Knowledge for your studies
Clearly explained: academic writing, research methods, qualitative content analysis, statistics and exam preparation — with examples and free tools.
103 articles · 551 terms in the glossary
✍️ Academic writing
Term papers, bachelor and master thesis: structure, research question, citing, literature, plagiarism, using AI properly.
- How to write a research paperPick a narrow question, find and read sources, build an outline, draft section by section, then cite and revise. Plan about two to four weeks.
- Dissertation structureMost dissertations have five chapters: introduction, literature review, methodology, results, and discussion/conclusion, plus front and back matter.
- Writing a master’s thesisA master’s thesis takes 4–12 months: settle topic and supervisor early, plan backward from the deadline, collect data by the halfway point, and revise.
- Choosing a research topicStart from your interests, read recent reviews to find gaps, narrow until one question fits your time and sources, then test it with your supervisor.
- Research proposalA research proposal explains what you will study, why it matters, and how you will do it: title, background, questions, method, timeline, references.
- Research questionA strong research question is open, focused, and answerable with your data. Start with “how”, “why”, or “to what extent” and name population and context.
- Thesis statementA thesis statement is one or two sentences, usually at the end of your introduction, stating your main claim and the reasons that support it.
- Dissertation outlineA dissertation outline lists chapters and subsections with numbers, key points, and planned word counts. Draft it early and revise it as your research develops.
- Writing an introductionA strong introduction moves from context to problem to gap, then states your research question or thesis and previews the structure. Write it last.
- Writing a conclusionA conclusion answers your research question directly, summarizes key findings, explains their significance, names limitations, and points to future research.
- Writing an abstractAn abstract summarizes purpose, method, key results, and conclusion in 150–300 words. APA 7 sets a 250-word limit; write it last as one paragraph.
- Academic writing styleAcademic style is clear, precise, and cautious. First person and active voice are widely accepted; hedge claims and keep US or UK spelling consistent.
- Literature searchDefine key concepts, list synonyms, combine them with AND/OR/NOT in library databases, follow citations (snowballing), and evaluate each source.
- Literature reviewA literature review synthesizes what research says about your topic, organized by themes, and shows the gap your study fills. It is not a list of summaries.
- APA 7th editionAPA 7 uses author–date citations: (Nguyen & Patel, 2021) or Nguyen and Patel (2021). Use “et al.” for three or more authors from the first citation.
- Harvard referencingHarvard is an author–date style widely used in UK universities: (Smith, 2020, p. 15) in text and an alphabetical reference list. Details vary by university.
- MLA formatMLA 9 uses author–page citations like (Morgan 45) and a Works Cited list built from core elements. Papers are double-spaced with a header and no title page.
- Chicago styleChicago style has two systems: notes-bibliography (footnotes plus bibliography, used in history and the arts) and author-date (used in the sciences).
- Quote, paraphrase, summarizeQuote when exact wording matters, paraphrase to restate one idea in your own words, summarize to condense main points. All three need a citation.
- Reference listA reference list contains every source cited in your text; a bibliography may include works you consulted. APA says “References”, MLA “Works Cited”.
- Avoiding plagiarismCite every idea, quote, and data point you take from others, paraphrase properly, never reuse graded work without permission, and track your sources.
- AI in academic writingAI rules vary by university and course. Check the policy, use AI for support rather than ghostwriting, verify every claim, and disclose your use as required.
- Declaration of originalityA declaration of originality is a signed statement that your work is your own, sources are cited, and it was not submitted elsewhere.
- Tables and figuresIn APA 7, label tables and figures in bold (Table 1), add an italic title in title case above, put notes below, and cite any source in a copyright note.
- Dissertation appendixAppendices hold supporting material like questionnaires, interview guides, consent forms, and extra tables. Label them A, B, C and refer to each in the text.
- Reference managers comparedZotero is free and open source, Mendeley free with an account, EndNote and RefWorks usually come via a university licence, JabRef suits LaTeX users.
