ABSTRACT
The process of transforming data into sounds for auditory display provides unique user experiences and new perspectives for analyzing and interpreting data. A research study for data transformation to sounds based on musical elements, called data-to-music sonification, reveals how musical characteristics can serve analytical purposes with enhanced user engagement. An existing user engagement scale has been applied to measure engagement levels in three conditions within melodic, rhythmic, and chordal contexts. This article reports findings from a user engagement study with musical traits and states the benefits and challenges of using musical characteristics in sonifications. The results can guide the design of future sonifications of multivariable data.
ABSTRACT
We introduce a new architecture for e-textbooks which contains two navigational aids: an index and a concept map. We report results from an evaluation in a university setting with 99 students. The interaction sequences of the users were captured during the user study. We found several clusters of user interaction types in our data. Three separate user types were identified based on the interaction sequences: passive user, term clicker, and concept map user. We also discovered that with the concept map interface users started to interact with the application significantly sooner than with the index interface. Overall, our findings suggest that analysis of interaction patterns allows deeper insights into the use of e-textbooks than is afforded by summative evaluation.
