Visualizing partitioned data in Audience Response Systems : A design-driven approach

Sammanfattning: Meetings and presentations are often monological in their nature, creating a barrier of productivity in workplaces around the world. By utilizing modern technologies such as a web-based Audience Response System (ARS), meetings and presentations can be transformed into interactive exercises where the audience’s views, opinions and answers can be expressed. Visualizing these audience responses and relating questions-specific partitioned answers between each other, through visualization structures, was the topic of this report. The thesis project was carried out in collaboration with Mentimeter, creator of a web-based ARS and online presentation tool. The Double Diamond design process model was used to investigate and ground the design and development process. To guide the implementation of the prototypes, a focus group was held with four visualization and design professionals knowledgeable about ARSs, to gather feedback on high fidelity sketches. The final prototypes were evaluated with the extended Technology Acceptance Model (TAM) for information visualization to survey end-users' attitudes and willingness to adopt the visualization structures. Eight end-users tested the final web-based prototypes. The findings of the user tests indicate that both visualizations prototypes showed promise for visualizing partitioned data in novel ways for ARSs, with an emphasis on a circle cluster visualization as it allowed for the desired exploration. The results further imply that there is value to be gained by presenting partitioned data in ways that allows for exploration, and that audiences would likely adopt a full implementation of the visualizations given some added functionalities and adjustments. Future research should focus on fully implementing and testing the visualizations in front of a live audience, as well investigating other contemporary visualization structures and their capabilities for visualizing partitioned ARS data.