Reviewerly/exHarmony huggingface dataset:
Digital Ethnography in Mixed Reality (MR) Communities: Searching New Usage Scenarios

This article aims to present the results of digital ethnographic research we conducted within the XR communities, seeking to understand what are the main pains of users of extended reality today, how they see this technology on the rise, and what perceptions they have about the future of the XR. From what we were able to analyze from the data collected in the digital ethnography, we were able to understand that XR technology is constantly evolving, but that it may soon reach a more accessible level within the market. The XR is a great revolutionary promise within several scenarios such as education, health, industry, entertainment, and social, but the current XR technologies have different factors that still need to evolve, from their immature UX within their applications to the strong deficit in their Form Factor. For these reasons they end up hindering the constant use of this technology by users in their daily routines, leaving them to use these devices only in specific activities that don't require much effort. All these factors make the mass adoption of this technology slower.
Creating a Positive Reframing Dictionary Using Machine Learning

Positive reframing is a cognitive process that involves giving negative events a new positive interpretation, leading to positive behavioral options and perceptions. Our research project aims to promote positive emotions by presenting positive reframing sentences to the negative ones the user has entered using a keyboard. To achieve this, we propose using GPT-3, a natural language processing model, to generate a large number of reframing dictionary entries in a short time. We trained GPT-3 on manually generated reframing pairs and tested it on new negative sentences. Our results show that, with three or more pairs of training data, GPT-3 can generally reframe negative sentences as expected. Our technique can be used to construct a high-quality reframing dictionary, which can help promote positive emotions and well-being.
Exploring New Futures in Video See-Through: Experience-es and Scenarios Using XR Technologies

Video-See Through (VST) is a promising tool in the XR (Mixed Reality) market today. VST allows the overlapping of digital elements in a real environment, allowing the user to see in real time the mixture of the virtual and real environment simultaneously, making XR technology more accessible and incorporated into our daily lives. VST is currently in a very experimental phase, but it already shows great promise when used to compose an XR product, gaining great notoriety in the area of security and complementation of the user experience. However, the use of VST is opening up new possibilities for XR to have even more positive impacts in its promising areas such as education, health, industry, entertainment and social. We understand these VST issues, based on research done with benchmarking, analysis of internal documents from Instituto Sidia and analysis of applications that have VST. This article presents the main findings of the exploration so far of VST in the market, presenting different types and uses of VST within an XR experience and how VST can directly influence.
Robot Path Verification Method for Automotive Glue-Coating Based on Augmented Reality and Digital Twin

The automotive glue-coating, as an important part of automobile manufacturing, has a crucial impact on automotive water-proof and rust-proof performances. The glue-coating robots need to be path planned with software, and the paths have to be repeatedly tested with the actual production line using prototype vehicles. There are multiple issues concerning nozzle damage and inefficiency by using the traditional glue-coating path verification method, which calls for a new method to solve these problems. This paper proposes a path verification method for automotive glue-coating based on augmented reality and digital twin. The results show that with this augmented reality and digital twin based method, the operator can observe the glue-coating process intuitively and immersively, so that he can adjust or re-plan the glue-coating path according to the verification results, even before the production of the actual prototype vehicle. The collision between the actual prototype vehicle and the nozzle of the glue-coating robot will be transformed into the collision between the virtual vehicle model and the robot digital twin, which can avoid nozzle damage, save a lot of time for waiting for the production of the prototype vehicle. This method is in line with the general trend of smart manufacturing development and effectively shortens the manufacturing cycle time.
Touched by VR Storytelling: A Pilot Study of the Interactive Digital Narrative Evaluation Matrix for Shaping Values

Interactive digital narrative (IDN) is a form of expression by a computer-based system with broad potential for virtual reality (VR) application. This study investigates the experience factors to clarify what it is like to shape the values of individuals and groups through VR storytelling. An IDN experience matrix is proposed for the design and evaluation of VR storytelling. This approach is based on the communication theory to map a bottom-to-up 3 × 3 structure, crossing the design process and perception level. Its usefulness was demonstrated by investigating 31 participants with a digital media background. The results show that the approach could be applied to understanding the cognitive experience of stories in VR and provides designers with an idea of how to improve the effect of shaping values. In addition, the matrix will be validated in more testing and evaluating of VR works in further study.
Model Educational ReVIso Based on Virtual Reality