- Zotero vs MendeleyZotero is free, open source and works with Word, LibreOffice and Google Docs; Mendeley is free with an account and Word add-in. Both are fine for a thesis.
- LaTeX vs WordLaTeX/Overleaf suits formula-heavy, long theses with BibTeX; Word suits most other fields and track-changes feedback. Use your university’s template.
- Turnitin similarity reportA Turnitin similarity score shows how much of your text matches other sources. It is not a plagiarism verdict: a person judges each match in context.
- AI tools for studentsChatGPT, Claude, Gemini, Copilot, Perplexity, Elicit and others can help you study and research, but your university’s policy decides what is allowed.
🧭 Research design and methods
Quantitative, qualitative, mixed methods: quality criteria, sampling, questionnaires, interviews, hypotheses.
- Sample sizeFor a survey with 95% confidence and a ±5% margin of error you need about 385 responses. For group comparisons, a power analysis sets the size.
- Quantitative vs qualitativeQuantitative research measures and tests hypotheses with numbers; qualitative research explores meanings with words. Your research question decides.
- Mixed methods researchMixed methods research combines quantitative and qualitative data in one study. The three core designs: convergent, explanatory and exploratory sequential.
- Reliability and validityReliability means a measure gives consistent results; validity means it measures what it is meant to. A measure can be reliable without being valid.
- TrustworthinessTrustworthiness is how qualitative research shows quality: credibility, transferability, dependability and confirmability (Lincoln & Guba, 1985).
- Writing a hypothesisA hypothesis is a testable prediction about the relationship between variables. Write a null (H₀) and an alternative hypothesis (H₁) for each test.
- OperationalizationOperationalization turns an abstract concept into measurable variables: define the concept, identify dimensions, choose indicators and a measurement method.
- Questionnaire designA good questionnaire starts from your research question, uses validated scales, neutral wording and a logical order, and is pilot tested before launch.
- Likert scaleA Likert scale measures attitudes with several agreement items, usually rated from 1 (strongly disagree) to 5 or 7 (strongly agree), combined into one score.
- Sampling methodsProbability sampling gives everyone a known chance of selection and supports generalization; non-probability sampling is quicker but limits it.
- Pilot studyA pilot study is a small trial run of your survey or interview guide that reveals unclear questions, technical issues and timing problems early on.
- Semi-structured interviewsA semi-structured interview follows an interview guide of open questions but lets you change order, follow up and probe. Typical: 8–15 interviews of 45–60 min.
- Expert interviewsExpert interviews draw on people with specialist knowledge of a field, process or organization. They suit applied and policy questions; 5–10 are typical.
- Interview transcriptionTranscription turns interview recordings into text. Choose verbatim or intelligent verbatim, set clear rules and pseudonymize names before analysis.
- Focus groupsA focus group is a moderated discussion with 5–8 participants on a defined topic. It reveals shared views and how opinions form through interaction.
- Observation researchObservation means systematically watching and recording behavior in its setting. Key choices: participant or not, structured or not, overt or covert.
- Case study researchA case study examines one or a few cases in depth and in their real-life context, using several data sources. Yin and Stake define the main approaches.
- Systematic reviewA systematic review answers a focused question by searching, selecting and appraising all relevant studies with an explicit, reproducible method (PRISMA 2020).
- Research ethicsResearch with people needs informed consent, ethics approval (IRB in the US, ethics committee in the UK/EU) and data protection that meets the GDPR.
- Survey response rateThe response rate is the share of invited people who complete your survey. Short surveys, personal invitations and reminders raise it most reliably.
🏷️ Qualitative analysis
Thematic analysis, qualitative content analysis, coding and codebooks, grounded theory, IPA, framework analysis.
- Thematic analysisThematic analysis finds patterns of shared meaning (themes) in qualitative data. Braun and Clarke describe six recursive phases from familiarisation to report.
- Qualitative content analysisQualitative content analysis systematically codes text into categories. Hsieh and Shannon distinguish conventional, directed and summative approaches.
