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Engagement is the Key: A New Journey for ADHD Treatment
Abstract
Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders diagnosed in children, for which Cognitive Behavioral Therapy (CBT) represents the main standard treatment used worldwide, despite its pedantic approach negatively affects both patients’ engagement and improvement. In this work we aim to renovate ADHD treatment with a new approach for cognitive, behavioral, and emotional patient rehabilitation. Iamhero is a first prototype of hi-tech multisensorial therapeutic environment, that bases its strength on patients physical and emotional engagement, leading therefore to cognitive and behavioral skills improvement. The first results show encouraging improvement in learning skills in patients that have steadily used the system for six months. In this paper we explain Iamhero main features, and the first experimental results obtained.
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In the e-Health domain, new and continuously evolving threats emerge every day. The security of e-Health telemonitoring systems is no longer negligible. In this paper, we propose a Cyberattack Detection System (CADS) model that exploits artificial intelligence techniques to detect anomalies without requiring a security analyst, explain the malicious activity, and display suspected attack data to healthcare personnel for feedback. The system description is contextualized to the case of the hacked remote patient health telemonitoring.
This work revisits security threats on smart electrical grids and focuses on the dimensions of dependability, serviceability, and accountability, which constitute the security requirements of an SG application. The first two dimensions deal with fault diagnosis and location, while the last element tackles building the system more transparent. We proposed a data-driven machine-learned fault prediction system that can provide abrupt and accurate fault type classification and location prediction. Furthermore, we reported a feature interaction visualization and elaborated on how this step can facilitate interpretation of the results and assessment of the security threats in the SG. The evaluation of the system is carried out on a large-scale dataset comprised of approximately 1.9K training samples. Results show the effectiveness of the proposed system both in prediction and interpretability steps.
Spatial reasoning has been shown to be an important, trainable cognitive skillset for developing successful engagement in science, technology, engineering and mathematics (STEM), but little empirical work has been conducted in the context of digitally mediated pedagogies. This paper reports on a study into the effectiveness of a technologically enhanced STEM program on the spatial reasoning of a cohort of year 7 students (n = 107). The students undertook five digitally based activities over the period of a week and were assessed on their spatial reasoning development and attitudes towards STEM prior and subsequent to the intervention. Results indicate that the week of learning activities had an impact on attitudes towards STEM and had a positive impact on overall spatial skills. However, no statistically significant improvements were found within the spatial sub-skills or in relation to specific activities.
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A number of algorithms in the field of artificial intelligence offer poorly interpretable decisions. To disclose the reasoning behind such algorithms, their output can be explained by means of so-called evidence-based (or factual) explanations. Alternatively, contrastive and counterfactual explanations justify why the output of the algorithms is not any different and how it could be changed, respectively. It is of crucial importance to bridge the gap between theoretical approaches to contrastive and counterfactual explanation and the corresponding computational frameworks. In this work we conduct a systematic literature review which provides readers with a thorough and reproducible analysis of the interdisciplinary research field under study. We first examine theoretical foundations of contrastive and counterfactual accounts of explanation. Then, we report the state-of-the-art computational frameworks for contrastive and counterfactual explanation generation. In addition, we analyze how grounded such frameworks are on the insights from the inspected theoretical approaches. As a result, we highlight a variety of properties of the approaches under study and reveal a number of shortcomings thereof. Moreover, we define a taxonomy regarding both theoretical and practical approaches to contrastive and counterfactual explanation.
Enrollment in courses taught remotely in higher education has been on the rise, with a recent surge in response to a global pandemic. While adapting this form of teaching, instructors familiar with traditional face-to-face methods are now met with a new set of challenges, including students not turning on their cameras during synchronous class meetings held via videoconferencing. After transitioning to emergency remote instruction in response to the COVID-19 pandemic, our introductory biology course shifted all in-person laboratory sections into synchronous class meetings held via the Zoom videoconferencing program. Out of consideration for students, we established a policy that video camera use during class was optional, but encouraged. However, by the end of the semester, several of our instructors and students reported lower than desired camera use that diminished the educational experience. We surveyed students to better understand why they did not turn on their cameras. We confirmed several predicted reasons including the most frequently reported: being concerned about personal appearance. Other reasons included being concerned about other people and the physical location being seen in the background and having a weak internet connection, all of which our exploratory analyses suggest may disproportionately influence underrepresented minorities. Additionally, some students revealed to us that social norms also play a role in camera use. This information was used to develop strategies to encourage –without requiring– camera use while promoting equity and inclusion. Broadly, these strategies are to not require camera use, explicitly encourage usage while establishing norms, address potential distractions, engage students with active learning, and understand your students’ challenges through surveys. While the demographics and needs of students vary by course and institution, our recommendations will likely be directly helpful to many instructors and also serve as a model for gathering data to develop strategies more tailored for other student populations.
