Research Methods and Data Collection

1. Research Methods and Data Collection

Effective research begins with a strong understanding of appropriate methods, ethical practices, and robust data collection procedures. This section supports EIT students and staff in developing the skills needed to design, conduct, analyse, and report research at undergraduate, postgraduate, and doctoral levels.

What Are Research Methods?

Research methods are the systematic tools, processes, and strategies used to collect and analyse data to answer research questions. Researchers may use a variety of approaches depending on the nature of their problem: quantitative, qualitative, or mixed methods.

Quantitative Methods:

Quantitative research involves collecting numerical data and using statistical techniques to test hypotheses, measure variables, and examine relationships.

Experimental design

Surveys and structured questionnaires

Statistical modelling and data analytics

Simulation and computational modelling

Field measurements and engineering testing

Qualitative Methods:

Qualitative research gathers non-numerical data such as experiences, perceptions, and behaviours to understand deeper meanings, context, and human-technology interaction.

Interviews, focus groups, and participant reflections
Case studies and organisational investigations
Document analysis
Ethnographic and observational techniques

Mixed Methods:

Combining quantitative and qualitative data to build a more comprehensive picture of engineering problems, human technology interactions, sustainability considerations, or learning outcomes.

2. Data Collection Practices

High-quality research requires data that is accurate, reliable, and ethically obtained. EIT encourages the following best practices:

Planning

Clearly define research questions, variables, and data requirements.
Select tools aligned with the methodology (e.g., sensors, simulations, EEG devices, digital logs, databases).

Collection

Follow standard operating procedures for equipment use.
Ensure informed consent when collecting human data.
Maintain version-controlled digital records.

Management

Store data securely on approved systems.
Anonymise or de-identify personal information where required.
Ensure data is traceable and reproducible as part of academic integrity expectations.

Analysis

Apply appropriate statistical, computational, or thematic techniques.
Validate findings using cross-checking, replication, or triangulation.

3. Research Ethics and Integrity

EIT is committed to upholding the highest standards of academic and research integrity. All research involving human participants, personal information, or specialised equipment must comply with:

Ethical review and approval processes
Confidentiality and privacy requirements
Accurate reporting, transparency, and avoidance of misconduct
Proper citation and acknowledgement of sources

4. Relevant EIT Policies and Procedures

Students and staff conducting research must adhere to the following EIT governance documents: