Research Studio

Add a journal entry

Record decisions, changes of mind, insights and tutor feedback as they happen. This journal - with the idea histories - is the raw material for analysing your development process later. Paste a session summary into the Word development record at the end of each working session.

What happened, and why?

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How to use this studio

• Ideate. + New idea, at the right of the search box, creates a full idea card in any stage. Your ideas move through Sparks → Exploring → Researching → Shortlist → Chosen, with Archived for ideas set aside - nothing is ever permanently deleted, so changes of mind are cheap and recorded. Drag a card into Archived (or anywhere else) to move it there directly; every move is logged in the idea's history.
• Sparks column. Type an idea in the box at the top: Add spark records it as-is. The Spark generator asks for a fuller picture of a topic area - description, short name, who it's for, the itch, constraints - and how many sparks to spin (1 - 20). The richer the entry, the more specific the angles: lenses cover scope, stakeholders, evidence, adoption, accountability, regulation, practice, time and combinations, plus lenses built from your audience, problem, constraints and the keywords in your description. It's a mechanical divergence aid, produced locally by rules, not by AI (artificial intelligence) - and your full entry is saved to the Journal with each run. Rate any spark 1 - 5 for interest and the column ranks highest first. Promote moves a keeper to Exploring; ✕ archives a spark into the Archived column.
• Idea detail. Click a card to sharpen the research question, log research findings with links and takeaways (Download references (.ris) sends a research log to Zotero; All references (.ris) in Session summary sends every one), note pros and cons, and score against your criteria. The search links run a one-click exploratory search on Scholar, Semantic Scholar, Consensus and Connected Papers. Under them, a Deep research prompt - built from the idea, editable, Copy prompt - asks a deep research tool to map the literature: coverage, the main positions, gaps, recent developments, methods and a search string, citing only sources it found, each with a link or DOI. Check every source before you use it.
• Compare. Weighted scores put your shortlist side by side, using your 100-point criteria budget from Settings. Treat the numbers as a conversation starter, not a verdict - a low score on curiosity should worry you more than a low score on anything else.
• Plan. The twelve weeks as tasks in four phases - Explore and orient, Choose your track, Build your project, Submit - drawn from the course's own Topic 1-3 material. Switch between a Gantt timeline (bars across the weeks, the Moodle area-choice window, milestones and today's date) and a Kanban board you can drag between To do, In progress and Done. Add your own tasks and sub-tasks, and move any date to fit your plan - in the Gantt, drag a bar to move a task, drag its ends to change its dates, or drag it up or down to reorder it. Dashed bars mark estimated dates: only the Moodle area window, the course's own week-9 literature review example and your submission date come from the course, so treat the rest as a starting point. Every status change is logged in the Journal as a Task update.
• Project setup. The Project setup tab fits the Studio to your project and your course: institution, programme, what you call the project, dates, phases, tasks, deliverables, assessment criteria, course rules and thematic areas. If your lecturer gave you a project template, load it first, under From your lecturer - the .zip, or the .json inside it: what your lecturer set shows read-only, with a lock and "Set by your lecturer", and nothing else you bring in changes it. Otherwise start Phases and tasks from a plan path - a general research project, a classic academic thesis, a business consultancy report, a company process analysis, a business plan, a practitioner book or a PhD over 3 or 4 years - fitted to your dates, then change anything. Fill in the rest by hand, or copy its interview prompt into any AI chatbot - ChatGPT, Gemini, Copilot or Claude - and paste the reply back. Record your course rules - AI use, referencing, word limits, extensions, ethics and more - with where each one says so and when you last checked it; your plan reminds you to check them again. Add your brief or handbook as a PDF, Word or text file and the Studio reads it on this computer, keeping the text but never the file. Every date it finds goes into your setup - one entry for each date and the thing it marks, filling in a date you left blank, or as a new task - and any it isn't sure of is marked Check this date; Re-read all documents does the same again, for documents you added before. The Studio merges everything, lists anything that disagrees under Needs your decision, and changes nothing in your plan until you save.
• Lecturers. Tick "I'm a lecturer" in Settings and a Lecturers tab appears. Build a project template for your course with the same form as Project setup - from a blank page, a plan path or a setup you already have - and choose, item by item, what students may change: untick "Students can change this" on anything every student should keep, untick "Students can add their own" to close a list, and tick "Fixed deadline" to keep a task's dates fixed on every student's plan. Download gives one .zip - the template and a one-page PDF telling students how to load it. Templates stay in your browser, never in your backups, so keep the .zip; Open a template file brings one back. Change a template after downloading it and it becomes the next version: students load it the same way, and keep their progress.
• Roadmap. The Roadmap button, at the top, shows what's being built, what's planned next and what's shipped - read from the Studio's website each time you open it, so it stays up to date between versions.
• Suggested prompts for Claude. Open any task to see a prompt built from the task, your current week and your leading idea - it updates as your plan changes. It asks for credible academic sources as APA 7 references with their links written out, and for a .ris file to import into Zotero - open and read every source before you cite it. Edit it and your version is kept; Reset to auto brings the suggestion back. Copy prompt copies it for any AI (artificial intelligence) assistant; Open in Claude starts Claude Code on this computer with the prompt typed in, ready for you to read and send - nothing is sent until you press Enter, and it needs Claude Code installed. Treat every source a prompt brings back as a lead: find it, open it and read it before you cite it.
• Submission readiness. At the foot of the Plan, six criteria the course states outright in Topics 1-2, each ticked when its linked tasks are done. The set is provisional until Topic 6 publishes the official evaluation criteria - when it does, check against those instead.
• Journal. The sequential record of decisions and changes of mind. End each working session by adding at least one entry, then use Session summary to copy a digest into the Word development record.
• A suggested rhythm. One 25-minute pass per week until week 5: run the coaching prompt at the top, touch three cards, log one journal entry, Save my data.

