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Bandwidth is still a limiting factor for the Quality of Service (QoS) of mobile communication applications. In particular, for Voice over IP the QoS is not yet as good as for common, well-engineered, public-switched telephone networks. Multisensory communication has been identified as a possibility to moderate this limitation. One of the strengths of mobile video technology lies in its combination of visual and auditory modalities. However, one of the most salient features of mobile video applications is its small screen size. To test the potential of multimodal synergy for mobile devices, we assessed to what extent small screens affect multimodal synergy. This potential was assessed in an experiment with 54 participants, who conducted a standardised video-listening test for three talking-heads videos with a signal-to-noise ratio of –9 dB. The videos were presented on three different screen sizes, whilst keeping the video and auditory signals equal. Compared to a ground truth based on 359 participants, intelligibility was found to be significantly higher when using a large screen than when using a small screen. This indicates that mobile video technology has the potential for a significant multimodal synergy to which screen size is a substantial constraint. To optimally benefit from their multimodal potential, we offer suggestions on how to increase the effective screen size for small screen (e.g. mobile) devices and applications through elaborating the most relevant (visual) features. We conclude that knowledge about human sensory processing can alleviate the identified constraint and maximise the potential QoS of mobile video technology.

Tangible user interfaces allow children to take advantage of their experience in the real world when interacting with digital information. In this paper we describe a model for tangible user interfaces specifically for children that focuses mainly on the user experience during interaction and on how to design interactions. This model is related to other user-centered models and has been used to design a multi-touch tabletop application for a museum. The results of a first evaluation of this museum application show that the interactions at the multi-touch table were engaging and fun, which was one of the goals of the museum application and one of the four themes of the model. Regarding a few other themes of the model results of the first observations are encouraging: the interactions seemed to be intuitive and seemed to facilitate exploration and collaboration. More systematic evaluation of the complete model by video analysis and an additional validation study is proposed.

Often, the way subject matter is included in educational games does not fully utilize or sometimes even inhibits the full learning potential of games. This paper argues that in order to optimally use the potential of games for learning, games should be endogenous. An endogenous educational game is a game where the educational content is integrated in the game play mechanics themselves, rather than bolted-on using explicit messages. This research examines the relation between explicit messages, explorative game behavior, and comprehension by developing two versions of an endogenous educational game about overfishing, one with and one without an explicit purpose. The game was tested with 13 children aged 8 to 11. The results indicate that factual knowledge and comprehension is increased with explicit messages, and in particular deep comprehension is fostered by explorative game behavior. This confirms the plea for endogenous games to teach about bombs, fish, coral reefs, and more.

How to provide users a positive experience during interaction with information (i.e., the “Information eXperience” (IX)) is still an open question. As a starting point, this work investigates how the emotion of interest can be influenced by modifying the complexity of the information presented to users. The appraisal theory of interest suggests a “sweet spot” where interest will be at its peak: information that is novel and complex yet still comprehensible. This “sweet spot” is approximated using two studies. Study One develops a computational model of textual complexity founded on psycholinguistic theory on processing difficulty. The model was trained and tested on 12,420 articles, achieving a classification performance of 90.87% on two classes of complexity. Study Two puts the model to its ultimate test: Its application to change the user’s IX. Using 18 news articles the influence of complexity on interest and its appraisals is unveiled. A structural equation model shows a positive influence of complexity on interest, yet a negative influence of comprehensibility, confirming a seemingly paradoxical relationship between complexity and interest. By showing when complexity becomes interesting, this paper shows how information systems can use the model of textual complexity to construct an interesting IX.

News feeds are an important element of information encountering, feeding our (new) interests but also leading to a state of information overload. Current solutions often select information similar to the user's interests. However, long-term interest in one topic, and being highly familiar with that topic, does not necessarily imply an actual interest response will occur when more of the same topic is selected. This study explores how important familiarity is in predicting an interest response. In a study with 30 subjects, interest was manipulated by topical familiarity using novel stimuli from a popular news source. This study shows, within this context, familiarity is moderately important for an interest response: familiarity does indeed make the news interesting, but only to a certain extent. The results set a baseline for predicting interest during information encountering, indicating familiarity is important, but not the only influential variable a system should consider when selecting information for users.

