network communication protocols
- Complexity and tractability
- Graphics and visual computing
- Assessment Schedule AS Digital Technologies 91636 (3.44)
- Issues from the Specifications
- Achievement Achievement with Merit Achievement with Excellence
Level 3 Digital Technologies 91636 (3.44) Common Assessment Guide — page of 5
Title Demonstrate understanding of areas of computer science Credits 4
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 have been developed in a range of the contexts in which technology is practised. 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 their own context. For this standard students will need to choose two (or more) of the six areas of computer science listed in the standard. Ideally they will be given an overview of each of the areas, and then choose two that particularly interest them, or that are of local interest. For each area, the common assessment guide gives the scope of the topic, and the specific assessment guide defines the particular algorithms, techniques, and applications that are relevant to producing a report at level 3 of the curriculum. The specific assessment guide also gives some ideas for how students at high school level can engage with the topic. All of these topics are also the subject of advanced university courses, and students are not expected to be working on them at this level, and should be warned not to be daunted if they come across advanced lectures, books, or encyclopaedia entries about the topic. They should focus on the kind of activities suggested in the guide, as the goal is for them to understand the main issues surrounding the topic, and to appreciate the kind of skills and knowledge that would be required to investigate the topic in detail. The common assessment guide gives generic rubrics that could be used for any of the six areas; however, it could be adapted for specific activities for the chosen areas – for example, some areas have techniques rather than algorithms and it is distracting to mention algorithms. Many of the activities don’t take students through the process in the sequence of the rubrics, and it is generally better to use the rubric as a guide rather than a sequence of instructions. Note that the student’s project is likely to state some basic facts that will be common to almost any project on the topic, but it is the student’s personalised examples that will demonstrate their understanding of the area.
You will produce a report that demonstrates understanding of areas of computer science.
This assessment guide must be read along with the achievement standard and the assessment specifications. The prompts provided below are guides to producing a report that demonstrates understanding of complex concepts from computer science. The prompts guide candidates to produce evidence for all grades of the standard – Achievement, Merit, and Excellence. It is not necessary to respond to all prompts to succeed at any level. The later prompts guide candidates to in-depth discussion. Each report will be assessed overall as to the level of understanding the report demonstrates of areas of computer science. Your report should focus on at least two of the six areas of computer science in the standard. To demonstrate understanding of areas of computer science at the achieved level you will need to describe:
To demonstrate in-depth understanding of areas of computer science at the merit level you will need to explain:
To demonstrate comprehensive understanding of areas of computer science at the excellence level you will need to:
The definitions below clarify the appropriate scope and focus of each of the six topics for this standard. The specific assessment guide gives details for each area defining algorithms, techniques, and applications that are relevant to producing a portfolio at level 3 of the curriculum.
The achievement standard governing this common assessment guide can be found at http://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 at http://www.nzqa.govt.nz/nqfdocs/ncea-resource/achievements/2013/as91636.pdf
The following definitions might be useful when you are writing your report. Concepts from computer science are formal languages, network communication protocols, complexity and tractability, intelligent systems, software engineering, and graphics and visual computing. Formal languages is about how to specify programming, mark-up, and other languages for computing, and systems that can parse and process programs or documents written in such languages. They are specified by formal representations such as syntax diagrams (“railroad diagrams”), grammars, regular expressions and finite state machines. The language could be a conventional programming language (such as Java, Python, C, or Basic), another formal language with a strict syntax (such as XML, HTML or SQL), or the focus could be on regular expressions and lexical analysis (such as detecting a well formed identifier or number in a programming language, or a string matching a given pattern). Most programming languages have very large formal definitions, and it would be sufficient to demonstrate understanding using a part of a language, such as expressions in a programming language, or a small selection of different kinds of tags in HTML. The demonstration would typically be done by using examples to show the parse tree (or syntax tree) for a correct and incorrect program fragment, or to show a sequence of grammar productions to construct a correct program fragment, or to show strings generated by a simple Regular Expression and accepted by a finite state machine that corresponds to it. Network communication