Discussion

How To Use These Prompts

Use these prompts for breakout activities, quick pair work, or end-of-session reflection. They are grouped by course theme so you can return to them across the programme rather than treating discussion as a one-off activity.

Digital Tools and Research Identity

Use alongside Digital Tools.

1. Which digital systems are essential in your current workflow, and where do they overlap or conflict?
2. Where do people in your team store files now, and which part of that setup feels most fragile?
3. What makes a researcher identity feel consistent across ORCID, RIS, local profiles, and outputs?
4. Which digital security habit would reduce the most risk for your current work?

Digital Delivery and Coordination

Use alongside Digital Delivery.

1. Where does work in your team become stuck: planning, handover, review, or follow-up?
2. What would a two-week research sprint look like in your context?
3. Which responsibilities are clear in your projects, and which are assumed but undocumented?
4. What would shared ownership look like in practice rather than as a slogan?

Governance, Ethics, and Data Protection

Use alongside Data Governance & Policy.

1. What kinds of data in your work are obviously high risk, and which are easy to underestimate?
2. When people say “we have consent”, what important governance questions may still be unanswered?
3. Which project decisions should be escalated early rather than solved informally?
4. Where are role boundaries around controller, processor, PI, and project team currently unclear?

Research Data Management

Use alongside Research Data Management.

1. If someone joined your project tomorrow, what would they struggle to find or understand?
2. Which part of your current DMP or data handling plan is most vague in practice?
3. How do you currently separate raw, cleaned, and derived data, if at all?
4. What is one realistic step that would make your data more reusable in six months?

Collecting, Organising, and Exploring Data

Use alongside Collecting the Right Data and Organising and Exploring Data.

1. What makes a data source trustworthy enough for your context?
2. Which variable or category decisions most affect data quality in your work?
3. What does “messy data” look like in your team?
4. What do you usually notice first when exploring a new dataset: missingness, outliers, patterns, or confusion about meaning?

Visualisation, Interpretation, and Impact

Use alongside Making Sense of Data and Insight to Impact.

1. What makes a visual convincing but still misleading?
2. Which kinds of context are often missing when data are presented in your area?
3. When does an insight become actionable rather than merely interesting?
4. What kinds of feedback reveal blind spots, and what kinds only add noise?

AI in Research

Use alongside How AI Impacts Research and How to Use AI in Research.

1. Which parts of the research lifecycle feel most changed by AI already?
2. Where does AI save time in your work, and where does it create checking work?
3. What should always remain a human responsibility in your context?
4. What would count as transparent and defensible AI use in your team?
5. Which prompt or workflow improvement would make AI use more useful without making it less trustworthy?

Group Debrief Format

After a small-group discussion, ask each group to report:

• Summarize one practical change your group recommends.
• Identify one barrier to implementing that change.
• Propose one realistic first step for the next 2–4 weeks.

End-of-Course Reflection

Use these prompts near the end of the course or as follow-up reflection.

1. Which one part of your workflow do you now see differently?
2. What is one decision you can make more confidently than before?
3. Which support service, platform, or practice do you need to engage with next?
4. What will you change first: tooling, documentation, governance, collaboration, or analysis practice?