Research Methods and Skills

The MSM Research Methods and Skills (RMS) course helps participants in the preparation of a research proposal. Divided over four modules, a series of short instructive videos explain the key elements of a research proposal and the basics of research methodology. Short instructive videos, course literature, individual assignments, virtual classes, group chat opportunities and individual feedback from the lecturer will prepare participants for the completion of the research proposal.

Module 1: Foundations of research proposal design

This module introduces participants into the world of academic research. The focus is on the various stages of the empirical research cycle, highlighting the prominent role theory plays in guiding research. The module helps you to formulate your research question and conceptualize your research interest by drawing on the relevant academic literature.

At the end of this module, you will be able to:

• Identify a research topic which is empirically feasible and theoretically defensible
• Draft a solid literature review to conceptualize the research topic
• Formulate a clear research question(s)
• Design a research strategy to address the research questions
• Understand what constitutes good research allowing a critical assessment of scholarly work

Module 2: Qualitative research: data collection and analysis  

This module introduces you to the characteristics of and approaches to designing and conducting qualitative research projects. A series of short videos explain the key elements of a selection of qualitative research methods. Each video will make references to documents for further self study. Participants will work individually on an assignment comprising the design of qualitative research, which will be discussed in the virtual class. 

At the end of this module, you will: 

• Be familiar with the characteristics and logic of various qualitative research methods
• Know the strengths and weaknesses of these methods
• Operationalize your conceptual model into items to be used in interview questionnaires
• Be able to design a basic qualitative research study
• Understand how to prepare quantitative data for analysis
• Understand which methods can be used to analyse qualitative data
• Have basic knowledge of the value of (software) tools for qualitative data analysis
• Assess issues relating to reliability and validity of empirical findings

Module 3: Quantitative research: data collection and analysis 

The first week aims to provide you with a brief introduction to two methods of data collection: the survey and the use of existing data sets. In quantitative research approaches, students may want to collect new data among specific populations that fit their research question. Alternatively, students may be professionally employed in organisations and have access to interesting data bases of these organizations. This module explains for both the survey and existing data sets the route ahead as well as the main challenges in data collection and data preparation.

This module also introduces you the most common statistical methods for conducting advanced-level quantitative data analysis. The videos explain how to select the proper statistical techniques for testing specific research hypotheses and conceptual models, and assessing the reliability and validity of their findings.

At the end of this module, you will be able to:

• Know the strengths and weaknesses of survey research
• Know the benefits and limitations of using existing data bases
• Operationalize your conceptual model into items with the help of a data-table
• Sample respondents
• Understand the different methods that can be used to collect the survey data (e.g. face-to-face, telephone, web-based)
• Understand how to prepare quantitative data for analysis
• Understand different statistical methods and when they can be applied
• Understand how to quantitatively test a conceptual model and research hypotheses
• Assess issues relating to reliability and validity of empirical findings

Module 4: Machine learning for research methods

This module introduces participants to the principles and applications of machine learning within the context of research methods and scientific inquiry. It explores how machine learning techniques can support the design, execution, and interpretation of research across a range of disciplines. Participants will learn how data-driven models are built, validated, and used to generate insights, predictions, and evidence for research questions. By the end of the module, participants will be able to critically assess when and how machine learning can be appropriately integrated into research design, and effectively communicate findings using ML-based methods.

The Research Proposal

After the completion of the fourth module, you will work on your research proposal and apply the knowledge gained in the earlier modules in the writing of your research proposal. The submission deadline for the research proposal is 31 August 2026. 

Teaching methods

• Instructive videos by the lecturer
• Course literature
• Individual assignments
• Individual feedback
• Group chat opportunities
• Virtual (feedback) classes

Study hours
Module 1: 2 weeks (20 hours self study and 1 live session)
Module 2: 2 weeks (20 hours self study and 1 live session)
Module 3: 2 weeks (20 hours self study and 1 live session)
Module 4: 2 weeks (20 hours self study and 1 live session)
Completion of the Research Proposal: Submission deadline 31 August 2026. 
Upon completion of the modules individual coaching sessions will take place to guide you in the completion of your research proposal. 

Live sessions
The main purpose of the live sessions is to provide the participants with the necessary theory and feedback in order to support you to submit the final assignment of each module, and in the end your research proposal.

Assignments
The modules include one or more assignments. These assignments will attribute to completing the research proposal. In addition, you will receive feedback on the assignments during the live sessions. The course will be completed with the successful completion of the research proposal. The completion of the assignments and a pass-level grade of the research proposal is necessary in order to obtain the certificate. 

*A positive assessment of the final assignment of the course (the Research Proposal) will not guarantee admission to any PhD programme, including the PhD programme of MSM. Decisions to a PhD programme are with the respective PhD Admission Committee.
**If you would like to apply for the MSM Executive PhD programme after the Research Methods and Skills programme, please take the MSM Research Themes into consideration. Click here for more information about the Research focus of the MSM Executive PhD in Private Sector Development. 

Certificate

Each participant receives a certificate of participation.
This certificate is being awarded as evidence of participation in a post-graduate training at indicative level 7 of the EQF. The minimum study load is 14 hours and an attendance level of 80% is required. This certificate is being awarded in the form of a soft copy when the training is online or a hard copy during a face-to-face training. The certificate will mention your full name, training title, training date and comprising core topics. Click here for more information about the MSM certification policy.