代写INST0001/Database Systems代做留学生SQL 程序

日期：2024-04-05 04:41

Assessment Brief

Module code/name	INST0001/Database Systems
Academic year	2023/24
Term	2
Assessment title	Coursework: a combination of group and individual work
Individual/group assessment	Group and Individual

Submission deadlines: Students should submit all work by the published deadline date and time. Students experiencing sudden or unexpected events beyond your control which impact your ability to complete assessed work by the set deadlines may request mitigation via the extenuating circumstances procedure. Students with disabilities or ongoing, long-term conditions should explore a Summary of Reasonable Adjustments.

Return and status of marked assessments: Students should expect to receive feedback within one calendar month of the submission deadline, as per UCL guidelines. The module team will update you if there are delays through unforeseen circumstances (e.g. ill health). All results when first published are provisional until confirmed by the Examination Board. 

Copyright Note to students: Copyright of this assessment brief is with UCL and the module leader(s) named above. If this brief draws upon work by third parties (e.g. Case Study publishers) such third parties also hold copyright. It must not be copied, reproduced, transferred, distributed, leased, licensed or shared any other individual(s) and/or organisations, including web-based organisations, without permission of the copyright holder(s) at any point in time.

Academic Misconduct: Academic Misconduct is defined as any action or attempted action that may result in a student obtaining an unfair academic advantage. Academic misconduct includes plagiarism, obtaining help from/sharing work with others be they individuals and/or organisations or any other form. of cheating. Refer to Academic Manual Chapter 6, Section 9: Student Academic Misconduct Procedure - 9.2 Definitions.

Referencing: You must reference and provide full citation for ALL sources used, including articles, text books, lecture slides and module materials.  This includes any direct quotes and paraphrased text.  If in doubt, reference it.  If you need further guidance on referencing please see UCL’s referencing tutorial for students. Failure to cite references correctly may result in your work being referred to the Academic Misconduct Panel. Use Harvard style. for all referencing.

Use of Artificial Intelligence (AI) Tools in your Assessment: Your module leader will explain to you if and how AI tools can be used to support your assessment. In some assessments, the use of generative AI is not permitted at all. In others, AI may be used in an assistive role which means students are permitted to use AI tools to support the development of specific skills required for the assessment as specified by the module leader. In others, the use of AI tools may be an integral component of the assessment; in these cases the assessment will provide an opportunity to demonstrate effective and responsible use of AI. See page 3 of this brief to check which category use of AI falls into for this assessment. Students should refer to the UCL guidance on acknowledging use of AI and referencing AI. Failure to correctly reference use of AI in assessments may result in students being reported via the Academic Misconduct procedure. Refer to the section of the UCL Assessment success guide on Engaging with AI in your education and assessment.

Content of this assessment brief

Section	Content
A	Core information
B	Assessment Brief and Requirements
C	Module learning outcomes covered in this assessment
D	Groupwork instructions (where relevant/appropriate)
E	How your work is assessed
F	Additional information - Appendix 1 - Appendix 2

Section A: Core information

Submission dates	Pre-requisites for self-assessment of the critical report:   Formative submissions: 07/02/24 - group members, chosen charity and SDGs, 21/02/24 - draft group report and SQL data dump, 13/03/24 - individual report progress.   Summative submissions (final edit - 12/03/24): Tues, 26/03/2024 – 50% Group work Tues, 26/03/2024 – 50% Individual work
Submission time	15:00 UK Time
Assessment is marked out of:	100
% weighting of this assessment within total module mark	100%
Maximum word count/page length/duration	Group work: 1,500 words maximum (including a 10% leeway). Individual work: 1,000 words maximum (including a 10% leeway).
Footnotes, tables and captions for tables, figures, diagrams, charts included in word count?	Included in the word count
Bibliographies, reference lists, cover page, appendices, excluded from word count?	Excluded from the word count
Penalty for exceeding word count/page length	Penalty for exceeding word count will be a deduction of 10 percentage points, capped at 40% for Levels 4,5, 6, and 50% for Level 7) Refer to Academic Manual Section 3: Module Assessment - 3.13 Word Counts.
Penalty for late submission	Standard UCL penalties apply. Students should refer to Refer to https://www.ucl.ac.uk/academic-manual/chapters/chapter-4-assessment-framework-taught-programmes/section-3-module-assessment#3.12
Artificial Intelligence (AI) category	Category 2: AI tools can be used in an assistive role. For this assignment, this means that you can use AI for: · structuring content; · acting as a support tutor;  · giving feedback on content, or proofreading content within the grounds permitted in the Academic Manual (9.2.2b). While you may use AI tools as an assistant, the intellectual or technical work should be your own and you need to clearly acknowledge how and where you have used generative AI. Any student use of Generative Artificial Intelligence (GenAI) tools that exceeds that permitted in the assessment brief will be subject to academic misconduct procedures.
Submitting your assessment	Submission via the INST0001 Moodle space only.
Anonymity of identity. Normally, all submissions are anonymous unless the nature of the submission is such that anonymity is not appropriate, illustratively as in presentations or where minutes of group meetings are required as part of a group work submission	The nature of this assessment is such that anonymity is required.