Background: A vast amount of mobile apps have been developed during the past few months in an attempt to “flatten the curve” of the increasing number of COVID-19 cases.
Objective: This systematic review aims to shed light into studies found in the scientific literature that have used and evaluated mobile apps for the prevention, management, treatment, or follow-up of COVID-19.
Methods: We searched the bibliographic databases Global Literature on Coronavirus Disease, PubMed, and Scopus to identify papers focusing on mobile apps for COVID-19 that show evidence of their real-life use and have been developed involving clinical professionals in their design or validation.
Results: Mobile apps have been implemented for training, information sharing, risk assessment, self-management of symptoms, contact tracing, home monitoring, and decision making, rapidly offering effective and usable tools for managing the COVID-19 pandemic.
Conclusions: Mobile apps are considered to be a valuable tool for citizens, health professionals, and decision makers in facing critical challenges imposed by the pandemic, such as reducing the burden on hospitals, providing access to credible information, tracking the symptoms and mental health of individuals, and discovering new predictors
Italy has adopted the strategy of inner areas, mainly based on physical distance from public services. The strategy promotes a multi-level and multi-fund governance approach and the local partnership of mayors. Our paper focuses on rural areas, identified by the national strategy of inner areas, as peripheral and ultra-peripheral, in the Italian insular region (Sicily and Sardinia). It analyzes, at the municipality level, socio-demographic, economic, and environmental sustainability using appropriate indicators. Aiming at discovering the underlying relationship portrayed by multi-attribute data in an information system, we applied rough set theory. The inductive decision rules obtained through this data mining methodology reveal the simultaneous presence or absence of important characteristics aiming at reaching different levels of sustainability. Without the requirement of statistical assumptions regarding data distribution or structures for collecting data, such as functions or equations, this method ensures the description of patterns exhibited by data. Of particular interest is the assessment of conditional attributes (i.e., the selected indicators), and the information connecting them to sustainability, as a decision attribute. The most important result is rule generation, specifically, decision rules that are able to suggest tools for policy makers at different levels.
As robots become increasingly common in a wide variety of domains , there is an increasing need to assess the trust humans have when interacting with robots. Specifically are two of the main objectives in this study: 1) to adapt and validate the Human-Computer Trust Model Scale (HCTM) to human-robot interaction (HRI), in a Portuguese population. This need is because trust in automation has been understood through its analogy to interpersonal trust. With the HCTM we intend to suggest an alternative to that. This measure of trust is a very recent scale, 2019, and based on the present context and research. More, this scale was subjected to robust statistical analysis tests and was tested at different scenarios of computing with successful. The final motive is that authors are not aware of a similar scale in the Portuguese context that can measure trust in HRI with COBOTS. The growth of this market is notable. For that, we used 243 undergraduate students with backgrounds on Management and Engineering and Industrial Management. Results, indicate a good measurement of the latent constructs, convergent reliability, internal consistency and discriminate validity. However, Dillon-Goldstein's rho measures for both Competency (0.696), Benevolence (0.686) and Reciprocity (0.604) constructs present scores close to 0.70. According to Hair et al [11] the composite reliability (inter-nal consistency) should be higher than 0.7 (or >0.6 in exploratory research). This means that the model is acceptable, and the Por-tuguese version of the model satisfies the criteria for measure trust in human-robot interaction (HRI), however, have a poor internal consist. CCS CONCEPTS • Human-centered computing → HCI theory, concepts and models.
Running is a popular recreational sport, yet for many amateur runners it remains challenging to turn intentions into sustainable running behavior. Although the market offers a myriad of running-related devices that aim to motivate runners, these often focus on the training itself and not on overcoming the barriers experienced prior to the run. A better understanding of these barriers to running is essential to identify design opportunities for technologies supporting amateur runners. We conducted two complementary studies among participants of a women-only running event. Combining an online survey (N = 114) and a journey mapping activity (N = 13), we investigated the influence of motivational barriers and enablers in runners' rituals. Based on our findings, we created the Runner's Journey, a visual narrative highlighting actionable design opportunities for running motivation technology. We propose five design recommendations to overcome barriers among amateur runners.
