From Ontology to Audit Trail: A Plain-English Glossary for UK Dissertation Writers

Supervisor feedback can feel like a second language. A comment about ontology may seem abstract when you are trying to finish a chapter, while saturation can sound like a pass-or-fail judgement. The glossary below translates common research terms into plain English. Each entry gives a short definition, a dissertation-ready example and a question you can put to your supervisor. It is not a substitute for your university handbook or your supervisor’s guidance, but it can make the next conversation more focused.

How to Use This Glossary

Read the term in context, then note one or two questions for supervision. The aim is not to memorise every definition, but to recognise which terms are shaping your decisions. If a term still feels unclear, ask for an example rather than another definition.

Foundations of Research

• Ontology. What you believe reality is. Example: treating motivation as measurable differs from exploring lived experience. Ask: which view of reality fits my question?
• Epistemology. How knowledge is justified. Example: interviews and surveys assume different routes to knowledge. Ask: how does my method justify my claims?
• Paradigm. The broad beliefs guiding a study. Example: positivist and interpretivist paradigms produce different designs. Ask: is my paradigm consistent with my methods?
• Methodology. The principles behind your research approach. Example: case study methodology shapes sampling and analysis. Ask: can we review my methodology chapter’s logic?
• Method. A specific data collection or analysis technique. Example: semi-structured interviews are a method. Ask: are my methods suited to my question?

Designing the Study

• Research question. The focused question your dissertation answers. Example: how UK undergraduates use written feedback. Ask: is my question narrow enough?
• Hypothesis. A testable prediction about a relationship. Example: tutorial attendance predicts higher confidence. Ask: does my design test this hypothesis?
• Literature gap. An unresolved or thin area in existing research. Example: few UK studies examine part-time mature students. Ask: is this gap persuasive?
• Theoretical framework. Established theory framing the study. Example: self-determination theory applied to motivation. Ask: which theory drives my analysis?
• Conceptual framework. Your map of key concepts and links. Example: a diagram linking workload, feedback and confidence. Ask: does it match my question?
• Variable. A factor that can change or be measured. Example: weekly study hours and dissertation grade. Ask: how will I measure each variable?
• Operationalisation. Turning an idea into something measurable. Example: defining confidence through a validated scale. Ask: is my definition defensible?

Sampling and Evidence

• Sampling. How you choose participants or cases. Example: purposive sampling of final-year undergraduates. Ask: why is this strategy suitable?
• Saturation. When new data add little new insight. Example: no new themes after twelve interviews. Ask: how should I evidence saturation?
• Triangulation. Using multiple sources or methods. Example: comparing interview themes with documents. Ask: would triangulation strengthen credibility?
• Validity. Whether the study explores what it claims. Example: a questionnaire that truly captures feedback literacy. Ask: what threats should I address?
• Reliability. Consistency of a method or measure. Example: two coders using the same frame. Ask: how can I show consistency?
• Generalisability. How far findings apply beyond the sample. Example: caution in generalising from one department. Ask: am I claiming too much?
• Bias. A distortion affecting design or interpretation. Example: recruiting only satisfied students. Ask: where could bias enter?

Ethics and Integrity

• Ethics approval. Formal permission from a university committee. Example: approval before contacting participants. Ask: what changes need an amendment?
• Informed consent. Voluntary agreement after understanding the study. Example: a plain-English information sheet. Ask: is my consent process clear?
• Anonymity. Ensuring participants cannot be identified. Example: removing names from transcripts. Ask: can anonymity be guaranteed?
• Confidentiality. Protecting data from unauthorised access. Example: encrypted storage and restricted access. Ask: who will see my data?
• Data protection. Following legal and institutional rules. Example: applying UK GDPR principles. Ask: does my plan meet requirements?
• Audit trail. A record of research decisions. Example: dated notes showing codes becoming themes. Ask: what should it include?

Analysis and Reflection

• Coding. Labelling data segments for analysis. Example: tagging extracts as ‘workload pressure’. Ask: should codes be inductive or deductive?
• Thematic analysis. Developing patterns across data. Example: grouping codes into feedback-confidence themes. Ask: which version am I following?
• Reflexivity. Examining your influence on the research. Example: a note on your assumptions as a student researcher. Ask: where should reflexivity appear?
• Positionality. Your location relative to the study. Example: interviewing peers and considering power. Ask: how might this shape the data?
• Limitations. The boundaries and weaknesses of the study. Example: a small sample limits generalisation. Ask: how candid should I be?

Making the Language Work for You

Use these questions to prepare for supervision, not to replace it. A productive meeting often begins with one clear term: ‘I understand triangulation in principle, but I am unsure whether it would strengthen my design.’ That is not a weakness. It is exactly the kind of focused question that turns intimidating terminology into a workable plan.