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ABSTRACT
Multimodal interaction in everyday life seems so effortless. However, a closer look reveals that such interaction is indeed complex and comprises multiple levels of coordination, from high-level linguistic exchanges to low-level couplings of momentary bodily movements both within an agent and across multiple interacting agents. A better understanding of how these multimodal behaviors are coordinated can provide insightful principles to guide the development of intelligent multimodal interfaces. In light of this, we propose and implement a research framework in which human participants interact with a virtual agent in a virtual environment. 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. An experiment is designed and conducted to investigate adaptive user behaviors in a human-agent joint attention task. Multimodal data streams are collected in the study including speech, eye gaze, hand and head movements from both the human user and the virtual agent, which are then analyzed to discover various behavioral patterns. Those patterns show that human participants are highly sensitive to momentary multimodal behaviors generated by the virtual agent and they rapidly adapt their behaviors accordingly. Our results suggest the importance of studying and understanding real-time adaptive behaviors in human-computer multimodal interactions.

USA 2010 HCI Tobii eye tracking 1750 interact virtual adjust behavior patterns human-computer

in list: HCI & Usability

ABSTRACT
Explanatory visualization is a promising approach that has been used in many tutoring systems. This paper presents an attempt to assess the value of adaptation in the context of explanatory visualization. It shows that a system employing a user model and tracking users’ progress gives students an opportunity to interact with larger amount of material in the same amount of time.

USA 2008 Cognitive Behavioral Tobii eye tracking 1750 explanatory visualization progress interact material progressive user adaptation

in list: Cognitive & Behavioural Psychology

Abstract
We used eye-tracking to study 28 users when they evaluated result lists produced by web search engines. Based on their different evaluation styles, the users were divided into economic and exhaustive evaluators. Economic evaluators made their decision about the next action (e.g., query re-formulation, following a link) faster and based on less information than exhaustive evaluators. The economic evaluation style was especially beneficial when most of the results in the result page were relevant. In these tasks, the task times were significantly shorter for economic than for exhaustive evaluators. The results suggested that economic evaluators were more experienced with computers than exhaustive evaluators. Thus, the result evaluation style seems to evolve towards a more economic style as the users gain more experience.

economic exhaustive evaluators interact 2005 Tobii 1750 eye tracking

in list: HCI & Usability