This paper describes a novel category of affective vibrotactile stimuli which evoke real-world sensations and details a study into emotional responses to them. The affective properties of short and abstract vibrotactile waveforms have previously been studied and shown to have a narrow emotional range. By contrast this paper investigated emotional responses to longer waveforms and to emotionally resonant vibrotactile stimuli, stimuli which are evocative of real-world sensations such as animal purring or running water. Two studies were conducted. The first recorded emotional responses to Tactons with a duration of 20 seconds. The second investigated emotional responses to novel emotionally resonant stimuli. Stimuli that users found more emotionally resonant were more pleasant, particularly if they had prior emotional connections to the sensation represented. Results suggest that future designers could use emotional resonance to expand the affective response range of vibrotactile cues by utilising stimuli with which users bear an emotional association.
Humor, as it is experienced in the physical world, is based on incongruities. This is well-known for jokes and it is a well-researched approach to joke analysis. Less well-known is the incongruity approach to humor for physical environments and human activities, although this approach has a history that is longer than that of joke analysis. We can, as mentioned above, have situations, activities, and human interactions in urban environments that are considered humorous or potentially humorous, for human observers. Elements of incongruity and incongruity humor are unexpected events, inappropriate situations, unusual activity, strange behavior, and interactions, and these events, situations, activity, behavior, and interactions can be compared to what is considered ordinary and often when they are sufficiently opposed in these comparisons, humor emerges. Augmented Reality allows us to introduce these potentially humorous situations. Augmented Reality allows us to integrate artificially generated virtual content with the real world that that is in contrast with what is already present. In this way, we can confront the user with artificially generated humorous situations. We can also deceive the user or let her have – not necessarily humorous – illusory experiences. This paper is devoted to playful and humorous experiences that can be realized with augmented reality and some examples of existing playful augmented reality applications will be presented.
The COVID-19 pandemic in spring 2020 caused the rapid introduction of remote schooling in many countries. This transition caused a variety of challenges to families, encompassing organizing home workspaces, setting up computing equipment, and, for many parents, managing their own remote working in parallel with the schooling arrangements. This paper describes the findings from an online survey (n = 114) and an in-depth interview study (n = 14) conducted in Finland during the COVID-19 remote schooling phase. Focusing on issues surrounding technology usage in the family setting, we report on the array of applications parents and children were required to manage, strategies to share ICT equipment within families, spatial organizational issues and the high levels of flexibility needed from parents and other stakeholders to enable the remote schooling.
The United Kingdom's National Health Service (NHS) has a higher-than-average level of stress-related sickness absence of all job sectors in the country. It is important that this is addressed as work stress is damaging to employees and the organisation, and subsequently impacts patient care. The aim of this study was to gain an in-depth understanding of working conditions and wellbeing in NHS employees from three employing NHS Trusts through a mixed-methods investigation. First, a cross-sectional organisational survey was completed by 1644 respondents. Questions examined working conditions, stress, psychological wellbeing, job satisfaction, and presenteeism. This was followed by 33 individual semistructured interviews with NHS staff from a variety of clinical and nonclinical roles. Quantitative findings revealed that working conditions were generally positive, although most staff groups had high levels of workload. Regression outcomes demonstrated that a number of working conditions influenced mental wellbeing and stress. Three themes were generated from thematic analysis of the interview data: wellbeing at work, relationships, and communication. These highlight areas which may be contributing to workplace stress. Suggestions are made for practical changes which could improve areas of difficulty. Such changes could improve staff wellbeing and job satisfaction and reduce sickness absence.
We present CoVR, a novel robotic interface providing strong kinesthetic feedback (100 N) in a room-scale VR arena. It consists of a physical column mounted on a 2D Cartesian ceiling robot (XY displacements) with the capacity of (1) resisting to body-scaled users’ actions such as pushing or leaning; (2) acting on the users by pulling or transporting them as well as (3) carrying multiple potentially heavy objects (up to 80kg) that users can freely manipulate or make interact with each other. We describe its implementation and define a trajectory generation algorithm based on a novel user intention model to support non-deterministic scenarios, where the users are free to interact with any virtual object of interest with no regards to the scenarios’ progress. A technical evaluation and a user study demonstrate the feasibility and usability of CoVR, as well as the relevance of whole-body interactions involving strong forces, such as being pulled through or transported.