Hover any button for a one-line explanation of what it does.

Your data - read this once

• Everything autosaves to this browser on this machine (localStorage). Nothing leaves your computer except what you choose to send through the feedback form.
• Course files you add in Project setup are read on this computer, and only their text is kept - never the file. The first time you add a PDF, the Studio downloads its PDF reader (PDF.js) from jsDelivr, a public code library host, and checks it against a fixed fingerprint before it runs; your file is never sent anywhere.
• Backups use JSON (JavaScript Object Notation) files - plain text, readable anywhere, openable in any editor.
• In Chrome and Edge, Save my data and Load my data remember the last folder you used, so the dialog opens there next time instead of your default Downloads folder. Safari and Firefox don't support this yet - Save/Load work exactly as before, opening the normal system dialog each time.
• Autosave is per browser: open the studio in a different browser or on another machine and it starts fresh.
• Three choices stay in this browser only and never go into your backups: the folder Open in Claude Code uses, "Don't show this on start-up", and "I'm a lecturer". A lecturer's templates stay in the browser too - the .zip they download is the copy to keep.
• Keep the studio open in one tab at a time. Two open copies save over each other's changes, and the studio warns you if it spots another one.
• The Word development record remains the canonical narrative of the project; this studio feeds it.
• Backward compatibility promise. Updates never cost you data: old JSON backups always import through a migration chain; backups from a newer version are refused rather than half-read; anything unreadable is preserved to a recovery slot instead of overwritten; and the studio snapshots your current workspace automatically before any import replaces it.

Your project and course

Timeline and milestones

Deadlines and key dates keep their calendar dates; phases count in weeks from your start date ( - change it in Settings or Project setup).

Edit your project setup

What the research project asks of you

Three connected deliverables, produced over roughly twelve weeks. Everything in this panel and the next comes from the course's own Topic 1-3 videos, transcripts and slides on Moodle, the Digital4Business (D4B) learning platform.