Section B: Assessment Brief and Requirements

1. Introduction:

The main objective of the assignment is to translate the operational needs of a chosen organisation into a scalable data strategy as a team, where each member has unique needs from a shared database.

This assessment involves designing and developing a database for a charity, selected from a provided list.

The coursework is divided into two components: group work and individual work. The group work requires translating your group’s understanding of the operational challenges faced by a chosen charity and translating these into a shared database system. Individual group members, however, are required to focus on a specific operational challenge, which corresponds to one of the UN’s Sustainable Development Goals (SDGs). Within a group, each student is expected to choose a different SDG.

For example, the group may select Save the Children charity. Save the Children's core business operations are around providing humanitarian assistance and development programs to improve the well-being of children worldwide. This includes delivering healthcare services, ensuring access to education, promoting child protection, responding to emergencies, and advocating for policies that benefit children's rights. Therefore, each of the three students would focus on a different SDG e.g., SDG1 (No Poverty), SDG2 (Zero Hunger) or SDG4 (Quality Education).

Individual work should identify SDG data indicators (see Annex 5: Detailed Description of Proposed Indicators and Monitoring Framework) that would enable monitoring progress/regress in the chosen SDG.

For example, if the individual working on the Safe the Children charity focuses on SDG4 (Quality Education), you may focus on monitoring Indicator 35 (i.e. Secondary completion rates for girls and boys). You can then focus on capturing educational completion rates disaggregated by income, disability, or regional conflicts. Your database will then allow to monitor disaggregated trends over time.

2. Group Work: Further Details 

2.1. Form. a Group:

· Groups should consist of three students, that belong to the same Thursday tutorial group (i.e. Group A, B or C). If you fail to form. a group by the given date, you will be assigned into a group randomly. Each group must choose a unique charity registered at the Charity Commission from England and Wales. You can use the Advanced Search option to explore the list of charities. Your choice of charity will be approved on a first-come, first-served basis. Therefore, make your choice early to avoid disappointment.

· Identify and finalise your group members, chosen charity and SDGs by 07/02/24 (Wednesday) via Moodle using this link (Assignment Group Choice: Group 1/2/3). 

2.2. Start the group work.

2.2.1. Database Schema Design and Development:

· Collaboratively design a conceptual model and logical schema for the chosen charity’s database. You will need to collectively provide:

a) Up to 300 words introducing and justifying your chosen charity and its main operations;

b) An ER diagram reflecting the key data components of its operations;

c) A more detailed, logical schema presented diagrammatically and implemented in MySQL, which shows context-specific data integrity considerations. These may include considerations of: primary/foreign keys, statement of constraints or domains and/or data permissions. 

2.2.2. Sample Data and Normalisation:

· Populate the database with synthetic data (for example, from a flat file). You can consider including around 10 rows of data, but you may choose to include as much data as necessary to demonstrate your work effectively. It may be helpful to start with having less than ten attributes.

· Using examples from your flat synthetic data, demonstrate how your database tables meet the requirements of 3NF. Clearly demonstrate the steps of your normalisation process.

2.3. Write a Group Report. Your report should discuss the above group work and extend the discussion to include:

· Requirement Collection and Analysis for the chosen charity,

· Limitations and Future Work, and

· References

· Submit a draft (of around 1,000 words) showing your group’s progress on 2.2 and 2.3 by 21/02/24 via Moodle using this link (). Include the MySQL database backup (mysqldump) of the created database as a plain text file.

Note: This submission will not be assessed, but it will give you a chance to ask for feedback during the following practical session.

3. Individual Work: Further Details

The requirements of individual group members should feed into the group work. However, students are asked to submit an individually written report to complement their group submission.

· Write an individual report. The report should:

- discuss the chosen SDG, and a problem that you are trying to address individually through the chosen monitoring indicators;

- provide justifications around the database design and development related to the chosen SDG;

- include details of MySQL implementation and testing; and

- provide a reflective account on your learning journey. 

