MODULE DETAILS
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Module 17: Algorithms
NOMINAL DURATION IN HOURS 2 weeks (24 hours total time commitment) This time commitment includes the structured activities, preparation reading, and attendance at each webinar, completing exercises, practical assessments and proctored assessments. It is also expected that students spend additional time on readings, personal study, independent research and learning, practicing on remote labs and required software and working on any projects and assignments. This module covers the basic fundamentals of algorithm and its use. |
MODULE PURPOSE |
The purpose of this module is for participants to gain an overview of the fundamentals of algorithms, how its represented and its uses. |
MODIFICATION HISTORY | Rev 4.0 |
PREREQUISITE AND/OR CO‑REQUISITE MODULES |
None
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ASSESSMENT STRATEGY |
METHODS OF ASSESSMENT Assessors should gather a range of evidence that is valid, sufficient, current and authentic. Evidence can be gathered through a variety of ways including direct observation, supervisor's reports, project work, structured assessments, samples and questioning. This will include short answer questions on the knowledge content, the use of remote and virtual labs, and writing tasks to apply the learning to academic tasks. CONDITIONS OF ASSESSMENT Assessors must:
Questioning techniques should not require language, literacy and numeracy skills beyond those required in this module. The candidate must have access to all tools, equipment, materials and documentation required. The candidate must be permitted to refer to any relevant workplace procedures, product and manufacturing specifications, codes, standards, manuals and reference materials. Assessments will be open book assessment and may be completed off campus. Invigilation software will be used for some assessments to ensure authenticity of work completed. Model answers must be provided for all knowledge-based assessments to ensure reliability of assessment judgements when marking is undertaken by different assessors. |
SUMMARY OF LEARNING OUTCOMES
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Learning Outcome 1
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Establish fundamental computing algorithms
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Assessment Criteria |
1.1 Identify the fundamentals features of computing algorithms |
1.2 Analyse the workings of basic algorithms | |
1.3 Determine elementary data structures | |
Learning Outcome 2 |
Identify and explain algorithm representation
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Assessment Criteria |
2.1 Identify and explain an algorithm using Pseudocode |
2.2 Explain an algorithm using flowcharts | |
2.3 Describe the use of UML diagrams | |
Learning Outcome 3 |
Describe the use of data structures |
Assessment Criteria | 3.1 Describe the use of arrays and binary trees |
3.2 Describe the use of tables and linked lists | |
3.3 Describe the use of stacks and queues | |
Delivery mode Online and/or face-to-face |
Software/Hardware Used
Software
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N/A
Hardware
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