Prototyping Visual Learning Analytics Guided by an Educational Theory Informed Goal

Prototype work can support the creation of data visualizations throughout the research and development process through paper prototypes with sketching, designed prototypes with graphic design tools, and functional prototypes to explore how the implementation will work. One challenging aspect of data visualization work is coordinating the expertise of people from a variety of roles to produce data visualizations guided by an educational theory informed goal (ETIG) in order to better support research. When collaborating, concessions must be made: typically, everyone seeks to follow the best practices established within their own disciplines. This paper attempts to illustrate how to rethink this interdisciplinary approach to adhere more strictly to educational research goals and consider how we may need to, at times, break away from best practices with the intent to evaluate the novel decisions resulting from this approach. A case study of the creation of a self-reported emotional measure is used to illustrate this type of collaboration. By taking this approach, a clear departure from best practices occurs in the scale selection for the visualization in order to support the ETIG