About Course
Course Code: RM-F01 | Status: IN DEVELOPMENT (Group A — Launch Priority) | Format: Self-paced, knowledge-first
Overview
Establishes how researchers reason about evidence, questions, and claims, distinguishing sound argument from assertion.
Target Learners
Undergraduate, postgraduate, and doctoral students; lecturers; early-career and established researchers; journal authors; research assistants; and institutional research teams.
Prerequisites
None for foundation courses; see course page for level-specific prerequisites.
Module Structure (proposed)
- Module 0 — Start Here: orientation and responsible use
- Modules 1–5 — core knowledge, methods, and applied practice
- Final module — applied project and assessment
Assessment
Knowledge checks, applied exercises (not only multiple-choice), and a final applied project. Certificate of Completion on meeting all requirements.
Instructor
INSTRUCTOR PENDING OWNER CONFIRMATION. Course materials were developed with AI assistance and are subject to human academic review.
Research Ethics & Responsible AI
This course requires acknowledgement of the School’s Research Ethics and Responsible AI policies. Evidence must never be invented; AI cannot replace scholarly judgment.
Enrollment
Price: Owner Approval Required. Enrollment opens after substantive content is complete and tested.
What this course is about
A great deal of research fails before any data is collected, because the question being asked cannot be answered by any evidence. This course is about the stage most training skips: deciding what is worth investigating, what would count as an answer, and what claim the resulting evidence can honestly support.
How the course is structured
The first part deals with questions. Students take vague research interests — their own, where possible — and work them into questions that are specific, answerable, and worth answering. This is harder and more useful than it sounds; most participants discard their first three attempts.
The second part deals with evidence. What kinds of evidence exist, what each kind can and cannot establish, and how method choices constrain the conclusions available later. The emphasis is on fit rather than hierarchy: there is no universally superior method, only methods appropriate to particular questions.
The third part deals with claims. Students examine published work — including well-regarded published work — and identify where conclusions outrun the evidence presented. Doing this to others makes it considerably easier to notice when doing it oneself.
What you will be able to do
You should finish able to formulate a researchable question, choose a method for stated reasons rather than habit, read empirical literature critically enough to see what it has not established, and write claims that are calibrated to your evidence. You should also be able to recognise when a project should be abandoned, which saves more time than any other research skill.
Who it suits
Postgraduate students beginning a thesis, lecturers supervising research for the first time, professionals who must commission or evaluate studies, and anyone who has been asked to produce evidence for a decision and is not sure where to start. No statistical background is assumed.
The course functions as the entry point to the School of Research Methodology & Academic Practice, and pairs naturally with courses on academic writing and publication. Related titles and reference material are held in the Library, and the wider curriculum is set out in the Academy.
Course Content
Module 0 — Start Here
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Lesson 0.1 — Welcome and How This Course Works
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Lesson 0.2 — Research Ethics and Responsible AI
Module 1 — Evidence, Questions, and Claims
Module 2 — Reading and Evaluating Research
Module 3 — Applied Project
Student Ratings & Reviews