Interaction between hands and the environment permits the interchange of microorganisms. The Mexico City subway is used daily by millions of passengers that get in contact with its surfaces. In this study, we used 16S rRNA gene sequencing to characterize the microbiomes of frequently touched surfaces and compare regular and women-only wagons. We also explored the effect of surface cleaning on microbial resettling. Finally, we studied passenger behavior and characterized microbial changes after traveling. Most passengers (99%), showed some type of surface interaction during a wagon trip, mostly with the hands (92%). We found microbiome differences associated with surfaces, probably reflecting diverse surface materials and usage frequency. The platform floor was the most bacterial diverse surface, while the stair handrail and pole were the least diverse ones. After pole cleaning, the resettling of microbial diversity was fast (5–30 minutes); however, it did not resemble the initial composition. After traveling, passengers significantly increased their hand microbial diversity and converged to a similar microbial composition among passengers. Additionally, passenger hand microbiomes resembled subway surfaces in diversity. However, microbial fingerprints were preserved within passengers after traveling.
Background
Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care.
Objective
This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application.
Methods
We performed a scoping review. A broad literature search was performed in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central with the search terms “conversational agents,” “conversational AI,” “chatbots,” and associated synonyms. We also searched the gray literature using sources such as the OCLC (Online Computer Library Center) WorldCat database and ResearchGate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by 2 reviewers. The included evidence was analyzed narratively by employing the principles of thematic analysis.
Results
The literature search yielded 47 study reports (45 articles and 2 ongoing clinical trials) that matched the inclusion criteria. The identified conversational agents were largely delivered via smartphone apps (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case studies describing chatbot development (n=18) were the most prevalent, and only 11 randomized controlled trials were identified. The 3 most commonly reported conversational agent applications in the literature were treatment and monitoring, health care service support, and patient education.
Conclusions
The literature on conversational agents in health care is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, artificial intelligence–driven, and smartphone app–delivered conversational agents. There is an urgent need for a robust evaluation of diverse health care conversational agents’ formats, focusing on their acceptability, safety, and effectiveness.
There is a growing body of research in the field of interaction between automated vehicles and other road users in their vicinity. To facilitate such interactions, researchers and designers have explored designs, and this line of work has yielded several concepts of external Human-Machine Interfaces (eHMI) for vehicles. Literature and media review reveals that the description of interfaces is often lacking in fidelity or details of their functionalities in specific situations, which makes it challenging to understand the originating concepts. There is also a lack of a universal understanding of the various dimensions of a communication interface, which has impeded a consistent and coherent addressal of the different aspects of the functionalities of such interface concepts. In this paper, we present a unified taxonomy that allows a systematic comparison of the eHMI across 18 dimensions, covering their physical characteristics and communication aspects from the perspective of human factors and human-machine interaction. We analyzed and coded 70 eHMI concepts according to this taxonomy to portray the state of the art and highlight the relative maturity of different contributions. The results point to a number of unexplored research areas that could inspire future work. Additionally, we believe that our proposed taxonomy can serve as a checklist for user interface designers and researchers when developing their interfaces.
Background:
People living with chronic illnesses are an increasingly large group. Research indicates that care and self-management should not only focus on the illness and problem-oriented aspects of these individuals' lives but also support them in recognizing and leveraging their personal strengths in daily life.
Objective:
This paper presents the design and developmental process of MyStrengths, a mobile health (mHealth) app designed to help its users (people with chronic conditions) both find and make use of their personal strengths in their daily lives. Through 4 consecutive phases, this paper presents participant- and researcher-driven activities, discussions regarding design, and development of both the MyStrengths app and its content.
Methods:
During the 4 phases, we used a range of methods and activities, including (1) an idea-generating workshop aimed at creating ideas for strengths-supporting features with different stakeholders, including patients, caregivers, relatives, and designers (N=35); (2) research seminars with an international group of experts (N=6), in which the concept, theoretical background, and design ideas for the app were discussed; (3) a series of co-design workshops with people in the user group (N=22) aiming to create ideas for how to, in an engaging manner, design the app; and (4) in 4 developmental iterations, the app was evaluated by people in the user group (N=13). Content and strengths exercises were worked on and honed by the research team, the expert groups, and our internal editorial team during the entire developmental process.