· Submit a draft showing your individual progress by 13/03/24 via Moodle using this link (Formative: Individual Report Progress).

Note: This will not be assessed, but it will give you a change to ask for feedback during the following practical session. Please do not exceed 700 words.

4. Final Submission Deliverables

4.1. Group Submission:

· Report including ER diagram, database schema (with details of normalisation), SQL scripts for database creation, and sample data. Include additional explanations and examples as needed for your specific case study and demonstrate the extent of your work by supplementing it with screenshots.

· MySQL database backup (mysqldump) of the created database as a plain text file.

· Submission Deadline: 26/03/24 using this link (Group Work Submission)https://moodle.ucl.ac.uk/mod/assign/view.php?id=5162020 

4.2. Individual Submission:

· Report detailing your: individual work around the chosen SDG and monitoring indicators, development and testing towards the chosen SDG, and reflections on  your learning.

· An appendix that includes: MySQL queries used in the report around the chosen SDG as a text, supplemented with screenshots of these query results. This appendix would not be included in your main report’s wordcount and page limit.

· Submission Deadline: 26/03/24 using this link (Individual Work Submission)

Section C: Module Learning Outcomes Covered

This assignment contributes towards the achievement of the following stated module Learning Outcomes as highlighted below: 

· Understand the dominant database paradigms available today, their strengths, weaknesses, and application examples.

· Extract requirements for, design and specify a relational database using standard notation and methodologies.

· Apply normalisation techniques on data.

· Implement, modify, and query a database solution using standard tools such as MySQL.

· Explain the major issues around database administration.

Section D: Groupwork instructions (where relevant/appropriate)

Groupwork Guidelines: · We encourage all groups to keep a log of all meetings. These would include group work decisions, progress, and outcomes. · We encourage an early assessment project start and proactive feedback request on your weekly progress during our Lab Sessions. · If there are any issues you experience as a group or individually seek support from the teaching team immediately. Additional Guidelines: Use the following checklist to help you assess your progress. 1. Does this project show an understanding of the relationship between business decision-making and systematic data management? 2. Is there evidence of a working understanding of the most dominant database paradigm available today with a relevant application example? 3. Have relevant issues of database administration been considered? 4. Is there a reflection on the inherent strengths and limitations of the proposed data architecture and information organisation? 5. Is there evidence of both: a. collaborative problem-solving and balanced teamwork? b. independent learning and self-reflection?

Section E: How your work is assessed

Assessment Criteria are provided in Section F. Institutional Policies and General Information: The process of confirming the mark will be reviewed/scrutinised by an internal assessor. This will be made available to an External Examiner for further review/scrutiny before consideration by the relevant Examination Board. To help you assess the relative strengths and weaknesses of your submission, please refer to UCL Assessment Criteria Guidelines, located at https://www.ucl.ac.uk/teaching-learning/sites/teaching-learning/files/migrated-files/UCL_Assessment_Criteria_Guide.pdf  You may consult Level 5 Assessment Criteria from the generic UCL Guide. Please note that these generic assessment criteria are intended to serve as indicative and complementary guidelines to the primary criteria outlined in this assessment brief. They can be particularly helpful for understanding grade boundaries, which are as follows: 85% or higher, 70% to 84%, 60% to 69%, 50% to 59%, 40% to 49%, and below 40%. Students who wish to request a review of a decision made by the Board of Examiners should refer to the UCL Academic Appeals Procedure, taking note of the acceptable grounds for such appeals. Note that the purpose of this procedure is not to dispute academic judgement – it is to ensure correct application of UCL’s regulations and procedures. The appeals process is evidence-based and circumstances must be supported by independent evidence. Institutional Policies on the Use of Generative AI Students are permitted to use AI tools for as assistive role within the assessment. The use of AI is not in itself a learning outcome. The use of generative AI must be acknowledged and detailed in the references section of the submitted report. There will be some aspects of the assessment where the use of AI is inappropriate, and you should seek clarity from tutor when in doubt. The use of generative AI must be acknowledged in the References section. The minimum requirement to include in acknowledgement: · Name and version of the generative AI system used; e.g. ChatGPT-3.5 · Publisher (company that made the AI system); e.g. OpenAI · URL of the AI system. · Brief description of context in which the tool was used and how. The References section of your report is excluded from the word count, enabling you to provide as much context with regards to the use of AI as you find necessary.