- Coding qualitative dataCoding means labelling segments of qualitative data with short codes. You code inductively or deductively, then group codes into categories in a second cycle.
- CodebookA codebook lists every code with a name, definition, inclusion and exclusion criteria and examples, so that coding is consistent and transparent.
- Inter-rater reliabilityInter-rater reliability shows how consistently two or more coders apply the same codes. Cohen’s kappa corrects for chance; κ above 0.60 is usually acceptable.
- Grounded theoryGrounded theory develops a theory from data through constant comparison, open and axial coding, memo writing and theoretical sampling until saturation.
- Analyzing interview dataTo analyze interviews, transcribe and anonymise them, choose a method, code systematically, develop themes or categories and check them against the data.
- QDA softwareQDA software helps you organise, code, retrieve and compare qualitative data. It does not analyse for you; for small projects, free tools can suffice.
- Writing qualitative findingsPresent qualitative findings theme by theme: state the analytic claim, support it with selected quotes, interpret them, and keep the discussion separate.
- Framework analysisFramework analysis organises qualitative data in a matrix of cases (rows) and codes or themes (columns), to compare within and across cases systematically.
- IPAIPA explores how individuals make sense of significant life experiences. It combines phenomenology, hermeneutics and idiography and works with small samples.
- Narrative analysisNarrative analysis studies how people tell stories about their lives: what they tell (thematic), how they tell it (structural) and for whom and why (dialogic).
- QDA software comparedNVivo, ATLAS.ti and MAXQDA are full-featured QDA packages, Dedoose runs in the browser, Taguette and QualCoder are free. Choose by data, team and licence.
- Thematic analysis in NVivoIn NVivo you import transcripts, code with codes and memos, cluster codes into candidate themes and review them with queries. The interpretation stays yours.
📊 Statistics explained
Levels of measurement, mean, t-test, chi-square, correlation, regression, p-value, effect size, power.
- Levels of measurementVariables are nominal, ordinal, interval or ratio. The level decides which averages, charts and statistical tests you are allowed to use.
- Descriptive statisticsDescriptive statistics summarize your data with numbers, tables and charts: sample size, central tendency (mean, median) and spread (SD, IQR).
- Mean, median, modeThe mean is the arithmetic average, the median the middle value, the mode the most frequent value. Use the median for skewed data or outliers.
- Standard deviation and varianceThe standard deviation is the typical distance of values from the mean. Variance is its square. Sample formula: SD = √(Σ(x − M)² / (n − 1)).
- Testing for normalityCheck normality with a histogram or Q-Q plot, skewness and kurtosis, and the Shapiro-Wilk test. With large samples, plots matter more than p-values.
- p-value and significanceThe p-value is the probability of a result at least as extreme as yours if the null hypothesis were true. p < .05 is usually called significant.
- Effect sizeAn effect size tells you how large a difference or relationship is, independent of sample size. Cohen’s d of 0.2, 0.5 and 0.8 is small, medium, large.
- Confidence intervalA 95% confidence interval gives a range of plausible values for a population parameter. It shows both the size of an estimate and its precision.
- Type I and Type II errorsA Type I error is a false positive (rejecting a true null hypothesis, risk α); a Type II error is a false negative (missing a real effect, risk β).
- t-testA t-test checks whether two means differ significantly: two independent groups, two paired measurements, or one mean against a fixed value.
- ANOVAAnalysis of variance (ANOVA) tests whether three or more group means differ. A significant F-test is followed by post-hoc tests such as Tukey HSD.
- Chi-square testThe chi-square test checks whether two categorical variables are related (independence) or whether frequencies match an expected distribution.
- CorrelationA correlation coefficient measures the strength and direction of a relationship between two variables, from −1 to +1. Correlation is not causation.
- Linear regressionLinear regression predicts a metric outcome from one or more predictors with a straight line: ŷ = a + b · x. R² shows how much variance it explains.
