Stream 2 | Research Data Collection

Overview

This stream is crafted for candidates who are preparing to enter the data collection phase of their research. It focuses on developing practical, ethical, and strategic data gathering techniques appropriate for qualitative, quantitative, or mixed-methods research. Participants will learn to plan and execute data collection effectively while managing challenges in the field. With close mentoring and peer engagement, this stream also supports the development of systems for managing and storing data responsibly, ensuring that participants are well-equipped to transition smoothly into the analysis stage.

Learning Objectives

By the end of this experience, participants will be able to:

  • Identify and evaluate suitable data collection methods for their specific research design.
  • Create and test effective instruments such as surveys, interview guides, or observation protocols.
  • Plan and implement data collection procedures with ethical rigour and logistical awareness.
  • Maintain accurate, secure, and well-organised data records using appropriate management tools.
  • Prepare collected data for analysis through processes such as transcription, coding, and anonymisation.
  • Reflect critically on the data collection experience and align findings with research objectives.

Monthly Sessions

Scheduled sessions will focus on these as core discussion topics:

  1. Introduction to Data Collection
    Overview of data collection approaches and choosing the right methods for your research design.
  2. Planning and Preparation
    Develop data collection protocols, pilot your tools, and anticipate real-world challenges in the field or online.
  3. Data Collection Techniques
    Practical advice and mentoring on conducting interviews, surveys, observations, or digital collection.
  4. Data Management
    Learn best practices for organising, storing, and protecting your data.
  5. Analysis Preparation
    Begin cleaning and coding your data; develop workflows for preparing data for analysis.
  6. Analysis and Interpretation
    Get mentoring on how to interpret your results and connect them back to your research questions and literature.