Can Unhappy Pictures Enhance the Effect of Personas? A User Experiment

There has been little research into whether a persona's picture should portray a happy or unhappy individual. We report a user experiment with 235 participants, testing the effects of happy and unhappy image styles on user perceptions, engagement, and personality traits attributed to personas using a mixed-methods analysis. Results indicate that the participant's perceptions of the persona's realism and pain point severity increase with the use of unhappy pictures. In contrast, personas with happy pictures are perceived as more extroverted, agreeable, open, conscientious, and emotionally stable. The participants’ proposed design ideas for the personas scored more lexical empathy scores for happy personas. There were also significant perception changes along with the gender and ethnic lines regarding both empathy and perceptions of pain points. Implications are the facial expression in the persona profile can affect the perceptions of those employing the personas. Therefore, persona designers should align facial expressions with the task for which the personas will be employed. Generally, unhappy images emphasize realism and pain point severity, and happy images invoke positive perceptions.

Using Different Error Handling Strategies to Facilitate Older Users’ Interaction With Chatbots in Learning Information and Communication Technologies

To support older users’ accessibility and learning of the prevalent information and communication technologies (ICTs), libraries, as informal learning institutes, are committed to information literacy education activities with friendly interfaces. Chatbots using Voice User Interfaces (VUIs) with natural and intuitive interactions have received growing research and practical attention; however, older users report regular frustrations and problems in using them. To serve as a basis for the subsequent design and development of an automated dialog mechanism in senior-friendly chatbots, a between-subject user experiment was conducted with 30 older adults divided into three groups. The preliminary findings on their interactions with the voice chatbots designed with different error handling strategies were reported. Participants’ behavioral patterns, performances, and the tactics they employed in interacting with the three types of chatbots were analyzed. The results of the study showed that the use of multiple error handling strategies is beneficial for older users to achieve effectiveness and satisfaction in human-robot interactions, and facilitate their attitude toward information technology. This study contributes empirical evidence in the genuine and pragmatic field of gerontechnology and expands upon voice chatbots research by exploring conversation errors in human-robot interactions that could be of further application in designing educational and living gerontechnology.

The Effectiveness of Adaptation Methods in Improving User Engagement and Privacy Protection on Social Network Sites

Research finds that the users of Social Networking Sites (SNSs) often fail to comprehensively engage with the plethora of available privacy features— arguably due to their sheer number and the fact that they are often hidden from sight. As different users are likely interested in engaging with different subsets of privacy features, an SNS could improve privacy management practices by adapting its interface in a way that proactively assists, guides, or prompts users to engage with the subset of privacy features they are most likely to benefit from. Whereas recent work presents algorithmic implementations of such privacy adaptation methods, this study investigates the optimal user interface mechanism to present such adaptations. In particular, we tested three proposed “adaptation methods” (automation, suggestions, highlights) in an online between-subjects user experiment in which 406 participants used a carefully controlled SNS prototype. We systematically evaluate the effect of these adaptation methods on participants’ engagement with the privacy features, their tendency to set stricter settings (protection), and their subjective evaluation of the assigned adaptation method. We find that the automation of privacy features afforded users the most privacy protection, while giving privacy suggestions caused the highest level of engagement with the features and the highest subjective ratings (as long as awkward suggestions are avoided). We discuss the practical implications of these findings in the effectiveness of adaptations improving user awareness of, and engagement with, privacy features on social media.

Graceful Language Extensions and Interfaces

<p>Grace is a programming language under development aimed at education. Grace is object-oriented, imperative, and block-structured, and intended for use in first- and second-year object-oriented programming courses. We present a number of language features we have designed for Grace and implemented in our self-hosted compiler. We describe the design of a pattern-matching system with object-oriented structure and minimal extension to the language. We give a design for an object-based module system, which we use to build dialects, a means of extending and restricting the language available to the programmer, and of implementing domain-specific languages. We show a visual programming interface that melds visual editing (à la Scratch) with textual editing, and that uses our dialect system, and we give the results of a user experiment we performed to evaluate the usability of our interface.</p>

Graceful Language Extensions and Interfaces

<p>Grace is a programming language under development aimed at education. Grace is object-oriented, imperative, and block-structured, and intended for use in first- and second-year object-oriented programming courses. We present a number of language features we have designed for Grace and implemented in our self-hosted compiler. We describe the design of a pattern-matching system with object-oriented structure and minimal extension to the language. We give a design for an object-based module system, which we use to build dialects, a means of extending and restricting the language available to the programmer, and of implementing domain-specific languages. We show a visual programming interface that melds visual editing (à la Scratch) with textual editing, and that uses our dialect system, and we give the results of a user experiment we performed to evaluate the usability of our interface.</p>

Characterizing and predicting the cross-app behavior in mobile search

PurposeThis paper aims to explore the users' cross-app behavior characteristics in mobile search and to predict users' cross-app behavior using multi-dimensional information.Design/methodology/approachThis paper presents a longitudinal user experiment in 15 days. This paper recruited 30 participants and collected their mobile phone log data in the whole experiment. The structured diary method was also used to collect contextual information in mobile search.FindingsThis study focused on the users' cross-app behavior in mobile search and described cross-app behavior's basic characteristics. Usage of communication app and tool apps could trigger more cross-app behavior in mobile search. The method of cross-app behavior prediction in the mobile search was proposed. Collecting users' more contextual information, such as search tasks, search motivation and other environmental information, can effectively improve the prediction accuracy of cross-app behavior in mobile search.Practical implicationsThe future research on cross-app behavior prediction should focus on context information in mobile search. Better prediction of cross-app behavior can reduce the users' interaction burden.Originality/valueThis paper contributes to research into cross-app behavior, especially in the mobile search research domain.

