MDSA 71412 Capstone Project Research Proposal 2026 | LUC Malaysia

MDSA71412 Capstone Project Research Proposal

1. General Direction

The capstone project must be clearly related to Data Science and Analytics. The study should address a data-driven problem, apply appropriate analytical methods, and produce a practical research output.

2. Data Requirement

The project should rely mainly on primary data collected by the student. Public or secondary data may be used only for supporting comparison and should not be the main source of data.

• what data will be collected
• who the respondents are
• where the data will be collected
• when the data will be collected
• how the data will be collected

3. Topic Requirement

• specific
• feasible within a 3-month semester
• practical to implement
• suitable for a Master’s capstone
• aligned with the student’s actual ability to collect data and complete the analysis

4. Research Structure Requirement

The research should include one research aim, about four research objectives, one main research question, and no hypothesis.

5. Writing Style Requirement

The writing should be in academic English, coherent and connected, written in thesis style, and not presented as an outline-only draft broken into too many short subsections. The supervisor expects fuller paragraphs, better flow between sections, and enough content and volume rather than overly shortened writing.

6. Proposal Structure Requirement

The proposal should follow a structured format similar to the sample shared by the supervisor:

• Title Page
• Abstract
• Chapter 1: Introduction
• Background of the Study
• Problem Statement
• Aim and Objectives
• Research Question
• Significance of the Study
• Scope of the Study
• Limitations
• Chapter 2: Literature Review
• Review of Existing Studies
• Main Themes / Key Variables
• Research Gap
• Conceptual Direction / Framework
• Chapter 3: Methodology
• Research Design
• Population and Sample
• Data Collection Instrument and Procedure
• Data Analysis Plan
• Ethical Considerations
• Project Timeline
• References

7. Chapter Requirement

The supervisor may review the work chapter by chapter. Students should be ready to submit work in chapter form, not only as a short overview note. The expected thesis structure is Chapter 1:

Introduction, Chapter 2: Literature Review, Chapter 3: Research Methodology, Chapter 4: Results and Analysis, and Chapter 5: Conclusion and Recommendations. There is no need for Chapter 6.

8. Communication Requirement

The supervisor does not want frequent messages about every small detail or delay. Students should avoid constant process updates, avoid sending messages for every minor difficulty, and report progress only when something reasonable and substantial has been completed.

9. Progress Expectation

Students are expected to work steadily, meet weekly expectations, come to meetings with visible progress, and avoid falling behind without real output.

10. Referencing Style

Use APA 7th edition unless the supervisor or faculty states otherwise.

11. Practical Rule for Topic Selection

Before finalising the topic, the student should be able to answer the following questions:

• Can I collect the data myself?
• Are the respondents accessible?
• Is the topic specific enough?
• Can I analyze it using Data Science / Analytics methods?
• Can I finish it within 3 months?

12. Final Reminder

Most important requirements

• primary data
• clear and feasible topic
• Data Science and Analytics relevance
• proper academic structure
• thesis-style writing
• real progress, not only discussion

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