The accelerated technological advance has brought opportunities in all sectors of society, one of them and the one that will be addressed in this study is the use of virtual reality in the educational aspect, for this reason, the main objective of the research is to propose the theoretical intervention model based on virtual reality to improve learning in basic and higher education students. The purpose of the ReVIso educational model is to use virtual reality as a learning medium that moves the student from a reality of abstract knowledge to a scenic, graphic and objective reality. It is concluded that the ReVIso model proposal improves student learning using virtual reality, which consists of changing the traditional practice of the teacher who generates abstract knowledge towards a context of digital transformation or metaverse where the contents are presented in a scenic way, dynamic and graphic, situation in which the student is able to generate synergy in the achievement of real and significant learning. The model moves the student and teacher to a new dimension where the dynamics of teaching and learning allows the student to develop critical, creative, reflective thinking and promote the capacity for autonomy, as well as generate empowerment spaces to propose alternative solutions in scenarios real.
Chinese Character Learning and Platform Tool Development for Junior Primary School Student Based on Orthographic Awareness

Chinese is the most spoken language in the world, and Chinese characters are the written symbol system of the Chinese language. As junior primary school students aged six to eight years old learning Chinese characters, they need to understand Chinese characters, learn to write and compose Chinese characters, and achieve certain reading skills in a relatively short period of time. In the actual learning process, junior primary school students face a variety of problems in learning Chinese characters, from their own factors to teaching methods and family environment. The need to learn Chinese characters well facing many challenges. Therefore, this study aims to understand the basic learning theory of Chinese characters and the characteristics of Chinese character learning for low school-age children, to explore the connection between Chinese character orthography awareness and children's Chinese character learning, to explore the possibility of combining Chinese character learning and digital technology, to design a mobile platform for Chinese character learning for the students, to promote the optimization and improvement of Chinese character education in the first school year, and to promote the improvement of Chinese character skills for the students aged six to eight. The study adopts a bibliometric approach, in which all the collected literature are from the China National Knowledge Infrastructure (CNKI) China Knowledge Database, and analyzed using keyword clustering via Citespace software to obtain the corresponding network. The analysis has obtained the current research hotspots and research trends, as well as relationships for Chinese character learning and tool platform development for the junior primary school student based on orthographic awareness.
Research on the Design of Digital Experience of Sichuan Opera Face-Changing Based on Flow Theory

Face-changing is a traditional performance form of Sichuan Opera in which the performer can switch between multiple faces in a short time. Special costumes and props are required for the performance, and the audience must enter the theater to watch it, making it impossible for this performance to be widely distributed. The digital products of Sichuan Opera face-changing in the market today only simulate the process of face-changing and do not allow users to have an immersive cultural experience. In this design study, we designed a Sichuan Opera digital face-changing interactive app based on the flow theory. According to the three principles of unambiguous objectives, accurate and timely feedback, and balancing skills and challenges, the app is divided into four modules: exploration, experience, interaction, and innovation. We recruited 23 users to experience the app, and the results showed that most users found the app interesting and were willing to accept them. This paper combine traditional cultural elements with modern digital technology allows traditional art performances to be widely disseminated and provides a reference point for other traditional cultures to be experienced in the digital society.
Detection of Voluntary Eye Movement for Analysis About Eye Gaze Behaviour in Virtual Communication

In this study, we aim to realize smoother communication between avatars in virtual space and discuss the method of eye-gaze interaction used for avatar communication. It is necessary for this purpose, a specific gaze movement detection algorithm, which is necessary for measuring characteristic eye movements, blinks, and pupil movements. We developed those characteristic movement counting methods using an HMD built-in eye tracking system. Most input devices used in current virtual reality and augmented reality are hand gestures, head tracking, and voice input, despite the HMD attachment type. Therefore, in order to use the eye expression as a hands-free input modality, we consider an eye gaze input interface that does not depend on the measurement accuracy of the measurement device. Previous eye gaze interfaces have a difficulty called as "Midas touch" problem, which is the trade-off between the input speed and input errors. Therefore, using the method that has been developed so far, which as an input channel using characteristic eye movement and voluntary blinks, it aims to realize an input method that does not hinder the acquisition of other meta information alike gestures of eyes. Moreover, based on involuntary characteristic eye movements unconsciously expressed by the user, such as movement of the gaze, we discuss a system that enables "expression tactics" in the virtual space by providing natural feedback of the avatar's emotional expression and movement patterns. As a first step, we report the result of measured eyeball movements face-to-face through experiments in order to extract features of gaze and blinking.
Are Scrutiny and Mistrust Related? An Eye-Tracking Study