Deliverable	What it is
Project Work	A focused dissertation of about 20 pages. Take ownership of a real, relevant challenge in your area, identify the problem through a literature review, then propose a solution - software, code, a digital strategy, a product concept or a detailed case study. Suggested outline: Introduction (400-600 words, written last) → Literature Review (1,200-1,800 words) → Methodology → Solution or Proposed Approach → Discussion → Conclusion → References in APA (American Psychological Association) style.
Digital Artefact	A visual or interactive expression of the project - a presentation, prototype or mock-up, short demo video or any digital format that shows what the result could look like. Build it alongside the writing, not after it, and submit it in a shareable form, ideally a PDF or a link.
Video Presentation	About 10 minutes of you presenting your project, your thinking and your solution. It serves as your viva (oral examination) and the academic team reviews it.

How they're marked. No weighting has been published for the September 2026 intake. Topic 6 (Project Evaluation and Reflection) covers the criteria projects are evaluated against - read it as soon as it opens and check your drafts against it.

The six topics on the platform

Six short video topics from the partner universities. They open in sequence as you mark each one complete on Moodle, and each university releases its material on its own schedule.

#	Topic (Moodle title)	Delivered by	What it gives you
1	Introduction and Project Proposal Development	UNIBO (University of Bologna)	The three deliverables, the twelve-week structure, and moving from a question to a plan
2	Research Methodologies	UNIBO	Writing the introduction, and the literature review step by step
3	Scientific Writing for Projects	UNL (Universidade NOVA de Lisboa - NOVA University Lisbon)	What makes scientific writing good, drafting habits, readability and the structure of a paper
4	Ethical Considerations and Sustainability in Digital Projects	NCI (National College of Ireland)	Governance, ethics, regulation and sustainability in your project, with a reflection exercise
5	Project Presentation and Communication Skills	LiU (Linköping University)	Structuring your narrative, visual materials and delivery - the groundwork for the video presentation
6	Project Evaluation and Reflection	UNIBO	The evaluation criteria, self-assessment and reflection on what you'd do differently

The four thematic areas

Code	Area	Tutor team
LiU	Data-Driven Decision Systems and Ethical AI Solutions for Business - data, intelligence and responsibility: cybersecurity, risk, compliance, ethics and law of AI (artificial intelligence) in business	Linköping University
NOVA	Data Science for Business - the full data science lifecycle with ethics and privacy built in	NOVA IMS (Information Management School), Lisbon
NCI	Cloud Computing for Business - cloud fundamentals, the NIST (National Institute of Standards and Technology) framework, governance and data protection in cloud adoption	National College of Ireland
UNIBO	Digital Transformation - strategies, platform business models, digital competences, sustainability and the UN SDGs (United Nations Sustainable Development Goals)	University of Bologna

Choosing your area. You pick your area, and with it your supervising university, in a Moodle activity with capped places (25 per area for the September 2026 intake). Read the area descriptions and tutor contacts on the activity page before the window opens - it isn't a form to leave to the last day. Once you've chosen, contact your tutor team with your idea.

Timeline and milestones

Weeks	Phase
1-5	Explore and orient - work through the platform topics, read, and find your question.
5-6	Choose your track - select your thematic area on Moodle. By then you should know your research question, have found the problem in the literature and have started thinking about the solution.
7-12	Build your project - write the Project Work and develop the Digital Artefact, with tutor support and office hours.
12-14	Submit - after the exam period, upload all three deliverables.

Dates below are computed from your start date ( - change it in Settings). The thematic-area window uses the September 2026 intake's dates, set relative to that start - check Moodle for the exact times.

