Journal paper at IEEE TVCG / VIS 2017
Our publication The explanatory visualization framework: An active learning framework for teaching creative computing using explanatory visualizations was presented in IEEE VIS2017, held in Phoenix, AZ, USA.
While visualization techniques are starting to pervade our work and leisure, we feel that there are many opportunities to use explanatoryvisualizations in teaching and learning. The Explanatory Visualization Framework (EVF) guides a learner to think through an explanatory visualization task, consider alternative solutions and reflect on their design, implementation choices, and actions. The framework is designed to provide a good balance between fostering creative thinking and providing the structured guidance that students need. It also enables teachers to swap-in their favoured exercise or assessment and apply the model to their situation. By creating their own explanatory visualizations, students learn and develop their creative, reflection and communication skills.
J. C. Roberts, P. D. Ritsos, J. Jackson, and C. Headleand, “The explanatory visualization framework: An active learning framework for teaching creative computing using explanatory visualizations,” IEEE Transactions on Visualization and Computer Graphics, vol. 24, no. 1, pp. 791–801, Jan. 2018.
Visualizations are nowadays appearing in popular media and are used everyday in the workplace. This democratisation of visualization challenges educators to develop effective learning strategies, in order to train the next generation of creative visualization specialists. There is high demand for skilled individuals who can analyse a problem, consider alternative designs, develop new visualizations, and be creative and innovative. Our three-stage framework, leads the learner through a series of tasks, each designed to develop different skills necessary for coming up with creative, innovative, effective, and purposeful visualizations. For that, we get the learners to create an explanatory visualization of an algorithm of their choice. By making an algorithm choice, and by following an active-learning and project-based strategy, the learners take ownership of a particular visualization challenge. They become enthusiastic to develop good results and learn different creative skills on their learning journey.