13,858 research outputs found
A Virtual Conversational Agent for Teens with Autism: Experimental Results and Design Lessons
We present the design of an online social skills development interface for
teenagers with autism spectrum disorder (ASD). The interface is intended to
enable private conversation practice anywhere, anytime using a web-browser.
Users converse informally with a virtual agent, receiving feedback on nonverbal
cues in real-time, and summary feedback. The prototype was developed in
consultation with an expert UX designer, two psychologists, and a pediatrician.
Using the data from 47 individuals, feedback and dialogue generation were
automated using a hidden Markov model and a schema-driven dialogue manager
capable of handling multi-topic conversations. We conducted a study with nine
high-functioning ASD teenagers. Through a thematic analysis of post-experiment
interviews, identified several key design considerations, notably: 1) Users
should be fully briefed at the outset about the purpose and limitations of the
system, to avoid unrealistic expectations. 2) An interface should incorporate
positive acknowledgment of behavior change. 3) Realistic appearance of a
virtual agent and responsiveness are important in engaging users. 4)
Conversation personalization, for instance in prompting laconic users for more
input and reciprocal questions, would help the teenagers engage for longer
terms and increase the system's utility
MANAGING A MIXED SKILL CLASS
In a digital environment students need to manage different types
of skills - cognitive, emotive and manual. When working in a
mixed-skill class the differences between student abilities can
disrupt the rhythm and style of the learning process and demand
flexibility in the teaching approach that is adopted
Optimising user engagement in highly automated virtual assistants to improve energy management and consumption
This paper presents a multi-dimensional taxonomy of levels of automation and reparation specifically adapted to Virtual Assistants (VAs) in the context of Human-Human-Interaction (HHI). Building from this framework, the main output of this study provides a method of calculation which helps to generate a trust rating by which this score can be used to optimise users' engagement. The authors believe that this framework could play a critical role in optimising energy efficiency in both management and consumption, particular attention has been given to the relevance of contextual events and dynamism in enhancing trust. For instance by understanding that trust formation is a dynamic process that starts before the user's first contact with the system, and continues long thereafter. Furthermore, following the evolving nature of the system, factors affecting trust and the system itself change during user interactions over time; thus, systems need to be able to adapt and evolve. Present work is being dedicated to further understanding of how contexts and its derivative unintended consequences affect trust in highly automated VAs in the area of energy consumption
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