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INST0001-Database Systems
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Module code/name |
INST0001/Database Systems |
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Academic year |
2023/24 |
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Term
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2 |
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Assessment title |
Coursework: a combination of group and individual work |
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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 briefdraws 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-basedorganisations, 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 obtainingan unfair academic advantage. Academic misconduct includes plagiarism, obtaining help from/sharing work with others bethey individuals and/or organisations or any other form. of cheating. Refer to Academic Manual Chapter 6, Section 9: StudentAcademic 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.
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Section |
Content |
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A |
Core information |
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B |
Assessment Brief and Requirements |
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C |
Module learning outcomes covered in this assessment |
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D |
Groupwork instructions (where relevant/appropriate) |
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E |
How your work is assessed |
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F |
Additional information
- Appendix 1
- Appendix 2
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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
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Submission time |
15:00 UK Time |
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Assessment is marked out of: |
100 |
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% weighting of this assessment within total module mark |
100% |
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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)
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Footnotes, tables and captions for tables, figures, diagrams, charts included in word count? |
Included in the word count |
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Bibliographies, reference lists, cover page, appendices, excluded from word count? |
Excluded from the word count |
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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. |
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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 |
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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. |
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Submitting your assessment |
Submission via the INST0001 Moodle space only. |
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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. |
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.
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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?
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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.
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