Department of Computer & Information Sciences

ASSESSMENT BRIEF
Module Title:	Data Fundamentals
Module Code:	KV4009
Academic Year / Semester:	2024-25 / Semester 2
Module Tutor / Email (all queries):	Yulei Li yulei.li@northumbria.ac.uk
% Weighting (to overall module):	50%
Assessment Title:	Written report on ethical, legal and security related issues concerning data and databases
Date of Handout to Students:	27^th January 2025
Mechanism for Handout:	Module Blackboard Site & Online Session
Deadline for Attempt Submission by Students:	4pm on 20^th March 2025
Mechanism for Submission:	Document upload to Turnitin.
Submission Format / Word Count	Please upload your written report as a single PDF or MS Word document. Your report should not exceed 2,000 words in length, not including the front cover, references, bibliography and appendices.
Date by which Work, Feedback and Marks will be returned:	17^th April 2025
Mechanism for return of Feedback and Marks:	Mark and written feedback will be uploaded to the Module Site on Blackboard. For further queries please email module tutor.

LEARNING OUTCOMES

The learning outcomes (LOs) for this module are:-

Knowledge & Understanding

MLO1 Understand the characteristics, strengths and limitations of current database systems.

MLO2 Demonstrate knowledge of information security issues and an awareness of tools and techniques used in implementing information security.

Intellectual / Professional skills & abilities

MLO3 Specify, design, implement and evaluate database solutions using appropriate tools.

ML04 Analyse and solve problems via data manipulation and information retrieval operations.

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA)

MLO5 Describe the ethical, legal and security related issues concerning the implementation and administration of databases and their management systems.

This assessment addresses learning outcomes MLO1, MLO2 and MLO5.

ASSESSMENT BRIEF

You are required to submit a 2,000-word report (+/- 10%) addressing 1–2 topics related to the ethical, legal, and security considerations in the use and management of data and databases.

Write this report as if you are advising your future manager, explaining the issues, why they matter, and how they can be addressed.

The report must demonstrate independent research and include a literature review, a discussion of challenges, and proposed solutions.

Report Structure:

Introduction [about 200 words]
- Background: Provide an overview of the chosen topic(s), explaining their relevance and importance within data and database management.
- Scope of the Report: Clearly outline the report’s focus, including the questions or problems to be addressed.
Literature Review and Challenges [about 1000 words]
- Current Landscape and Key Concepts: Discuss the chosen issue(s) in data management. Use relevant academic and industry literature.
- Problematic and Challenging Issues: While discussing the literature, integrate real-world cases or examples to highlight the consequences of these issues.

Note: Blend the literature review and discussion of challenges seamlessly.

Potential Solutions [about 600 words]
- Existing solutions for the chosen challenge(s): Summarise current approaches for addressing the identified challenges.
- Recommendations: Provide your own recommendations, detailing actionable steps or measures.
- Justification: Support your solutions with evidence from your literature review and/or practical examples.
Conclusion [200 words]
- Summarise the key points discussed in the report, highlighting the importance of addressing the challenges and the potential impact of the proposed solutions.

NATURE OF THE SUBMISSION REQUIRED:

The report should be submitted as a PDF or MS Word file. The cover page should include your student number and name. The file should be submitted to Turnitin.

SUBMISSION REQUIREMENTS

You must comply to the following criteria to fulfil the assignment submission requirements:

The word limit is 2000. However, if the assignment is within +10% (i.e., up to 200 words) then NO penalty will be applied.
The word count should be declared on the cover page of your assignment. The word count does not include title page, table of contents page, references and appendices and in text citations [e.g. (O’Brien, 2020)].

IF YOU NEED AN EXTENSION

Contact ask4Help. Tutors and Module tutors cannot grant extensions.

Make sure that your report is submitted on time. University regulations state that assignments submitted late without approval will incur a 10% reduction for the first 24hours then a zero mark after this.

You may apply for an extension of time to complete assessed coursework if there are personal circumstances which are unforeseen and unpreventable and have a serious effect on your ability to submit the work by the published hand-in deadline. You must submit an ‘Application for Authorisation for Late Submission of Assessed Work’ before the hand-in deadline. Appropriate medical certification, or other relevant evidence confirming the circumstances, must be provided. Information regarding this policy and procedure can be accessed through your student portal.

ACADEMIC MISCONDUCT

Assessment Regulations for Taught Awards (ARTA) contain the regulations and procedures applying to cheating, plagiarism and other forms of academic misconduct. The full policy is available here. You are reminded that plagiarism, collusion and other forms of academic misconduct as referred to in the Academic Misconduct procedure of the assessment regulations are taken very seriously. Assignments in which evidence of plagiarism or other forms of academic misconduct is found may receive a mark of zero.

