Training activity information
Details
Using the results generated by a statistical analysis make use of appropriate data visualisation tools and communicate the relevant findings to:
- An expert audience
- A non-expert audience
Type
Developmental training activity (DTA)
Evidence requirements
Evidence the activity has been undertaken by the trainee.
Reflection on the activity at one or more time points after the event including learning from the activity and/or areas of the trainees practice for development.
An action plan to implement learning and/or to address skills or knowledge gaps identified.
Considerations
- Data visualisation tools
- Data visualisation methods
- Stakeholders needs
- Communication with a non-expert audience
Reflective practice guidance
The guidance below is provided to support reflection at different time points, providing you with questions to aid you to reflect for this training activity. They are provided for guidance and should not be considered as a mandatory checklist. Trainees should not be expected to provide answers to each of the guidance questions listed.
Before action
- What are the key findings from the statistical analysis? What data visualisation tools are appropriate for different types of data and audiences? How do you tailor communication for expert and non-expert audiences?
- What will you learn about creating effective data visualisations? How will you adapt your communication style for different levels of expertise?
- Will you explore different data visualisation techniques? Will you consider the key messages for both expert and non-expert audiences?
- How do you feel about communicating these findings to different audiences? Are you comfortable explaining technical information to both specialists and non-specialists?
In action
- For the expert audience, what types of visualisations are you currently creating to highlight the key findings? What level of detail are you including in your communication? For the non-expert audience, how are you simplifying the visualisations and the language to ensure understanding? What are the key messages you are trying to convey to each audience?
- Are the data visualisation tools effectively representing the findings? Are you finding it challenging to balance technical accuracy with clarity for different audiences? What are you learning about the principles of effective data visualisation and communication? How does this activity relate to your communication skills and understanding of different stakeholder needs?
- If an initial visualisation is too complex for a non-expert audience, are you trying alternative graphical representations? Are you adjusting your language and the level of technical detail based on your perception of the audience’s understanding? Are you seeking feedback on the clarity and effectiveness of your communication?
On action
- How did you tailor your visualisations and communication style for the expert audience? How did this differ for the non-expert audience? What key findings did you aim to communicate to each group? How effective do you think your visualisations were in conveying the information?
- What did you learn about the principles of effective data visualisation for different audiences? Did you find it challenging to balance technical detail with clarity for non-experts? How did your real-time decisions about visualisation types and language influence the communication of your findings? How important is audience understanding when communicating data analysis results? What are the key considerations when presenting data to both expert and non-expert stakeholders?
- How will you approach data visualisation and communication in the future? What data visualisation tools or techniques do you want to explore further? How will you assess the effectiveness of your communication with different audiences? What are your next steps to enhance your skills in communicating data analysis findings through visualisations?
Beyond action
- With your current understanding of data visualisation principles and tools, how would you refine the visualisations you created for both expert and non-expert audiences? Have you communicated data analysis findings to different audiences since this training activity? What strategies did you find most effective for each group? Did you learn new data visualisation techniques or tools that you could have used in this training activity? Review your reflect-on-action notes. How has your understanding of tailoring communication for different audiences evolved?
- Has this exercise improved your ability to select appropriate data visualisation techniques for different types of data and audiences? How has it highlighted the importance of clear and concise communication of complex findings to both experts and non-experts? Has this training activity enhanced your awareness of the potential pitfalls of data misrepresentation through visualisation? Has it influenced how you consider the audience’s understanding when preparing data summaries and presentations?
- What communication, visual design, and audience engagement skills did you develop through this training activity that will be invaluable for disseminating your work and influencing stakeholders? What further learning will you undertake to master advanced data visualisation techniques and communication strategies? How will your ability to effectively communicate data analysis findings contribute to your future role in translating data insights into policy and practice?
Relevant learning outcomes
| # | Outcome |
|---|---|
| # 4 |
Outcome
Summarise findings from data analysis for stakeholders using a variety of data visualisation techniques and considering the audiences understanding of the subject matter. |