| Subject Code: | TECH6300 |
| Subject Name: | Algorithms and Data Structures |
| Assessment Title: | Presentation investigation |
| Assessment Type: | Presentation |
| Word Count: | 6 Minutes (+/-10%) |
| Weighting: | 20 % |
| Total Marks: | 20 |
| Submission: | Via MyKBS |
| Due Date: | Week 4 |
Your Task
In this assessment, you will investigate various data structures and abstract data types as outlined in LO1. You will do an in-class presentation, investigating various data structures and abstract data types.
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Assessment Description
Prepare a presentation investigating data structures and abstract data types. Analyse their theoretical foundations, design principles, and implementation considerations. Evaluate their applicability in solving complex computational problems. Provide a detailed analysis of their performance, trade-offs, and potential optimisations. Your presentation should demonstrate advanced knowledge and critical thinking skills in the field of data structures and abstract data types. Your presentation must include slides, with the following slide headings:
(1) Introduction
(2) Data Structures Overview
(3) Importance of Data Structures
(4) Data Structures Operations
(5) Investigating Different Data Structures
(6) Conclusion
This assessment aims to achieve the following subject learning outcomes:
| LO1 | Investigate data structures and abstract data types. |
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Assessment Instructions
Students must conduct research externally and included references to produce a well referenced assessment. You should use at least ten (10) sources of information and reference these correctly, using your chosen referencing style (note the ASC team can assist you with Kaplan Harvard Referencing). These references may include websites, social media sites, industry reports, census data, journal articles, and newspaper articles. They should be presented as in-text citations and a referencing list at the end of your assessment. Wikipedia and other ‘popular’ sites are not to be used.
1. You must present your presentation in-class at week 4.
2. The presentation should exhibit depth and sophistication in discussing data structures and abstract data types.
3. It should demonstrate a comprehensive understanding of the theoretical foundations and practical aspects.
4. Analyse the design principles and implementation strategies for different data structures and abstract data types.
5. Evaluate their strengths, weaknesses, and trade-offs in solving complex computational problems.
6. Provide insights into optimising data structures and abstract data types for specific scenarios.
7. Use scholarly references to support your analysis and provide a well-rounded perspective.
8. Present your ideas in a logical and coherent manner, adhering to academic writing conventions.
9. Please refer to the assessment marking guide to assist you in completing all the assessment criteria.
Page 4 Kaplan Business School Assessment Outline
Important Study Information
Academic Integrity and Conduct Policy
https://www.kbs.edu.au/admissions/forms-and-policies
KBS values academic integrity. All students must understand the meaning and consequences of cheating, plagiarism and other academic offences under the Academic Integrity and Conduct Policy.
Please read the policy to learn the answers to these questions:
• What is academic integrity and misconduct?
• What are the penalties for academic misconduct?
• How can I appeal my grade?
https://www.kbs.edu.au/admissions/forms-and-policies
Length Limits for Assessments
Penalties may be applied for assessment submissions that exceed prescribed limits.
Study Assistance
Students may seek study assistance from their local Academic Learning Advisor or refer to the resources on the MyKBS Academic Success Centre page. Further details can be accessed at
https://elearning.kbs.edu.au/course/view.php?id=1481
Page 5 Kaplan Business School Assessment Outline
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Generative AI Traffic Lights
Please see the level of Generative AI that this assessment is Level 2 has been designed to accept:
| Traffic Light | Amount of Generative Artificial Intelligence (GenerativeAI) usage | Evidence Required | This assessment (✓) |
| Level 1 | Prohibited:No GenerativeAI allowedThis assessment showcases your individual knowledge, skills and/or personal experiences in the absence of Generative AI support. | The use of generative AI is prohibited for this assessment and may potentially result in penalties for academic misconduct, including but not limited to a mark of zero for the assessment. | |
| Level 2 | Optional:You may use GenerativeAI for research and content generation that is appropriately referenced.See assessment instructions for detailsThis assessment allows you to engage with Generative AI as a means of expanding your understanding, creativity, and idea generation in the research phase of your assessment and to produce content that enhances your assessment. I.e., images. You do not have to use it. | The use of GenAI is optional for this assessment.Your collaboration with GenerativeAI must be clearly referenced just as you would reference any other resource type used. Click on the link below to learn how to reference GenerativeAI.https://library.kaplan.edu.au/referencingother-sources/referencing-other-sourcesgenerative-aiIn addition, you must include an appendix that documents your GenerativeAI collaboration including all prompts and responses used for the assessment.Unapproved use of generative AI as per assessment details during the content generation parts of your assessment may potentially result in penalties for academic misconduct, including but not limited to a mark of zero for the assessment. Ensure you follow the specific assessment instructions in the section above. | ✓ |
| Level 3 | Compulsory:You must use GenerativeAI to complete your assessmentSee assessment instruction for detailsThis assessment fully integrates Generative AI, allowing you to harness the technology's full potential in collaboration with your own expertise.Always check your assessment instructions carefully as there may still be limitations on what constitutes acceptable use, and these may be specific to each assessment. | You will be taught how to use generative AI and assessed on its use.Your collaboration with GenerativeAI must be clearly referenced just as you would reference any other resource type used. Click on the link below to learn how to reference GenerativeAI.https://library.kaplan.edu.au/referencingother-sources/referencing-other-sourcesgenerative-aiIn addition, you must include an appendix that documents your GenerativeAI collaboration including all prompts and responses used for the assessment.Unapproved use of generative AI as per assessment details during the content generation parts of your assessment may potentially result in penalties for academic misconduct, including but not limited to a mark of zero for the assessment. Ensure you follow the specific assessment instructions in the section above. |
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