USE OF AI:

Please refer to the student guidance below on how to use AI in this assignment.

STUDENTS WITH SAPS

Contact the module lead tutor about reasonable adjustments.

REFERENCING STYLE:

Where you have used words from someone else (quotations), they should be correctly quoted and referenced in accordance with the Northumbria Harvard System. You will be required to submit the report for the work via Turnitin.

APPENDIX A

Marking criteria

	Below 40%	40% – 49%	50% – 59%	60% – 69%	70%+
Introduction [10%]	Inadequate background information and unclear scope.	Basic background with a somewhat clear scope.	Adequate background and scope definition.	Comprehensive background with a clear, well-defined scope.	Exceptional and insightful background information with a highly focused and articulate scope.
Literature Review [30%]	Limited or no use of academic literature. Concepts poorly explained.	Some use of relevant literature. Basic explanation of key concepts.	Good use of literature. Clear explanation of concepts.	Very good use of academic literature. Thorough and accurate explanation of key concepts.	Excellent integration of a wide range of literature. Expert-level discussion and understanding of key concepts.
Problematic and Challenging Issues [25%]	Fails to identify key issues. No real-world examples.	Identifies only basic issues. Few real-world examples.	Identifies main issues with some real-world examples.	Clearly identifies all relevant issues with detailed real-world examples.	Exceptionally detailed identification of issues with insightful real-world examples.
Potential Solutions [25%]	No or irrelevant solutions. Lack of justification.	Basic solutions provided with minimal justification.	Adequate solutions with some justification.	Well-developed solutions with strong justification.	Innovative and exceptionally well-justified solutions.
Presentation of the Report [10%]	Poor formatting, numerous citation errors, disorganised references, weak grammar and style.	Some formatting issues, minor citation errors, somewhat organised references, basic grammar and style.	Good formatting, few citation errors, well-organised references, good grammar and style.	Very good formatting, minor citation errors, very well-organised references, very good grammar and style.	Excellent formatting, no citation errors, exceptionally organised references, outstanding grammar and style.

Using AI Responsibly and Ethically: A Guide for Students

AI tools like ChatGPT, Grammarly, and others can support your learning and improve your assessments. However, responsible and ethical use is essential. This guide outlines how to use AI appropriately while maintaining academic integrity.

Key Points About Using AI

Support, Not Substitute:
AI can assist with grammar, organising ideas, and providing suggestions, but the core content, analysis, and conclusions must always be your own. AI should not complete the primary tasks of your assessment unless explicitly allowed.
Acknowledge AI Use:
If you use AI, clearly state how and where you used it (e.g., for structuring, summarising, or proofreading). Transparency is a key part of academic integrity.
Verify Information:
AI can produce incorrect or fabricated information (known as “AI hallucinations”). It’s your responsibility to fact-check all content and sources.
University Policy:
Familiarise yourself with your university’s Academic Misconduct Policy to understand the rules around using AI.

How You Can Use AI in Assessments

Essays and Written Assignments:

Permitted Use: Organise ideas, draft structures, and check grammar or spelling.
Not Permitted: Submitting AI-drafted content or extensive editing by AI.
Support Research: Use AI to find relevant sources but verify their accuracy.

Presentations:

Permitted Use: Generate slide headings, suggest layouts, and plan presentation flow.
Not Permitted: Relying entirely on AI to create the presentation.

Projects and Portfolios:

Permitted Use: Plan tasks, set timelines, and get general guidance.
Not Permitted: Using AI for reflective content, which must demonstrate personal learning.

Coding Assignments:

Permitted Use: Debugging or error checking.
Not Permitted: Submitting AI-generated code as your own.

Always disclose AI assistance in your work.

How to Declare AI Use

Include a brief statement in your submission, such as:

“I used Grammarly to check for grammar and spelling mistakes.”
“I used ChatGPT to suggest a draft structure for my essay.”

Be prepared to provide additional details, such as the prompts you used, if required by your lecturer.

Academic Integrity and AI

When in Doubt, Ask: If your assignment brief doesn’t mention AI, check with your lecturer before using it.
Transparency: Declare AI usage in your work as you would reference other sources.
Avoid Misuse: Misusing AI can be considered academic misconduct.

The University Library provides advice on referencing AI in academic integrity sessions and support materials: Library Guidance on AI.

Key Reminders

Follow Guidelines: Check your assessment brief for specific rules about AI.
Be Transparent: Always acknowledge how you used AI.
Think Critically: Your work should reflect your own ideas and arguments.
Fact-Check AI Output: Ensure all AI-generated content is accurate and credible.

By using AI responsibly and ethically, you can enhance your work while maintaining academic integrity. If unsure, always consult your module tutor.

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