Results:
The first phase found a wide range of stakeholder requirements to, and ideas for, strengths-focused mHealth apps. From reviewing literature during the second phase, we found a dearth of research on personal strengths with respect to people living with chronic illnesses. Activities during the third phase creatively provided numerous ideas and suggestions for engaging and gameful ways to develop and design the MyStrengths app. The final phase saw the output from all the earlier phases come together. Through multiple increasingly complete iterations of user evaluations testing and developing, the final prototype of the MyStrengths app was created.
Conclusions:
Although research supports the use of strengths-focused mHealth tools to support people living with chronic illnesses, there is little guidance as to how these tools and their content should be designed. Through all activities, we found great support among participating users for strengths-focused apps, and we can consider such apps to be both appropriate and valuable. This paper illustrates how combining a range of user-, researcher-, literature-, and designer-based methods can contribute to creating mHealth tools to support people with chronic illnesses to find and use more of their own personal strengths.
We investigate opportunities and challenges of running virtual reality (VR) studies remotely. Today, many consumers own head-mounted displays (HMDs), allowing them to participate in scientific studies from their homes using their own equipment. Researchers can benefit from this approach by being able to recruit study populations normally out of their reach, and to conduct research at times when it is difficult to get people into the lab (cf. the COVID pandemic). In an initial online survey ( N = 227), we assessed HMD owners’ demographics, their VR setups and their attitudes toward remote participation. We then identified different approaches to running remote studies and conducted two case studies for an in-depth understanding. We synthesize our findings into a framework for remote VR studies, discuss strengths and weaknesses of the different approaches, and derive best practices. Our work is valuable for Human-Computer Interaction (HCI) researchers conducting VR studies outside labs.
Design fiction (DF) is gaining ground as an approach that helps designers to explore possible futures. As a method founded upon critical attitudes and creative thinking, DF may be challenging for design students. In this study, we explore how design students use DF during creative design activities. Students engaged in an individual digital brainstorm and an in-depth, semi-structured interview about their experiences with the brainstorm based on DF. The results show that DF can be challenging for students who do not have a clear appreciation of what is technologically feasible for a particular time frame in the future and do not yet have the breadth of knowledge to argue about broader topics that DF is particularly attuned to into the discussion as, for example, economics and societal norms. This study contributes insights into how DF impacts the students’ design thinking, as well as difficulties they had regarding their individual thinking process.
Purpose
The paper aims to propose a knowledge visualization approach and algorithm to support public decision makers to define the inner areas, which represents a strategic topic in the European debate about territorial inequality and development.
Design/methodology/approach
The study has been developed by following the design science research, which includes six steps: problem identification and motivation; identification of the objectives for a solution; design and development; demonstration; evaluation; and communication. As for the design and development step, the proposed approach and algorithm ground on association mining to discover hidden relationships existing among municipalities. They have been applied to analyse the 97 municipalities of the Lecce province, and each municipality has been described through 30 multi-domain indicators organized into seven categories, whose data have been collected from institutional datasets, local sources or web-scraping process.
Findings
A set of complementary analyses has been generated through the construction of dynamic and interactive knowledge maps that show “similar” municipalities according to the indicators selected.
Originality/value
The approach and algorithm proposed allow discovering similarities existing among distinct municipalities, based on the analysis of a set of multi-domain indicators. The approach may complement or completely substitute the existing ones used to define inner areas, thus overcoming both the methodological limits of the “top-down” line imposed by the central legislator, and the “bottom-up” paradox consisting in the illusion that single (and often small) towns have the economic and cognitive resources necessary to implement effective territorial mapping and development strategies. In such a way, policy makers can be aware on similarities existing among distinct towns and can thus share cognitive and financial resources to define a common plan and a set of practices for territorial development.