This study explores the feasibility of sensitive machines; that is, machines with empathic abilities, at least to some extent. A signal processing and machine learning pipeline is presented that is used to analyze data from two studies in which 25 Post-Traumatic Stress Disorder (PTSD) patients participated. The feasibility of speech as a stress detector was validated in a clinical setting, using the Subjective Unit of Distress (SUD). 13 statistical parameters were derived from five speech features, namely: amplitude, zero crossings, power, high-frequency power, and pitch. To achieve a low dimensional representation, a subset of 28 parameters was selected and, subsequently, compressed into 11 principal components (PC). Using a Multi-Layer Perceptron neural network (MLP), the set of 11 PC were mapped upon 9 distinct quantizations of the SUD. The MLP was able to discriminate between 2 stress levels with 82.4% accuracy and up to 10 stress levels with 36.3% accuracy. With stress baptized as being the black death of the 21st century, this work can be conceived as an important step towards computer aided mental health care.

An endogenous educational game is a game where the educational content is integrated in the game play mechanics themselves. These games rely on a constructivist approach to learning, where the learner constructs knowledge through concrete experiences. Endogenous educational games which are specifically developed for educational purposes mostly make this purpose explicit: they make it clear in advance what is about to be learned. This research tried to find out how such an explicit purpose influences the game behavior and comprehension by developing two versions of an endogenous educational game about over fishing, one with and one without an explicit purpose. It showed that children who played the explicit version got more shallow knowledge and showed more active game behavior. The players who showed more explorative game behavior acquired more deep knowledge about the game.

We approach Information Retrieval (IR) from a User eXperience (UX) perspective. Through introducing a model for Information Retrieval eXperience (IRX), this paper operationalizes a perspective on IR that reaches beyond topicality. Based on a document's topicality, complexity, and emotional value, a model of relevance is proposed to influence user's IRX and, consequently, the synthesis and use of the retrieved information. Additionally, methods are discussed to assess UX through interaction and feedback mechanisms. As such, the proposed multi-dimensional IRX model is highly user-dependent and determines document's relevance from a non-traditional human-centered, personalized perspective on IR.

Although Information Retrieval (IR) is meant to serve its users, surprisingly little IR research is not user-centered. In contrast, this article utilizes the concept complexity of information as the determinant of the user's comprehension, not as a formal golden measure. Four aspects of user's comprehension are applied on a database of simple and normal Wikipedia articles and found to distinguish between them. The results underline the feasibility of the principle of parsimony for IR: where two topical articles are available, the simpler one is preferred.

Access to information suitable and understandable for children is key to their development. Regrettably, current state-of-the-art Information Retrieval (IR) is mainly made with adults in mind, resulting in IR systems that do not suit children well: they require complicated queries and often retrieve inappropriate results in a format unsuitable for children. To conrm this, this paper presents four groups of salient problems children have with IR. To explain these problems, a comprehensive review of children's use of IR systems is given, dening relevant aspects of the user, system, interaction, and context, and relating these to the search performance of children. Based on this framework, an integrative perspective on relevance is proposed, specificially geared at children's needs. It is proposed that complexity, interestingness, and aective value are key relevance criteria for children, and should be incorporated in an information system for children, if to arrive at an optimal search result and experience.

Contains fulltext : 77245.pdf (Publisher’s version ) (Open Access) A posttraumatic stress disorder (PTSD) is a severe handicap in daily life and its treatment is complex. To evaluate the success of treatments, an objective and unobtrusive expert system was envisioned: an therapy progress indicator (TPI). Speech was considered as an excellent candidate for providing an objective, unobtrusive emotion measure. Speech of 26 PTSD patients was recorded while they participated in two reliving sessions: re-experiencing their last panic attack and their last joyful occasion. As a subjective measure, the subjective unit of distress was determined, which enabled the validation of derived speech features. A set of parameters of the speech features: signal, power, zero crossing ratio, and pitch, was found to discriminate between the two sessions. A regression model involving these parameters was able to distinguish between positive and negative distress. This model lays the foundation for an TPI for patients with PTSD, which enables objective and unobtrusive evaluations of therapies.

In this paper we present the first experimental step of a larger study investigating the effects of agents’ gender identification on the perceived interaction quality. The purpose was to determine how test subjects judge the ‘gender’ of virtual humans. 48 test subjects rated 7 agents according to their degree of feminity, masculinity and gender ambiguity. The results showed that subjects’ gender combined with the order in which the agents were presented have a strong impact on their perceived degree of feminity, masculinity and gender ambiguity. The agents identified as having strong feminine, masculine and androgynous traits will be used in the next experimental session to represent a multimodal dialogue system for medical queries.