Adult Learning Sign Language by combining video, interactivity and play

One in every six persons in the UK suffers a hearing loss, either as a condition they have been born with or a disorder they acquired during their life. 900,000 people in the UK are severely or profoundly deaf and based on a study by Action On Hearing Loss UK in 2013 only 17 percent of this population, can use the British Sign Language (BSL). That leaves a massive proportion of people with a hearing impediment who do not use sign language struggling in social interaction and suffering from emotional distress, and an even larger proportion of Hearing people who cannot communicate with those of the deaf community. This paper presents a theoretical framework for the design of interactive games to support learning BSL supporting the entire learning cycle, instruction, practice and assessment. It then describes the proposed design of a game based on this framework aiming to close the communication gap between able hearing people and people with a hearing impediment, by providing a tool that facilitates BSL learning targeting adult population. The paper concludes with the planning of a large scale study and directions for further development of this educational resource

Integrating Haptic Feedback into Mobile Location Based Services

Haptics is a feedback technology that takes advantage of the human sense of touch by applying forces, vibrations, and/or motions to a haptic-enabled device such as a mobile phone. Historically, human-computer interaction has been visual - text and images on the screen. Haptic feedback can be an important additional method especially in Mobile Location Based Services such as knowledge discovery, pedestrian navigation and notification systems. A knowledge discovery system called the Haptic GeoWand is a low interaction system that allows users to query geo-tagged data around them by using a point-and-scan technique with their mobile device. Haptic Pedestrian is a navigation system for walkers. Four prototypes have been developed classified according to the user’s guidance requirements, the user type (based on spatial skills), and overall system complexity. Haptic Transit is a notification system that provides spatial information to the users of public transport. In all these systems, haptic feedback is used to convey information about location, orientation, density and distance by use of the vibration alarm with varying frequencies and patterns to help understand the physical environment. Trials elicited positive responses from the users who see benefit in being provided with a “heads up” approach to mobile navigation. Results from a memory recall test show that the users of haptic feedback for navigation had better memory recall of the region traversed than the users of landmark images. Haptics integrated into a multi-modal navigation system provides more usable, less distracting but more effective interaction than conventional systems. Enhancements to the current work could include integration of contextual information, detailed large-scale user trials and the exploration of using haptics within confined indoor spaces

The role of trust and relationships in human-robot social interaction

Can a robot understand a human's social behavior? Moreover, how should a robot act in response to a human's behavior? If the goals of artificial intelligence are to understand, imitate, and interact with human level intelligence then researchers must also explore the social underpinnings of this intellect. Our endeavor is buttressed by work in biology, neuroscience, social psychology and sociology. Initially developed by Kelley and Thibaut, social psychology's interdependence theory serves as a conceptual skeleton for the study of social situations, a computational process of social deliberation, and relationships (Kelley&Thibaut, 1978). We extend and expand their original work to explore the challenge of interaction with an embodied, situated robot. This dissertation investigates the use of outcome matrices as a means for computationally representing a robot's interactions. We develop algorithms that allow a robot to create these outcome matrices from perceptual information and then to use them to reason about the characteristics of their interactive partner. This work goes on to introduce algorithms that afford a means for reasoning about a robot's relationships and the trustworthiness of a robot's partners. Overall, this dissertation embodies a general, principled approach to human-robot interaction which results in a novel and scientifically meaningful approach to topics such as trust and relationships.Ph.D.Committee Chair: Arkin, Ronald C.; Committee Member: Christensen, Henrik I.; Committee Member: Fisk, Arthur D.; Committee Member: Ram, Ashwin; Committee Member: Thomaz, Andre