Growing research demands leave students struggling with research design, data collection, data analysis, and research paradigms
According to a survey conducted, the PhD failure rate in the UK is 19.5%, with 16.2% of students leaving their PhD programme early. When students are asked which section they struggle with the most, the answer is the methodology section.
Dissertation methodology is now emerging as the most challenging and complex stage of dissertation writing for UK university students. Once they select a topic and conduct a comprehensive literature review, they move towards choosing the methodology for their study. However, they struggle to understand which research method is the most appropriate for their research question, how to justify methodological choices, and how to maintain academic rigor throughout their dissertation.
Also, the methodology section is considered the technical pillar of a dissertation; it explains how a study was conducted, why particular research methods were chosen, how data was gathered, and how the results were analyzed.
Furthermore, students face difficulty transforming the theoretical knowledge of a research method into practical methodology that will align with their research question.
“Students often understand individual research concepts but face complexity in connecting those concepts into one coherent research strategy”, said UK Dissertation Helper Online.
Indeed, the methodology section is the most complex section, as it requires students to make informed academic decisions and demonstrate in-depth understanding of research philosophy, approaches, designs, sampling techniques, data collection tools, ethical considerations, and analytical methods.
Students struggle to connect research questions with methodology
There are many methodologies available for students to replicate, but the most common challenge students face is that they are unable to connect research questions with their chosen methodology.
A dissertation starts with an interesting and specific research question. The quality of the final study depends mainly on the research design and whether it was able to address the questions of the research. Students may understand that qualitative and quantitative methods exist, but they struggle to decide which method is suitable for their specific research problem.
Let’s take an example: a student is investigating the employees’ experiences of remote working. That student may benefit from qualitative interviews if the objective is to explore perceptions, experiences, and attitudes; on the other hand, if a student is examining the statistical relationship between remote working and employee productivity, then it will require a quantitative approach.
However, a student cannot differentiate these methods only by knowing their definitions. They must know what their research aims to discover and then choose a methodology that can produce meaningful evidence.
Choosing between qualitative, quantitative, and mixed methods is mounting pressure
Another challenge students face is choosing between qualitative, quantitative, and mixed methods research.
Qualitative research focuses on understanding meanings, experiences, opinions, and social phenomena; on the other hand, quantitative research focuses on numerical data, measurable variables, statistical relationships, and patterns. Moreover, mixed methods research combines elements of both approaches
Sometimes, students select a method because it seems easier. However, methodology should not be decided by convenience, but rather by the research question.
The easy availability of online surveys and research tools confuses students about whether they should draft their own questionnaire or use the one available online. However, even if students choose available surveys or tools, they need to consider sample size, question design, participant selection, reliability, validity, and potential response bias.
Furthermore, conducting interviews also requires meticulous focus on participant selection, interview structure, recording methods, transcription, confidentiality, and thematic analysis.
Research philosophy adds another challenge
Research philosophy is another area where students face complexity. Terms like positivism, interpretivism, pragmatism, ontology, and epistemology are highly theoretical, especially for students who encounter research at an advanced academic level for the very first time.
The challenge is not simply to understand what each philosophical framework means, as students must also understand how their philosophical assumptions influence their research approach.
For example, if a researcher is studying measurable relationships between variables, then he/she must adopt a philosophical position that supports objective observation and quantitative analysis, i.e., a positivist research paradigm. On the other hand, a researcher exploring individual experiences may instead adopt an approach that focuses on subjective interpretations, i.e., interpretivism or constructivism.
Moreover, universities expect students to demonstrate this connection between the philosophical framework and their research problem. Therefore, they must go beyond definition and explain why their selected framework is more suitable.
Data collection and sampling create another difficulty
Choosing appropriate participants and collecting reliable data is equally important, but it is a difficult process.
Sampling is crucial as students often have limited time and have to decide who will participate in their research, how they will be selected, and whether the chosen sample addresses their research objectives.
Probability and non-probability sampling techniques include random, stratified, purposive, convenience, and snowball sampling, and each of these has different applications and limitations.
Also, students must justify the technique they have chosen rather than simply stating the technique they have used.
Data collection can also raise issues because participants may withdraw, response rates may be low, interviews may produce unexpected information, or survey responses may not provide enough data for meaningful analysis.
Data analysis creates additional pressure
Now that the data has been collected, students also struggle with data analysis.
Quantitative studies require students to use statistical techniques to identify relationships, differences, and patterns within the numerical data. On the other hand, qualitative studies involve thematic or content analysis to identify recurring ideas and meanings.
In addition, students need to connect findings to their research questions.
Methodology is not just another chapter
The methodology section is the pillar of a strong dissertation. It reflects that a student can approach a research problem, collect evidence, justify choices, and acknowledge limitations in a study.