Doing the work well

Find your question, then plan (Topic 1)

• A topic is broad; a question is focused. "Artificial intelligence in business" is a topic. "How do small and medium-sized enterprises (SMEs) manage the ethical risks of AI-driven hiring systems?" is a starting question.
• Before you commit, run exploratory searches in Google Scholar, Scopus or Web of Science. If someone has already reviewed the topic thoroughly, find a different angle or narrow it. One specific idea researched thoroughly beats a broad theme skimmed.
• Turn the idea into a plan: broad aims, broken into objectives that each have a timeline and an expected output. Make them SMART (specific, measurable, achievable, realistic, time-bound) - not "write the literature review" but "complete a first draft of the literature review covering at least 15 sources by the end of week 9". Put the timeline in a Gantt chart and review it every week.

Writing the introduction (Topic 2)

About 400-600 words, roughly 10% of the project. It has five components. They don't need their own headings - treat them as a checklist, and they'll usually flow across three or four paragraphs.

Component	What it does	Rough length
Background	The wider context: what's happening in the field that makes this relevant now. Orientation, not the literature review.	200-250 words together
Research focus	Narrow to your corner of the field and state your research question explicitly - don't bury it.
Aim and objectives	One aim (what you want to achieve) and a short list of specific, active objectives (how you'll get there), each tied to a phase of the work.	100-150 words
Methods and timescales	A high-level note on how you did the research - literature review, case study, prototype or a mix - and its scope and timeframe.	60-80 words
Value of the research	The "so what?": who benefits, what it contributes that didn't exist before, and the practical implications. The component most students underwrite.	80-120 words

Write it last. Draft a rough placeholder at the start to orient yourself, then write the real introduction once the literature review, solution and conclusions exist.

Doing the literature review (Topic 2)

• It's an argument, not a list of summaries. Map what's known, show where knowledge is incomplete or contested, and end on what remains unknown and how your project contributes. That gap is where your solution starts.
• The five-step loop: identify the topic → define your terms (key terms and their synonyms) → set boundaries (inclusion and exclusion criteria such as date range, geography, study type and language - you'll justify them in the methodology) → select sources (titles and abstracts first, then full text) → analyse sources (does each one confirm, contradict, extend or challenge the others?). Then loop back as findings reshape the question.
• Search at least two or three databases: Google Scholar (the easy starting point), DOAJ (Directory of Open Access Journals), CORE (an aggregator of open-access papers), Semantic Scholar and SSRN (Social Science Research Network).
• Build your search string from a concept map and combine the concepts with Boolean operators, written in capitals: AND narrows (every concept must appear), OR broadens (use it for synonyms), NOT excludes - carefully, as it can drop relevant papers. For example: (artificial intelligence OR machine learning) AND (hiring OR recruitment) AND (ethics OR fairness OR bias). Long strings work best in Semantic Scholar or Scopus; keep Google Scholar searches simpler, with a few quoted phrases.
• Three more techniques: truncation - organ* finds organisation, organisational and organise; phrase search - "digital transformation" in quotes finds the two words together, in that order; citation chasing - take one relevant, well-cited paper, look at who has cited it since, and work back through its own reference list.
• Keep a synthesis matrix (author, year, aims, methods, findings, strengths, limitations, relevance). Organise the write-up by theme - usually the strongest choice for a Project Work - or chronologically, or by method.
• Aim for 1,200-1,800 words, the longest section. Under 1,000 is likely too thin to justify a solution.
• Set up Zotero before you start searching and save each paper the moment you find it; it formats APA citations in Word and Google Docs.
• Specialised AI research tools (Consensus, Elicit, Research Rabbit, Connected Papers, SciSpace) search real literature and are fine for exploring - but verify every source in Google Scholar or CORE and read the paper before citing it. General chatbots (ChatGPT, Claude, Gemini) can map a topic, suggest search terms and suggest sources - ask for credible academic sources as APA 7 references with each DOI or link written out, then find every one, open it and read it before you cite it: fabricated references are among the most common and serious mistakes.
• Which kind of review? Topic 2's decision tree, "What Type of Review Is Right For You?" (on Moodle, login needed), points a solo twelve-week project to a literature (narrative) review. Systematic, scoping and umbrella reviews assume a team of three or more and 12-18 months; a rapid review applies systematic methods with shortcuts under time pressure; a meta-analysis combines quantitative results statistically.

