NBS8062 Research Methods: Dissertation Research Proposal Assessment Brief 2026 | Newcastle University
| Assessment Type | Research Proposal |
|---|
Assessment Brief – NBS8062
Module Code: | NBS8062 |
Module Title: | Research Methods |
Assessment Type: | Research Proposal |
Submission Date: | 8th May, 2026 |
Submission Time: | 12pm GMT |
Submission Method: | Online via Canvas |
Word Limit: | 2500+/- 10% words |
Weighting: | 70% |
Assessment Brief
You are required to design and justify a feasible dissertation project for your programme. Drawing on concepts and techniques from this module, you will develop an individual research proposal of 2,500 words (±10%), worth 70% of the module mark. The proposal should set out a clear research focus, be grounded in academic literature, and present a coherent and realistic methodology.
Your dissertation research proposal should include three main sections:
1.Introduction
Briefly introduce the research topic, context, and its practical and academic relevance within operations, logistics and supply chain management. Clearly identify the research gap, explain why it matters, and state focused research aim(s), objectives and, where appropriate, research questions and/or hypotheses.
2.Literature Review
Demonstrate critical engagement with relevant theoretical and empirical literature. Show how existing work informs your research focus and how your study will build on, extend, or challenge current knowledge. The review should support a clear rationale for your project and lead logically to your proposed methodology.
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3.Methodology and Ethical Reflection
Explain and justify your overall research design and philosophical stance. Describe and justify your data collection methods, sampling strategy and data analysis approach, showing that the project is feasible within the dissertation timeframe.
You must also explicitly reflect on ethical considerations:
- identify the key ethical issues relevant to your project (e.g. informed consent, anonymity, data protection);
- consider potential risks to participants and data privacy;
- explain how you will mitigate these risks and implement appropriate ethical safeguards;
- show how your ethical reflection is aligned with your methodology and data collection plan rather than added as a separate afterthought.
You are expected to use academic literature throughout the proposal to support your choices and arguments. As a guide, you should normally draw on at least 25 academic sources, cited and referenced using the (Cite Them Right Harvard) format.
In addition to the written proposal, you must submit the required ethical approval form signed by your supervisor, please refer to (Ethics at Newcastle University) for guidance on completing this process. No data collection involving potential risk may commence until ethical approval has been formally granted.
The Business School has three overarching learning goals that graduates from all our programmes should attain. These goals are derived from our mission and are:
Disciplinary Competency “A systematic understanding of knowledge, and a critical awareness of current problems and/or new insights, much of which is at, or informed by, the forefront of the digital business discipline, field of study, or area of professional practice.”
Sustainability and Ethics “Apply adequate practices for ethical conduct to address ethical issues in digital business contexts.”
Formative Feedback
Students will receive formative feedback and support on ideas in the seminar and assignment clinic prior to deadlines. Students will also have the benefit of feedback from the initial research proposal assessment and initial contact with their Dissertation Supervisor.
Expectations for the use of AI
You may use generative AI tools (e.g. ChatGPT, Gemini, Claude, Microsoft Copilot, Grammarly) to help improve spelling, grammar and make recommendations to improve your academic writing style, but you must review those suggestions critically. AI tools should not be used to automatically change the language, meaning and tone of your original work. Before using AI, please also review the University’s Academic Integrity checklist for AI use: Artificial Intelligence and Your Learning.
Submitting Your Work
Please submit your work ONCE on or before 8th May 2026 at 12:00 GMT. You do not need to submit a physical copy. All submissions received after 12pm will be automatically capped at 50%, providing it is received within 7 days of the submission date. All submissions received after 7 days will be automatically capped at 0%. By submitting your assignment, you have confirmed you understand the guidance provided and the University’s policy on plagiarism.
Summative Feedback
Your feedback for this assessment will be available to you after 20 working days (not including weekends or public holidays). You can expect feedback in the form of include details here. For guidance on how to understand, interpret and the implement feedback from your assessment please visit the Academic Skills Kit website.
Contacts
For academic and assessment-related queries:
Module Leader: Dr Xinyue Hao Email: xinyue.hao@newcastle.ac.uk Policies
No assignments will be accepted late unless an extension has been granted. Computing problems are not acceptable grounds for late submissions. Plagiarism and any other form of academic misconduct are strictly prohibited and will be dealt with in accordance with University regulations.
Students who fail this assessment will be required to resubmit another assessment during the August resit period. Please note this may impact on the dissertationproject timeframes (typically June-August with the Dissertation Deadline of Friday 1st September), so students will need to seek approval from Dissertation Supervisors to proceed with their project in advance of the resit deadline.
NBS8062 Dissertation Research Proposal Assessment Criteria
Criteria | Components | Weight |
1. Research Background | 1) Research gap – 5% 2) Research question(s) – 5% 3) Research aim(s) – 5% | 15% |
2. Literature Review | 1) Understanding of the topic – 5% 2) Coverage of the existing literature – 5% 3) Critical debate – 10% 4) Linkage to the research background – 5% | 25% |
3. Research Methodology | 1) Research philosophy – 10% 2) Data collection plan – 10% 3) Data analysis plan – 5% 4) Project plan / feasibility – 5% | 30% |
4. Evidence of Reading | 1) Use of literature – 5% 2) Citation number (at least 25 academic references: at least 20 in the literature review and at least 5 in the research methodology) – 5% | 10% |
5. Ethical Reflection | 1) Identification of relevant ethical issues – 3% 2) Consideration of risks to participants/data privacy – 3% 3) Mitigation strategies and ethical safeguards – 2% 4) Alignment of ethical reflection with methodology and data collection – 2% | 10% |
6. Presentation | 1) Writing & structure – 5% 2) Referencing format (Cite Them Right Harvard) – 5% | 10% |
