Hypertext development should benefit from a systematic, structured development, especially in the case of large and complex applications. A structured approach to hypertext development suggests the notion of authoring-in-the-large . Authoring-in-the-large allows the description of overall classes of information elements and navigational structures of complex applications without much concern with implementation details, and in a system-independent manner. The paper presents HDM (Hypertext Design Model), a first step towards defining a general purpose model for authoring-in-the-large. Some of the most innovative features of HDM are: the notion of perspective ; the identification of different categories of links (structural links, application links, and perspective links) with different representational roles; the distinction between hyperbase and access structures ; and the possibility of easily integrating the structure of a hypertext application with its browsing semantics. HDM can be used in different manners: as a modeling device or as an implementation device. As a modeling device, it supports producing high level specifications of existing or to-be-developed applications. As an implementation device, it is the basis for designing tools that directly support application development. One of the central advantages of HDM in the design and practical construction of hypertext applications is that the definition of a significant number of links can be derived automatically from a conceptual-design level description. Examples of usage of HDM are also included.

Our understanding of the effectiveness of motion-based touchless games for autistic children is limited, because of the small amount of empirical studies and the limits of our current knowledge on autism. This paper offers two contributions. First, we provide a survey and a discussion of the existing literature. Second, we describe a field study that extends the current body of empirical evidence of the potential benefits of touchless motion-based gaming for autistic children. Our research involved five autistic children and one therapist in the experimentation of a set of Kinect games at a therapeutic center for a period of two and a half months. Using standardized therapeutic tests, observations during game sessions, and video analysis of over 20 hours of children’s activities, we evaluated the learning benefits in relationship to attentional skills and explored several factors in the emotional and behavioral sphere. Our findings show improvements of the considered learning variables and help us to better understand how autistic children experience motion-based touchless play. Overall, our research sheds a light on the opportunities offered full body touchless games for therapy and education of these special users

This paper investigates the use of automatically extracted visual features of videos in the context of recommender systems and brings some novel contributions in the domain of video recommendations. We propose a new content-based recommender system that encompasses a technique to automatically analyze video contents and to extract a set of representative stylistic features (lighting, color, and motion) grounded on existing approaches of Applied Media Theory. The evaluation of the proposed recommendations, assessed w.r.t. relevance metrics (e.g., recall) and com

Limited studies exist that explore motion-based touchless applications for children with ASD (Autism Spectrum Disorder) and investigate their design issues and the benefits they can bring to this target group. The paper reports a structured set of design guidelines that distill our experience gained from empirical studies and collaborations with therapeutic centers. These heuristics informed the design of three touchless games that were evaluated in a controlled study involving medium functioning ASD children at a therapeutic center. Our findings confirm the potential of motion-based touchless applications games in technology-enhanced interventions for this target group. BACKGROUNDThe Autistic Spectrum Disorder (ASD) is a general term for a group of complex disorders of brain development, characterized, in varying degrees, by difficulties in social interaction, verbal and nonverbal communication and repetitive behaviors often accompanied by sensorimotor impairments. Autism, estimated to affect 1 of every 88 children, is marked by the presence of impairments along a triad of dimensions: social interaction, communication, and imagination. Children with autism show a great variance of symptoms, ranging from a delay or a total lack of spoken language to a severe impairment in the use of nonverbal behaviors that regulate social interaction, to a failure to develop peer relationships appropriate to age. ASD children also show imagination inability, manifested in the difficulty to generalize between environments, in a limited range of imaginative activities and in a difficulty in figuring out future events and abstract ideas. This reflects to a lack of spontaneous make-believe play or social imitative play and tendency to repetitive and stereotyped patterns of activity. Other behavioral symptoms include hyperactivity, short attention span, impulsivity, aggressiveness, self-injurious behavior, and temper tantrums. Studies conducted to consider the effectiveness of digital technologies for ASD children reveal that these tools are in general well received [16]. A digital environment provides stimuli that are more focused, predictable, and replicable than conventional tools. It also reduces the confusing, multi-sensory distractions of the real world that may induce anxiety and create barriers to social communication. In addition, digital tools can exploit the benefits of visually based interventions adopted in existing therapeutic practices such as video modeling [6]. Existing products and prototypes for autistic children exploit a variety of technologies and interaction modes, from desktop to multitouch mobile devices, tangibles and digitally augmented objects, robots [11], and more recently, touchless motion based environments, enabling users to interact using body movements without any physical contact with digital tools. The goal of our research is to design, develop and evaluate touchless motion based games that can be used for educational and therapeutic purposes in different contexts -school, therapeutic center, home...

No abstract

Recommender Systems (RSs) help users search large amounts of digital contents and services by allowing them to identify the items that are likely to be more attractive or useful. RSs play an important persuasion role, as they can potentially augment the users' trust towards in an application and orient their decisions or actions towards specific directions. This article explores the persuasiveness of RSs, presenting two vast empirical studies that address a number of research questions.First, we investigate if a design property of RSs, defined by the statistically measured quality of algorithms, is a reliable predictor of their potential for persuasion. This factor is measured in terms of perceived quality, defined by the overall satisfaction, as well as by how users judge the accuracy and novelty of recommendations. For our purposes, we designed an empirical study involving 210 subjects and implemented seven full-sized versions of a commercial RS, each one using the same interface and dataset (a subset of Netflix), but each with a different recommender algorithm. In each experimental configuration we computed the statistical quality (recall and F-measures) and collected data regarding the quality perceived by 30 users. The results show us that algorithmic attributes are less crucial than we might expect in determining the user's perception of an RS's quality, and suggest that the user's judgment and attitude towards a recommender are likely to be more affected by factors related to the user experience.Second, we explore the persuasiveness of RSs in the context of large interactive TV services. We report a study aimed at assessing whether measurable persuasion effects (e.g., changes of shopping behavior) can be achieved through the introduction of a recommender. Our data, collected for more than one year, allow us to conclude that, (1) the adoption of an RS can affect both the lift factor and the conversion rate, determining an increased volume of sales and influencing the user's decision to actually buy one of the recommended products, (2) the introduction of an RS tends to diversify purchases and orient users towards less obvious choices (the long tail), and (3) the perceived novelty of recommendations is likely to be more influential than their perceived accuracy.Overall, the results of these studies improve our understanding of the persuasion phenomena induced by RSs, and have implications that can be of interest to academic scholars, designers, and adopters of this class of systems.

No abstract

No abstract