Writing it well (Topic 3)

• Five qualities: clarity (unambiguous), conciseness (every word earns its place), structure (a logical progression - journal papers use IMRaD: Introduction, Methods, Results and Discussion), objectivity (evidence, not belief) and consistency (the same terms and tone throughout). "Performed really well on some datasets" becomes named datasets and measured results.
• Let verbs do the work. Avoid nominalisations - verbs turned into abstract nouns. "The evaluation of the model's accuracy was followed by a comparison of its performance" becomes "We evaluated the model's accuracy and compared its performance".
• Draft in stages - Franklin's (1986) three-stage model: outline (a few words, sentences or a visual map), draft (then shift and sort, moving whole paragraphs), and only then edit each sentence. Avoid both extremes: perfecting every sentence before moving on, and rushing a draft without caring how messy it is. With an hour to write, try four 15-minute drafts rather than one.
• Start from one page. Before designing the full project, draft a one-page overview: problem, research question, aims, data sources, method and why it matters.
• Make writing a habit: small, regular amounts while you're fresh, in protected half-hour blocks. Track time spent writing, pages finished and the share of planned tasks done (Creswell, 2014).
• Readability: use one term per concept throughout - no synonyms for your key variables - and keep the same order whenever you mention independent and dependent variables. Wilkinson's hook-and-eye exercise tests flow: circle the words that carry a new idea forward (hooks) and box the words that refer back (eyes). Too few eyes reads as disjointed; too few hooks reads as repetitive.
• Final pass (Creswell, 2014): cut unnecessary words, prefer the active voice, keep at most one qualifier, drop overused phrases, go easy on quotations, italics and asides, and use strong verbs. Tense: past for the literature and your results, present to introduce the study and discuss results, future for a proposal.
• Parts of a paper: the PLOS (Public Library of Science) author guides cover the title and the rest of the manuscript (study design, keywords, the finding), the abstract (background, aims, methods, results, conclusions), the methods section (enough detail for someone to reproduce the work), reporting statistics (never manipulate results), discussions and conclusions (your results, related research, how they compare with your starting hypothesis, and one take-home message) and editing (set goals first, check the draft against them, rest it for a day or two, one idea per sentence, no double negatives, and say exactly how often and which sources).

Do's and don'ts (Topics 1 and 2)

Area	Do	Don't
Question	Narrow to a specific, researchable question with a gap the literature shows.	Settle on a broad topic like "AI in business" with no gap and no boundary.
Literature review	Build the argument for why your project is needed.	List paper summaries without synthesis.
Solution and artefact	Propose a realistic, well-reasoned solution that answers the gap, and make it tangible in an artefact built alongside the writing. It doesn't need to be fully built or tested.	Start with a solution and hunt for a problem to attach it to, or build the artefact after the text is finished.
Video	Keep to about 10 minutes: your project, your thinking and your solution. It's your viva.	Leave it to the end - Topic 5 covers presenting in depth.
AI tools	Use them to rephrase an unclear sentence, as a thinking partner, or to steelman the opposing view and find weaknesses in your argument.	Let them write the text, cite a source you haven't found and read yourself, or confirm what you already think.
Your tutor	Bring a specific question, a draft paragraph, sources you're unsure of or a decision you can't make alone. Email a short summary afterwards.	Ask "am I on the right track?" in the abstract.
Time	Plan backwards from submission and review the plan weekly. On low-energy days, do the mechanical work - references, formatting, re-reading annotated sources.	Leave the reading and writing for the last few weeks.

Sources: the Topic 1-3 materials on Moodle; Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches. SAGE, as adapted in the Topic 3 slides; the PLOS author resources linked above.

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