The purpose of this capstone project is to enable learners (who would wish to graduate with a post graduate diploma in Mathematical Innovation) apply concepts learned to  concrete situations in industry. Learners will be equipped with skills of designing and implementing a project, and writing a report at the end of the implementation period. 

ELO1: Explain the theories and methodologies relevant to the project.

ELO2: Use learned theories and methodologies to design and implement the project.

ELO3: Analyse data using appropriate tools.

ELO4: Develop and write a project proposal and final report.

Objective of the capstone project:  

The primary goal of this research project is to conduct a thorough investigation into a learner’s specific topic or problem within the learners area of interest. The project will focus on exploring key questions, identifying trends, and providing new insights or solutions. This research aims to contribute to the academic or professional understanding of the subject and potentially influence future studies or practices.

Description of the capstone project:  

The capstone research project will involve a structured process of literature review, data collection, analysis, and interpretation to answer a significant research question or hypothesis. It will be guided by a strong methodological framework, ensuring that the research is valid, reliable, and ethical. 

Key steps in the research process will include:

1. Research Question: Formulation of a clear, focused research question or hypothesis based on gaps in existing literature or current challenges in the field.

2. Literature Review: A comprehensive review of relevant studies, theories, and findings that provide the foundation for understanding the research context.

3. Methodology: Selection of appropriate research methods, such as qualitative interviews, surveys, experiments, or case studies, depending on the nature of the topic.

4. Data Collection: Gathering primary data through interviews, surveys, experiments, or secondary data from academic sources or databases.

5. Data Analysis: Analyzing the data using statistical tools (e.g., SPSS, Excel, R, or Python) or qualitative analysis techniques.

6. Discussion: Interpretation of results in the context of the original research question, comparing findings with existing literature and theories.

7. Conclusion & Recommendations: Presenting final conclusions, addressing limitations, and offering recommendations for future research or practical applications.