Eyes are an important organ in both information processing and communicating. Eye gaze contains rich information about our attention and internal state. It has previously been studied as a measure of trust in various contexts such as air traffic control, driving, and online shopping. The study uses fixation and saccadic measurements to obtain a viable measure of human trust. The experiment involved nine participants and their trust level was indicated by whether they accepted or rejected a decision made by an Artificial Intelligence (AI). A Tobii pro nano eye-tracker and psychopy software were used to track the participants' eye gaze and responses. Results indicate that saccade count shows a statistically significant variation between trust and mistrust conditions with p < 0.05, while the fixation count showed a variation at p < 0.2. Through this study, we show that the count of saccades is a viable measure of a human's mistrust in an AI system.
Exploring the Potential of Augmented Reality in English Language Learning: Designing an Interactive Pronunciation Training App

Augmented reality (AR) has the potential to transform teaching and learning by providing real-time interactions, displaying information in various ways, and connecting the physical and digital worlds. While AR technology is becoming more accessible through mobile devices and head-mounted displays (HMDs), its widespread adoption in education depends on providing an engaging and interactive user experience. Designing appropriate AR user interfaces is crucial for ensuring the technology is easily adopted and enjoyed by users. One area where AR can be particularly beneficial is in the teaching of the English language and correct pronunciation, especially at an early stage of education. In the English language, vowels play a key role as they appear in every syllable of every word. Understanding vowel sounds is closely tied to reading skills. To address this, an AR-based pronunciation training app has been developed, based on linguistic theory and with a focus on usability for students learning English as a second language. The app is implemented using a Microsoft HoloLens head-mounted display and provides an AR-based learning experience. This study describes the factors that led to the development of the AR-based pronunciation app. This is an app that allows a user to be assessed on the pronunciation of selected 3D learning objects and receive meaningful feedback. As hardware advances and becomes more widely available, realistic holograms will be created. This will enable better technology integration with the physical world and more intuitive input methods. This will further enhance the user experience and increase technology acceptance.
Wetland Challenge—Using Service Design Research as an Approach to Establish an AR APP for Environmental Education

Given the looming threat of catastrophic environmental disasters, there has never been a more urgent need for establishing awareness of the importance of sustainable environments through environmental education. Chenglong Wetland in Kouhu Township, Yunlin County, Taiwan, has been dramatically affected by land subsidence and slow climate change resulting from global warming. This has forced Chenglong Village to abandon its traditional fish farming industry and instead turn to green energy and economic development. However, this shift has led to the loss of wetland ecological resources, highlighting the pressing need for environmental education among the residents. The current study aims to explore how service design, a methodology incorporating input from experts and stakeholders, can facilitate communication with residents regarding the wetland, environmental crises, and associated risks. This study employed service design methods to explore the experiential and cognitive needs of stakeholders through the Chenglong Wetland narrative project. A digital environmental guide system was created for local elementary school students using a persona and user map developed after interviews. The guide system integrated Augmented Reality (AR) technology and location-based functions to establish a narrative experience flow and provide relevant information for wetland environmental education. The resulting AR environmental guide app is expected to enhance public awareness of climate change issues and increase attention to ecological and environmental conservation.
Road Scene Risk Estimation Using Driving Video

In this study, we propose a method for potential risk estimation of road scenes from driving videos and investigate the relationship between the potential risk estimation and the risk perception of humans. We employ a frame prediction method and define scenes where the frame prediction accuracy decreases as risky scenes. We also use the scene depth estimated from the color image and use the prediction error of the scene depth as another risk criteria. The relationship between the proposed risk criteria and the risk perception of humans was evaluated by subject experiments.
Considerations for Developing a Generalized Gradebook for an Open-Source Intelligent Tutoring System Framework