- Mann-Whitney U testThe Mann-Whitney U test compares two independent groups using ranks. It is the non-parametric alternative to the independent-samples t-test.
- Cronbach’s alphaCronbach’s alpha measures the internal consistency of a scale: how well its items measure the same construct. Values of .70 and above are acceptable.
- Choosing a statistical testYour research question, the level of measurement of your outcome, the number of groups and whether samples are paired decide which statistical test fits.
- Reporting statistics in APAAPA style reports test statistic, degrees of freedom, exact p-value and effect size, e.g. t(13.46) = 3.42, p = .004, d = 1.71. Examples for every test.
- Hypothesis testing in 7 stepsHypothesis testing in 7 steps: state H₀ and H₁, set α, choose the test, check assumptions, compute the statistic, decide with p, report the effect size.
- Logistic regressionLogistic regression predicts a binary outcome (yes/no) from one or more predictors. Coefficients are log-odds; exp(b) gives the odds ratio.
- Statistics software comparedSPSS and Stata are menu- or command-based commercial packages, R and Python are free code, JASP and jamovi are free point-and-click. Choose by field and task.
- t-test in SPSSIn SPSS: Analyze → Compare Means → Independent-Samples T Test. Read Levene’s test, then t, df, p and the CI, and report with Cohen’s d in APA style.
- Free SPSS alternativesThe best free SPSS alternatives are JASP and jamovi (menus, APA tables), PSPP (SPSS-like syntax) and R (code). All open .sav files.
🎯 Studying and exams
Exam preparation, evidence-based learning techniques, time management, oral exams, thesis defense, presentations.
- How to study for examsStart four weeks out: map what is tested, quiz yourself rather than reread, take past papers under timed conditions, and use the final week to review and sleep.
- Study scheduleA good study schedule starts from your fixed commitments, splits topics into short blocks, spaces reviews over days and keeps 20 % of the time as a buffer.
- Study techniquesPractice testing and spaced practice work best; interleaving, elaboration and self-explanation help; highlighting and rereading do little on their own.
- Flashcards and spaced repetitionWrite one question per card in your own words, answer before you flip, and review on a growing schedule: cards you know move back, cards you miss return soon.
- ProcrastinationProcrastination is a problem of mood and motivation, not laziness. Shrink the first step, plan when and where, remove distractions and set close deadlines.
- Time management for studentsTrack one week, plan the next every Sunday, block time for your most important tasks first, work in focused blocks and protect sleep and buffer time.
- Oral exams and vivasPrepare for an oral exam by speaking, not reading: explain topics aloud from memory, practice likely questions with someone else and rehearse a short opening.
- Thesis defensePrepare a 15–20 minute talk on question, method, results and limits, anticipate likely questions, rehearse aloud with an audience and know your weak spots.
- Class presentationsBuild your talk around one core message, use one idea per slide with few words, rehearse aloud at least three times and plan two minutes of buffer.
- Study groupsEffective study groups have 3–5 members, meet regularly, come prepared and spend most of the time quizzing and explaining, not rereading together.
- Test anxietyTest anxiety is common and treatable. Prepare with practice tests, write down worries before exams, reframe arousal as energy and seek support if it persists.
- GPA calculationMultiply each course’s grade points by its credit hours, add them up and divide by total credit hours. A 3.0 on the 4.0 scale is a B average.
- Motivation for studentsMotivation grows when you feel in control, see progress and feel connected. Set concrete goals, build routines that do not depend on mood and track small wins.
- Reading academic papersRead papers in passes: abstract, figures and conclusion first, then the full text selectively, and finally critically. Take notes in your own words as you go.
- Note-takingTake notes in your own words rather than verbatim, use a structure like the Cornell method and review them within a day by testing yourself, on paper or laptop.
- Flashcard apps comparedAnki has the strongest spaced repetition, Quizlet the easiest sharing and games, RemNote combines notes and cards. Pick the app you will open every day.
