Mutlu Belgin, Sabol Vedran, Gursch Heimo, Kern Roman
2016
From Data to Visualisations and Back: Selecting Visualisations Based on Data and System Design Considerations
arXiv
Graphical interfaces and interactive visualisations are typical mediators between human users and data analytics systems. HCI researchers and developers have to be able to understand both human needs and back-end data analytics. Participants of our tutorial will learn how visualisation and interface design can be combined with data analytics to provide better visualisations. In the first of three parts, the participants will learn about visualisations and how to appropriately select them. In the second part, restrictions and opportunities associated with different data analytics systems will be discussed. In the final part, the participants will have the opportunity to develop visualisations and interface designs under given scenarios of data and system settings.
Luzhnica Granit, Pammer-Schindler Viktoria, Fessl Angela, Mutlu Belgin, Veas Eduardo Enrique
2016
Designing Generic Visualisations for Activity Log Data
Workshop on Awareness and Reflection in Technology Enhanced Learning (ARTEL16) CEUR-WS Lyon
Especially in lifelong or professional learning, the picture of
a continuous learning analytics process emerges. In this proces
s, het-
erogeneous and changing data source applications provide data
relevant
to learning, at the same time as questions of learners to data cha
nge.
This reality challenges designers of analytics tools, as it req
uires ana-
lytics tools to deal with data and analytics tasks that are unk
nown at
application design time. In this paper, we describe a generic vi
sualiza-
tion tool that addresses these challenges by enabling the vis
ualization
of any activity log data. Furthermore, we evaluate how well parti
cipants
can answer questions about underlying data given such generic
versus
custom visualizations. Study participants performed better in
5 out of
10 tasks with the generic visualization tool, worse in 1 out of 1
0 tasks,
and without significant difference when compared to the visuali
zations
within the data-source applications in the remaining 4 of 10 ta
sks. The
experiment clearly showcases that overall, generic, standalon
e visualiza-
tion tools have the potential to support analytical tasks suffi
ciently well