The current paper describes a use case of an open-source intelligent tutoring system (ITS) framework, the Generalized Intelligent Framework for Tutoring (GIFT). GIFT has been primarily used by researchers, and it is a highly flexible system that allows for tutoring to be created in the topic area of the author’s choice. While there are tools to output data from GIFT, there is not a traditional standardized gradebook tool that can be easily used by a non-researcher. Due to the generalizable design of GIFT, and the unique characteristics of intelligent tutoring performance, this is an interesting design challenge. The current paper discusses the current state of data export in GIFT, describes the adaptive courseflow approach to tutoring in GIFT, and discusses potential approaches to visualizing adaptive tutoring data in a way that instructors can easily understand and gain the maximum knowledge from.
Key Factors Influencing the Degree of Acceptance of an Intelligent Customer Service System - A Literature Review

In the context of artificial intelligence offensive markets, intelligent customer service robots have joined the traditional customer service system. Although intelligent customer service is widely used in e-commerce, finance, education and the phenomenon of rejecting intelligent customer service services often turned directly to manual. This article searches and investigates the current intelligent customer service market through a large number of literature. The purpose is to explore the key factors that affect the success of intelligent customer service, and propose the intelligent customer service system that can be more accepted by the public. The work done in the article is to use the existing Systematic Satisfaction Evaluation Model and TAM to explore the key factors affecting the acceptance of the intelligent customer service system. From the analysis of the three elements of tasks, intelligent customer service robots, and users five indicators of Flexibility, Integration, Accessibility, and Timelits’ starting points to change the system’s perception and usefulness and perception to improve the user experience, and the user is willing to accept and trust intelligent customer service. Finally, make predictions on the customer service industry in the future: intelligent customer service and manual customer service coexist, division of labor cooperation, and complementary advantages, so that intelligent customer service can be used, creating intelligent and empathized customer service systems.
Requirements for Explainability and Acceptance of Artificial Intelligence in Collaborative Work

Abstract The increasing prevalence of Artificial Intelligence (AI) in safety-critical contexts such as air-traffic control leads to systems that are practical and efficient, and to some extent explainable to humans to be trusted and accepted. The present structured literature analysis examines $$n = 236$$ articles on the requirements for the explainability and acceptance of AI. Results include a comprehensive review of $$n = 48$$ articles on information people need to perceive an AI as explainable, the information needed to accept an AI, and representation and interaction methods promoting trust in an AI. Results indicate that the two main groups of users are developers who require information about the internal operations of the model and end users who require information about AI results or behavior. Users’ information needs vary in specificity, complexity, and urgency and must consider context, domain knowledge, and the user’s cognitive resources. The acceptance of AI systems depends on information about the system’s functions and performance, privacy and ethical considerations, as well as goal-supporting information tailored to individual preferences and information to establish trust in the system. Information about the system’s limitations and potential failures can increase acceptance and trust. Trusted interaction methods are human-like, including natural language, speech, text, and visual representations such as graphs, charts, and animations. Our results have significant implications for future human-centric AI systems being developed. Thus, they are suitable as input for further application-specific investigations of user needs.
Volition Learning: What Would You Prefer to Prefer?

When queried, humans do not always give their utmost attention to provide their best possible answer. In particular, they may give different answers to the same question, depending on their level of concentration and interest. This raises a challenge for ethical preference learning. Arguably, we would prefer to learn what humans answer after thoughtful considerations, rather than what they answer when they are tired and lack focus. To distinguish it from instinctive unreflexive preferences, the former is sometimes called a volition. In this paper, we propose a basic machine learning approach to learn volitions rather than preferences. To do so, we developed a pairwise comparison model that learns from comparison ratings of pairs of items based on selected quality features. We considered the time spent in producing these ratings as an important contextual metadata: we assume that it effectively contributes to describe volitional behavior, rather than noisy preference-based behavior. Then, we designed an evaluation methodology based on a volition prediction method, that we defined using the learned parameters of our model. We run extensive simulations using synthetic data, as well as a real-world dataset, to validate our claims about users’ volitional behaviors. The experimental results proved the efficiency of our model to provide concrete measurements of important volition-dependent parameters, which can be used primarily to assess the reliability and the importance of users’ decisions, as well as their level of confidence and knowledge. In general, our model can serve as a foundation for further theoretical and empirical investigations in this topic. It may further incentivize research interest towards friendly and beneficial human-AI interactive systems (e.g., recommender systems) using the theory of volition.