Anomaly detection is crucial to ensure the security of cyber-physical systems (CPS). However, due to the increasing complexity of CPSs and more sophisticated attacks, conventional anomaly detection methods, which face the growing volume of data and need domain-specific knowledge, cannot be directly applied to address these challenges. To this end, deep learning-based anomaly detection (DLAD) methods have been proposed. In this article, we review state-of-the-art DLAD methods in CPSs. We propose a taxonomy in terms of the type of anomalies, strategies, implementation, and evaluation metrics to understand the essential properties of current methods. Further, we utilize this taxonomy to identify and highlight new characteristics and designs in each CPS domain. Also, we discuss the limitations and open problems of these methods. Moreover, to give users insights into choosing proper DLAD methods in practice, we experimentally explore the characteristics of typical neural models, the workflow of DLAD methods, and the running performance of DL models. Finally, we discuss the deficiencies of DL approaches, our findings, and possible directions to improve DLAD methods and motivate future research.
The transmission risk of airborne diseases in public transportation systems is a concern. This paper proposes a modified Wells-Riley model for risk analysis in public transportation systems to capture the passenger flow characteristics, including spatial and temporal patterns, in the number of boarding and alighting passengers, and in number of infectors. The model is used to assess overall risk as a function of origin–destination flows, actual operations, and factors such as mask-wearing and ventilation. The model is integrated with a microscopic simulation model of subway operations (SimMETRO). Using actual data from a subway system, a case study explores the impact of different factors on transmission risk, including mask-wearing, ventilation rates, infectiousness levels of disease, and carrier rates. In general, mask-wearing and ventilation are effective under various demand levels, infectiousness levels, and carrier rates. Mask-wearing is more effective in mitigating risks. Impacts from operations and service frequency are also evaluated, emphasizing the importance of maintaining reliable, frequent operations in lowering transmission risks. Risk spatial patterns are also explored, highlighting locations of higher risk.
This article maps political rhetoric by national leaders during the COVID‐19 pandemic. We identify and characterize global variations in major rhetorical storylines invoked in publicly available speeches ( N = 1201) across a sample of 26 countries. Employing a text analytics or corpus linguistics approach, we show that state heads rhetorically lead their nations by: enforcing systemic interventions, upholding global unity, encouraging communal cooperation, stoking national fervor, and assuring responsive governance. Principal component analysis further shows that country‐level rhetoric is organized along emergent dimensions of cultural cognition: an agency‐structure axis to define the loci of pandemic interventions and a hierarchy‐egalitarianism axis which distinguishes top‐down enforcement from bottom‐up calls for cooperation. Furthermore, we detect a striking contrast between countries featuring populist versus cosmopolitan rhetoric, which diverged in terms of their collective meaning making around leading over versus leading with, as well as their experienced pandemic severity. We conclude with implications for understanding global pandemic leadership in an unequal world and the contributions of mixed‐methods approaches to a generative political psychology in times of crisis.
Highlights
During a global pandemic, political leaders must adapt their rhetoric to local societal conditions. Our work affirms the importance of political governance that elevates strong institutions while empowering public cooperation, but cautions that these may be most readily enacted in more democratic and economically developed contexts. In poorer, less democratic settings, rhetoric emphasizing accountable governance should be responsive to bottom‐up grassroots efforts in local communities, in contrast to the tightening grip of top‐down militarized policing in states witnessing the opportunistic creep of authoritarianism during a period of societal disorder. Finally, rhetoric where leaders uphold global ideals underscore wider identities of international collaborations in a global crisis, in contrast to more insularizing nationalistic rhetoric.
Our future urban environments are smart. Sensors and actuators are embedded in these environments and their inhabitants. We have an Internet of Things, where the 'Things' include objects, cars, tools, buildings, street furniture, and whatever can be equipped with sensors and actuators, including human and non-human animals. Augmented humans and augmented animals have their senses extended with digital technology. Their smart wearables connected with the smart environment make humans and animals smarter. Rather than on living animals, in this survey paper we focus on non-living virtual and augmented reality non-human animals that will inhabit our smart and playable urban environments. They will co-exist with robotic animals and (digitally augmented) humans and non-human animals. We include observations on augmented humans interacting with virtual and augmented reality animals. The paper is meant to raise awareness for the possibilities of augmented reality to introduce virtual animals for social, entertainment, and educational reasons.
