Research methods and scholar examples

Research training beyond introductory study: evidence synthesis, causal design, modelling, qualitative analysis and reproducible experiments.

Start with your research question, choose a method, study original materials and produce work others can examine. Sources are mainly in English, with bilingual reading tasks.

Six methods workbooks Scholars, courses and sources YouTube and talks

Learn through your research project

Find a question, read papers and learn with AI

Eight units with methods, worked examples and free primary sources. Practise here or offline, take work to your AI, then import feedback and revise.

Open research learning studio →Advanced methods and scholar courses →

Choose a research task

The workbooks and review criteria are platform-designed exercises for projects or group discussion, not assignments set by the source authors.

Questions and contributions: distinguish competing explanations

Compare candidate questions, map claims to evidence and draft a proposal that can be challenged.

Method · example · deliverable · review criteria →

Evidence synthesis: protocols, bias and disagreement

Move from rerunnable searches to synthesis; separate reporting, study quality and comparability.

Method · example · deliverable · review criteria →

Causal design: estimands, DAGs and sample justification

Define the target trial and identification assumptions before estimation, then simulate where the design fails.

Method · example · deliverable · review criteria →

Bayesian workflow: generative models, diagnostics and revision

Connect priors, sampling diagnostics, predictive checks and sensitivity analysis in an auditable workflow.

Method · example · deliverable · review criteria →

Reflexive thematic analysis: from extracts to interpretation

State epistemology and positionality, trace codes into themes and revise interpretations using counterexamples.

Method · example · deliverable · review criteria →

Reproducible experiments: baselines, fair comparisons and failure audits

Fix splits, comparison budgets and sources of variability so another researcher can rebuild the main result.

Method · example · deliverable · review criteria →

Scholar examples and professional resources

Format: Video and course Clear all

2 resources found

Statistical modelling · Video and course · Graduate · methods prerequisites

Statistical Rethinking · 2023

Richard McElreath · 2023

Reading target: Focus on lecture 6, Good & Bad Controls, and lecture 12, Multilevel Models; the author links the full course.
Prerequisites: Probability, regression, R and willingness to simulate data.
Platform-designed exercise: Simulate grouped data; compare complete, separate and partial pooling, including uncertainty for small groups.
Method boundary: Adjustment depends on causal structure; complexity or better fit does not establish causality.
Access: Public lectures, slides and code; textbook obtained separately. This selection uses the fixed 2023 edition.

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Source checked 2026-10-25 · Video addresses verified from author pages; recordings were not reviewed end to end.

Questions and arguments · Video and course · Advanced · subject foundations

How to Write a Great Research Paper

Simon Peyton Jones · 经典讲座 / recorded talk

Reading target: Use writing as part of research thinking, organizing around contributions and readers' questions.
Prerequisites: An initial finding or a claim that can be tested.
Platform-designed exercise: Draft a one-page argument: problem, gap, contribution, evidence, strongest objection and scope.
Method boundary: Advice reflects a research tradition; clear writing cannot repair weak evidence.
Access: Author page provides video and slides; original video linked below.

YouTube · How to Write a Great Research Paper · Simon Peyton Jones ↗

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Source checked 2026-10-25 · Video addresses verified from author pages; recordings were not reviewed end to end.