protocols focus on the techniques applied in computer networks to ensure reliable communication of data between two parts of a network in the face of different kinds of threats and failures. The project would typically be done by giving examples of the sequence of events that occur in these situations, discussing how the protocols and their coding schemes overcome the problems, and evaluating how successful they are at addressing them. This topic is distinct from the coverage of networking in the infrastructure standards because it focuses on the issues that the protocols address (ie the design of the protocol), rather than how to configure a system that uses a given protocol. Complexity and tractability is about the relationship between problems and their algorithms, and the idea that some common problems don’t 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. Intelligent systems are systems that exhibit aspects of human intelligence in their interaction with their users or environment. Engineering such systems and the study of theoretical and practical issues surrounding them is the subject of the field of artificial intelligence (AI). AI is primarily a branch of computer science. But it has borrowed a lot of concepts and ideas from other fields, such as biology, psychology, neuroscience and philosophy. AI has borrowed especially from mathematics – particularly logic, combinatorics, statistics, probability, and optimisation theory. This area can be explored by experimenting with existing AI systems, such as on-line chatbots, decision systems, machine learning systems, search engines, machine translation, spam detectors, video game bots, and object recognition (e face detection) systems. There is a lot of opportunity for exploring predictions and ethical debates regarding intelligent systems, such as the concept of the singularity, Moravec’s Paradox, Searle’s Chinese Room, and the value of the Turing test; these have some bearing on this concepts in this standard, but could be explored as part of a separate generic standard relating to ethics or the effect of technology on society. Software engineering is about systematic approaches applied to large software projects, typically with many team members and large amounts of program code, so that the products behave reliably and efficiently, are affordable to develop and maintain, and satisfy customer requirements. This area can be explored by learning about common software engineering methodologies (including examples of “plan-driven” and “agile” approaches) and the different roles and skills required in a software engineering project, particularly analysis, development, testing and maintenance. Understanding can be demonstrated by doing case studies of software projects through interviews with software engineers, researching reports about successful and unsuccessful projects, running a simulation of a software engineering project, or reflecting on teamwork experiences that simulate the issues that arise in software engineering. The report should discuss the main issues and compare different approaches in the context of commercial projects that involve multiple team members. This topic is distinct from the programming standards because it explores large systems developed by teams of people; participating in such a project is way beyond the scope of Level 3 work, and the expectation is that students will review commercial or simulated projects, rather than run one themselves. Graphics and visual computing is about using computers to create images and animations based on a description of a scene or collected data (computer graphics and visualisation), and the reverse process of processing images and recognising elements in an image (computer vision). Often the term “visual computing” encompasses computer graphics, so the term “graphics” isn’t strictly required in the name of this area; also note that in this context is does not refer to the use of “visual programming languages” or “visual programming environments” eg Visual Studio. The creation of images could be as simple as a 2D drawing program, or as advanced as 3D systems for entertainment or to help visualise a data set. Computer vision is used to capture information from the real world or to recognise situations such as a potential vehicle collision. These topics can be explored by evaluating the effectiveness of existing software for these purposes, and exploring algorithms and techniques for rendering images and recognising the contents of an image. This topic is distinct from the standards that explore the use of multimedia software as it explores the details of how that software works.
Further information can be found at http://www.techlink.org.nz. Appropriate reference information is available in:
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.
Directory: nqfdocs -> ncea-resource -> schedules -> 2013 nqfdocs -> Nzqa registered unit standard 22528 version 2 nqfdocs -> Nzqa registered unit standard 26968 version 1 nqfdocs -> Nzqa registered unit standard 10212 version 5 nqfdocs -> Nzqa expiring unit standard 11867 version 7 nqfdocs -> Nzqa expiring unit standard 6862 version 5 nqfdocs -> Nzqa expiring unit standard 2780 version 8 2013 -> Level 3 Digital Technologies 91636 44) Specific Assessment Guides Complexity and Tractability: 1–4 Formal Languages: 5–8 Graphics and Visual Computing: 9–12 Intelligent Systems: 13–16 Network Communication Protocols: 17–20 Software ncea-resource -> Number as91076 Version ncea-resource -> Number as91075 Version Download 30.63 Kb. Share with your friends:
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