Dynamic graph exploration by interactively linked node-link diagrams and matrix visualizations

The visualization of dynamic graphs is a challenging task owing to the various properties of the underlying relational data and the additional time-varying property. For sparse and small graphs, the most efficient approach to such visualization is node-link diagrams, whereas for dense graphs with attached data, adjacency matrices might be the better choice. Because graphs can contain both properties, being globally sparse and locally dense, a combination of several visual metaphors as well as static and dynamic visualizations is beneficial. In this paper, a visually and algorithmically scalable approach that provides views and perspectives on graphs as interactively linked node-link and adjacency matrix visualizations is described. As the novelty of this technique, insights such as clusters or anomalies from one or several combined views can be used to influence the layout or reordering of the other views. Moreover, the importance of nodes and node groups can be detected, computed, and visualized by considering several layout and reordering properties in combination as well as different edge properties for the same set of nodes. As an additional feature set, an automatic identification of groups, clusters, and outliers is provided over time, and based on the visual outcome of the node-link and matrix visualizations, the repertoire of the supported layout and matrix reordering techniques is extended, and more interaction techniques are provided when considering the dynamics of the graph data. Finally, a small user experiment was conducted to investigate the usability of the proposed approach. The usefulness of the proposed tool is illustrated by applying it to a graph dataset, such as e co-authorships, co-citations, and a Comprehensible Perl Archive Network distribution.

Augmented reality flavor: cross-modal mapping across gustation, olfaction, and vision

Gustatory display research is still in its infancy despite being one of the essential everyday senses that human practice while eating and drinking. Indeed, the most important and frequent tasks that our brain deals with every day are foraging and feeding. The recent studies by psychologists and cognitive neuroscientist revealed how complex multisensory rely on the integration of cues from all the human senses in any flavor experiences. The perception of flavor is multisensory and involves combinations of gustatory and olfactory stimuli. The cross-modal mapping between these modalities needs to be more explored in the virtual environment and simulation, especially in liquid food. In this paper, we present a customized wearable Augmented Reality (AR) system and olfaction display to study the effect of vision and olfaction on the gustatory sense. A user experiment and extensive analysis conducted to study the influence of each stimulus on the overall flavor, including other factors like age, previous experience in Virtual Reality (VR)/AR, and beverage consumption. The result showed that smell contributes strongly to the flavor with less contribution to the vision. However, the combination of these stimuli can deliver richer experience and a higher belief rate. Beverage consumption had a significant effect on the flavor belief rate. Experience is correlated with stimulus and age is correlated with belief rate, and both indirectly affected the belief rate.

Development of a model of subjective feelings for the front visual quality during automobile driving

The main goal of this study is to develop a model of subjective feelings for frontal visibility, often called the feeling of ‘openness’, for automobile drivers. Moreover, this study proposed a method to overcome the limitations of the rating scale method, although it has been used in a great number of studies. To this end, eight potential design variables of automobiles were extracted from 25 candidate design variables. A questionnaire for evaluating the openness of an automobile was developed based on these variables. By using this questionnaire, a user experiment was conducted to investigate a relationship between the feeling of openness of automobiles and the design variables. Twenty-six participants evaluated the feeling of openness and the perceived rate of the design variables for 30 automobiles. The results showed that the variables such as the height of headlining, the height of cluster housing, the inclination angle of wind shield, and the volume of A-pillar were the critical design variables affecting the feeling of openness of the automobiles. Moreover, the optimal perceived level of each design variable was found out. The results of this study can be applied to designing automobile interior for good frontal visibility.

INTERACTIVE VIDEOS AS GEOSPATIAL INTERFACES: A CASE STUDY FOR REGIONAL PROMOTION

In this paper we discuss the potential of interactive video as an interface to geospatial information, and demonstrate our findings in a case study driven by goals of promoting a region for tourism and for preventing brain drain. Use of video is controversial due to various technical and human-centric debates; on the one hand, they offer unique qualitative insights as they enable a certain level of immersion via walk-throughs and fly-throughs and they are considered attractive by viewers, on the other hand, they are complex because they contain unfiltered (possibly too much) information that may be irrelevant to the goals of the users, and require careful consideration from computational and bandwidth concerns. We examine these arguments from the literature briefly, and demonstrate our case study in which we have embedded and overlain statistical and other local information interactively over drone footage, and measured levels of usability and user engagement using standardized scales. Our implementation and design choices are detailed in the article. Our small user experiment (n = 6) suggests high levels of usability, desirability and engagement by our participants, leading to the hypothesis that video is an attractive medium and indeed has strong potential for regional promotion, given that the computational and cognitive issues are taken into account.