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ABSTRACT
Visual analytics is often based on the intuition that highly interactive and dynamic depictions of complex and multivariate databases amplify human capabilities for inference and decision-making, as they facilitate cognitive tasks such as pattern recognition, association, and analytical reasoning (Thomas and Cook 2005). But how do we know whether visual analytics really works? This article offers a generic evaluation approach combining theory- and data-driven methods based on sequence similarity analysis. The approach systematically studies users' visual interaction strategies when using highly interactive interfaces. We specifically ask whether the efficiency (i.e., speed) of users can be characterized by specific display interaction event sequences, and whether studying user strategies could be employed to improve the (interaction) design of the dynamic displays. We showcase our approach using a very large, fine-grained spatiotemporal dataset of eye movement recordings collected during a controlled human subject experiment with dynamic visual analytics displays. With this methodological approach based on empirical evidence, we hope to contribute to a deeper understanding of how people make inferences and decisions with highly interactive visualization tools and complex displays.

Switzerland 2010 HCI Usability Tobii eye tracking X120 visual analytics strategy interactions dynamic display efficiency design

in list: HCI & Usability

ABSTRACT
A better understanding of the human user’s expectations and sensitivities to the real-time behavior generated by virtual agents can provide insightful empirical data and infer useful principles to guide the design of intelligent virtual agents. In light of this, we propose and implement a research framework to systematically study and evaluate different important aspects of multimodal real-time interactions between humans and virtual agents. Our platform allows the virtual agent to keep track of the user’s gaze and hand movements in real time, and adjust his own behaviors accordingly. Multimodal data streams are collected in human-avatar interactions including speech, eye gaze, hand and head movements from both the human user and the virtual agent, which are then used to discover fine-grained behavioral patterns in human-agent interactions. We present a pilot study based on the proposed framework as an example of the kinds of research questions that can be rigorously addressed and answered. This first study investigating human-agent joint attention reveals promising results about the role and functioning of joint attention in human-avatar interactions.

USA 2010 Tobii eye tracking 1750 HCI evaluate multimodal real-time interactions virtual avatar attention

in list: HCI & Usability

ABSTRACT
User-system interactions (e.g., mouse clicks and movements) can be logged with the uLog computer program. A Web-based study with 20 participants was conducted to investigate the feasibility of using uLog data as an indicator of workload and attention. Eye fixation, heart rate variability (HRV), and skin conductance were used to unveil users' workload and attention and, hence, to validate uLog data as indicators of these. Results on one of the Tasks did indeed show correlations between uLog data and HRV. This is a promising first step toward the validation of uLog mouse data as indicators of workload and attention.

Netherlands 2009 Cognitive Behavioral Tobii eye tracking interactions log workload attention

in list: Cognitive & Behavioural Psychology

ABSTRACT
Eye tracking is now used regularly in static display analysis
but making sense of eye movements over dynamic scenes
such as game play is still problematic. This paper describes
how an eye tracker can be incorporated into a configuration
that permits the synchronous capture of eye movements and
dynamic scenes from a game. This configuration is then
used to conduct an experiment in which eye movement
recordings are analysed to reveal one possible reason why
even expert players become trapped at a particular level in a
game. A quantitative analysis of eye fixations is also
undertaken in order to look for signs of stress or frustration
during play. An innovative way of using the same fixation
data is then described which enables not only differences in
fixation distribution over the dynamic display scenes to be
evaluated but also enables the differentiation between scan
path sequences which are thought to evidence game play
differences.

HCI Dynamic scenes eye tracking games player interactions UK 2007 Tobii 1750

in list: HCI & Usability