Games are used in various learning situations and domains, among which is cultural heritage. Storytelling is used in games regarding cultural places, but it often takes a simple form. Thus, the authors’ aim is to investigate the possibility to communicate cultural content through a narrative-based game that can function with multiple narratives. Another core element of our design is the less exploited in serious games combination of endogenous cooperation and competition. The social dimension of our design was expressed through features of Classroom Multiplayer Presential Games (CMPGs), in respect of using a one-to-many game environment projected on a single screen, while enhancing collaborative work in small teams. After providing an overview of the game, we briefly explain how this was implemented with the use of Twine, a free authoring tool for the creation of interactive stories and text-based games. Subsequently, we present the two interventions we conducted, one with teenage students (n = 19) and one with post-graduate students (n = 14), to test how our game design functions with real users. A mixed research methodology was followed in the two trials and data were collected through observation, focus group discussions, short questionnaires, and game reports. Findings indicated that the suggested design is playable but provided helpful insights into its future improvements. The game managed to engage both teenagers and adults with the cultural content and create motivation towards it. Learning gains were registered for both groups, but these were more appreciated by the adult participants, who additionally found the game to be more entertaining. The limited character of our results imposes the need for future extensive evaluation of the game design in both formal and non-formal educational contexts.
In this paper we present a multi-criteria classification of Vocational and Educational Programs in Extremadura (Spain) during the period 2009–2016. This ranking has been carried out through the integration into a complete database of the detailed information of individuals finishing such studies together with their labor data. The multicriteria method used is TOPSIS together with a new decision support method for assessing the influence of each criterion and its dependence on the weights assigned to them. This new method is based on a worst-best case scenario analysis and it is compared to a well known global sensitivity analysis technique based on the Pearson's correlation ratio.
We present ENGAGE, the first battery-free, personal mobile gaming device powered by energy harvested from the gamer actions and sunlight. Our design implements a power failure resilient Nintendo Game Boy emulator that can run off-the-shelf classic Game Boy games like Tetris or Super Mario Land. This emulator is capable of intermittent operation by tracking memory usage, avoiding the need for always checkpointing all volatile memory, and decouples the game loop from user interface mechanics allowing for restoration after power failure. We build custom hardware that harvests energy from gamer button presses and sunlight, and leverages a mixed volatility memory architecture for efficient intermittent emulation of game binaries. Beyond a fun toy, our design represents the first battery-free system design for continuous user attention despite frequent power failures caused by intermittent energy harvesting. We tackle key challenges in intermittent computing for interaction including seamless displays and dynamic incentive-based gameplay for energy harvesting. This work provides a reference implementation and framework for a future of battery-free mobile gaming in a more sustainable Internet of Things.
A second-year engineering course at the authors’ institution was offered via a blended synchronous learning (BSL) method of delivery whereby students could choose to attend lectures live (face-to-face) or remotely (via a synchronous, live stream over the internet) during a summer semester. Survey and grade data were collected across two years of this offering. Attendance, interaction, communication with the instructor, and general distractions were main themes affecting the student learning experience both positively and negatively. Specifically, students found the remote access, the ability to ask questions, the teaching style, and having more time during the summer semester as positive aspects to their learning experience. Negative influences on their learning experience related primarily to their busy work schedules, technological issues associated with BSL, and typical summer distractions. Critically, our results indicate that attendance is a key indicator of student grades (after correcting for GPA), regardless of whether students attended lectures remotely or face-to-face: students attending more than 75% of the lectures performed on average 12% better than students who did not (p=0.0093). The consensus in the student comments was that the remote attendance option allowed students to attend in situations where the alternative was no attendance at all, implying that the potential gain in grades due to higher attendance may outweigh any potential impact the mode of attendance may have. Overall, a synchronous, remote attendance option may provide a lifeline to students who would not otherwise be able to attend a course, and (assuming a mode of interaction, such as the synchronous chat, is available) students do not perceive remote attendance as having a negative influence on their learning.
Ethnographic Experiential Futures (EXF) is an approach to foresight that aims to increase the accessibility, variety and depth of images of the future for design. In this paper, we present a EXF-based case study imagining the future supermarket. Rooted in already-existing images of future supermarkets, we propose that the future super- market experience is autonomous, efficient, informed, local and personal. Based on the idea of four "generic futures" we illustrate each of these categories with a set of scenarios in a variety of ex- periential forms. These were exhibited first in an open exhibition and second in a closed exhibition for experts. To close, we offer reflections on the use of Ethnographic Experiential Futures in the form of a set of questions to inspire future research.
