Data visualisation transforms data and information into graphical representations. What tools do designers use to ensure the resulting visualisations are simultaneously accurate and enthralling?
You will explore the theory and practice of transforming sometimes complex datasets into compelling visual narratives. You will learn to interpret and communicate data effectively, exploring various visualization techniques and tools. Emphasis is placed on understanding the principles of information design, including hierarchy, clarity, and accessibility as well as data ethics and importance of accuracy in creative solutions.
On completion of this module you will be able to analyse datasets and generate stories around them, honing your ability to distil insights and engage audiences through visually impactful design outcomes. You will be proficient in creating data-driven design solutions that inform and engage. You will emerge with a heightened understanding of the role of graphic design in shaping perceptions and facilitating understanding in an increasingly data-driven world.
Workshop / studio - 40 hours
Main Assessment Methods:
Presentation: 10-minute pitch plus pitch deck worth 20%.
Project: to include presentation, presentation slide deck, project brief(s), final outcome(s), and supporting documentation. worth 80%. This Assessment is Pass Compulsory.
Reassessment Method: Like-for-like
On successfully completing the module, students will be able to:
1. Recognise and apply theories underpinning data visualisation, conducting research to explore diverse approaches and methodologies. (A2)
2. Analyse the effectiveness of data visualisation solutions and utilise critical thinking skills to assess the clarity, accuracy, and impact of visual narratives. (A5)
3. Create and implement innovative design solutions that effectively communicate data crafting coherent and engaging visual narratives which convey meaningful insights and provoke audience engagement. (B2)
4. Evaluate their own work, identifying strengths and weaknesses in their data visualization practice. Through reflective analysis, they will refine their skills and strategies that lead to iterative improvement in their work. (A7, C4)
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