Asking your supervisor for feedback on your quantitative research data collection plans? Include this information.

One of the challenges students face when planning their data collection us to understand what areas they need to consider. Students should always get their supervisor's input about their data collection plans, and when my students want my feedback there are a number of area they must include in their document. For quantitative research, I ask them to prioritise 5 areas, because they are the areas of a study's methodology that make or break the reliability and validity of the study. In this post I will briefly explain these five areas. A much more comprehensive explanation is included in the Methodology resource within the Virtual Tutor Resource.

🎯 Aim & Objectives

The aim and objectives of a research study are crucial in shaping the design of a quantitative research methodology. The aim sets the direction and scope, while objectives break down the aim into specific questions, guiding the research process. They influence the methodology by determining the variables to be measured, sample size, and statistical tests. Due to their importance, aim and objectives should be included at the beginning of the draft methodology chapter to ensure all decisions within the methodology are aligned with them.

🔭 Conceptual framework

A conceptual framework is an essential feature in quantitative research as it defines the variables and concepts influencing the phenomenon being studied and their relationships. It acts as a lens to observe real-world phenomena and ensures that key variables and their interactions align with the research objectives. Designing a robust framework requires considering all relevant variables, including dependent and independent ones, and planning data analysis strategies. The framework guides the selection of indicators to measure each concept, ensuring accurate and reliable data collection. A well-designed framework facilitates answering the research questions and developing hypotheses.

📋Questionnaire Design

Questionnaire design is a critical component of the methodology chapter in research. I usually look at five key tasks: overall strategy, measurement of variables, measurement scale, context of questions, and instructions. The overall strategy considers the big picture and the approach to be employed, such as cross-sectional, longitudinal, or within-subject designs. Measurement of variables explains how each concept in the research framework is measured through specific items in the questionnaire, ensuring accurate and reliable data collection. Measurement scales are essential for quantifying responses and analyzing data statistically, with choices influencing reliability, validity, and ease of understanding for respondents. The context of questions ensures that all participants answer based on the same frame of reference, achieving high levels of validity and reliability. Providing clear instructions on how to complete a questionnaire is crucial, as it helps respondents understand the purpose, how to answer questions, and what is expected of them.

It is important to spend time getting the questionnaire right before starting data collection, as a poor questionnaire cannot be corrected once implemented. Ultimately, the strength of the research design depends on the consistency and coherence of the methodological design, leading to successful data collection.

🙋 Population and sampling

Considering the study’s population and sampling is crucial when designing a methodology for a dissertation. Selecting suitable participants ensures that the data collected is relevant and meaningful. The participants' connection to the topic is vital, and could take the form of in-group membership or knowledge and experience related to the research topic. Accessibility of participants is important for practical reasons, and detailed information about this is necessary. The size of the accessible population should be large enough to achieve the targeted number of responses, given response probability expectations. The geographical boundaries also affect the size of the accessible population, with questionnaires conducted online potentially removing fewer barriers to collecting data from other regions or countries. The size of the sample affects the reliability of the statistical analysis, since a larger sample size increases the power of the study and reduces the margin of error. The sample size should be determined based on the statistical tests planned for the analysis.

📊 Statistical Analysis

The type of statistical analysis conducted in research is influenced by the objectives and relationships between variables within the conceptual framework. It is crucial to plan the data analysis strategy when designing the questionnaire, rather than waiting until data collection is complete. The purpose of data analysis is to explore patterns and relationships in the data, requiring an understanding of the tests likely to be used. This necessitates clarifying dependent and independent variables within the conceptual framework. Proper planning ensures that the data analysis aligns with the research objectives and yields meaningful insights.

* * *

A significant part of my discussion with students revolves around their plans for each of these five areas. My approach to assessing a quantitative data collection plan outlined in this document emphasises the importance of examining each area individually while also considering their interrelations. This approach ensures that the research design is both consistent and coherent, ultimately leading to successful data collection. The focus is always extended to the reasoning behind their choices. Why are they approaching it this way? Ultimately, the strength of their work depends on the strength of their explanation. If the explanation is strong, the decision is robust. If the explanation is weak, the decision can be questioned.

If you want to know more about these areas, check out the pdf (over 3000 words) which is part of the Methodology resource. Alternatively, consider getting hold of the entire Virtual Tutor Resource, which contains over 13 hours of videos explaining how to write a top dissertation, with many of the videos addressing data collection-related issues. For example, one of the resources provides a fairly comprehensive explanation of Quantitative Conceptual Frameworks, while another one focuses on Questionnaire design.

And if you feel you would benefit from direct input from an experienced supervisor when designing your methodology / questionnaire, consider getting my support.