We propose a new approach—called PK-clustering—to help social scientists create meaningful clusters in social networks. Many clustering algorithms exist but most social scientists find them difficult to understand, and tools do not provide any guidance to choose algorithms, or to evaluate results taking into account the prior knowledge of the scientists. Our work introduces a new clustering approach and a visual analytics user interface that address this issue. It is based on a process that 1) captures the prior knowledge of the scientists as a set of incomplete clusters, 2) runs multiple clustering algorithms (similarly to clustering ensemble methods), 3) visualizes the results of all the algorithms ranked and summarized by how well each algorithm matches the prior knowledge, 4) evaluates the consensus between user-selected algorithms and 5) allows users to review details and iteratively update the acquired knowledge. We describe our approach using an initial functional prototype, then provide two examples of use and early feedback from social scientists. We believe our clustering approach offers a novel constructive method to iteratively build knowledge while avoiding being overly influenced by the results of often randomly selected black-box clustering algorithms.
People relate to other people, not to simplified types or segments. This is the concept that underpins this book. Personas, a user centered design methodology, covers topics from interaction design within IT, through to issues surrounding product design, communication, and marketing.
Project developers need to understand how users approach their products from the product’s infancy, and regardless of what the product might be. Developers should be able to describe the user of the product via vivid depictions, as if they – with their different attitudes, desires and habits – were already using the product. In doing so they can more clearly formulate how to turn the product's potential into reality.
Based on 20 years’ experience in solving problems for businesses and 15 years of research, currently at the IT University of Copenhagen, Lene Nielsen is Denmark’s leading expert in the persona method. She has a PhD in personas and scenarios, and through her research and practical experiences has developed her own approach to the method – 10 Steps to Personas. This second edition of Personas – User Focused Design presents a step-by-step methodology of personas which will be of interest to developers of IT, communications solutions and innovative products. This book also includes three new chapters and considerable expansion on the material in the first edition.
Here, we present the outcome of the 4 th workshop on Multisensory Approaches to Human-Food Interaction (MHFI), developed in collaboration with ICMI 2020 in Utrecht, The Netherlands. Capitalizing on the increasing interest on multisensory aspects of human-food interaction and the unique contribution that our community offers, we developed a space to discuss ideas ranging from mechanisms of multisensory food perception, through multisensory technologies, to new applications of systems in the context of MHFI. All in all, the workshop involved 11 contributions, which will hopefully further help shape the basis of a field of inquiry that grows as we see progress in our understanding of the senses and the development of new technologies in the context of food.
CCS CONCEPTS • Human-centered computing, Human computer interaction (HCI), Interaction paradigms
In human interaction, people will keep different distances from each other depending on their gender. For example, males will stand further away from males and closer to females. Previous studies in virtual reality (VR), where people were interacting with virtual humans, showed a similar result. However, many other variables influence proximity, such as appearance characteristics of the virtual character (e.g., attractiveness). Our study focuses on proximity to virtual walkers, where gender could be recognised from motion only, since previous studies using point-light displays found walking motion is rich in gender cues. In our experiment, a walking wooden mannequin approached the participant embodied in a virtual avatar using the HTC Vive Pro HMD and controllers. The mannequin animation was motion captured from several male and female actors and each motion was displayed individually on the character. Participants used the controller to stop the approaching mannequin when they felt it was uncomfortably close to them. Based on previous work, we hypothesised that proximity will be affected by the gender of the character, but unlike previous research, the gender in our experiment could only be determined from character’s motion. We also expected differences in proximity according to the gender of the participant. We additionally expected some motions to be rated more attractive than others and that attractive motions would reduce the proximity measure. Our results show support for the last two assumptions, but no difference in proximity was found according to the gender of the character’s motion. Our findings have implications for the design of virtual characters in interactive virtual environments.
Advertisements in social media can be tailored to psychographic profiles based on consumers' digital-trace data. An experiment (N = 936) investigated the conditions under which such trait-based personalization of social media messages is more effective than non-personalized messages and which personality traits and user characteristics are most suitable for this purpose. In a 9 × 2 between-subjects design, the persuasive appeal of a Facebook ad and the advertised product (phone vs. soda) were varied. Participants' ‘Big Five’ personality traits, need for cognition, and susceptibility to persuasive strategies were assessed in a questionnaire. Results showed limited effects of personality matching. Matched messages led to increased intentions to engage with the post when they addressed specific persuasive susceptibilities (particularly toward authority influence). However, there were no consistent effects on consumers' attitudes toward the advertised products. Findings are discussed regarding the ongoing debate on microtargeting in social media.