As Human-Robot Interaction (HRI) and Human-Robot Collaboration (HRC) integrate into society, there's a growing need for flexible, safe, and cost-effective methods to evaluate HRI and HRC from a human perspective. Current evaluation techniques, which often rely on physical hardware, are limited by high costs, safety risks, and low replicability. To address these challenges, we introduce Platform for Evaluating Human-Robot Collaboration and Interaction in Virtual Environments (PEHRCIVE), a software tool built with Unity that leverages Virtual Reality (VR) to provide a safe, flexible, and low-cost research platform. PEHRCIVE provides a customizable, immersive VR environment for HRI and HRC research, based on a collaborative interlocking block assembly task, three distinct collaborative robots (Kuka LBR iiwa, Rethink Robotics Sawyer, and Baxter), and sequential and simultaneous collaboration modes. Features include an easily modifiable external configuration file, a robust data logging system with timestamps and task-specific metrics, and customizable answered-in-VR questionnaires for data collection. PEHRCIVE was validated with 36 participants by collecting physiological and psychological data and responses to the Godspeed Questionnaire Series and VR Presence questionnaire. Participants reported a high sense of presence and a positive VR experience, confirming the platform's effectiveness as a research tool. PEHRCIVE facilitates the design, testing, and evaluation of HRI and HRC experiments more efficiently and safely, accelerating progress for the research community.

Rhythmic Gymnastics is an Olympic sport that demands an exceptional level of expertise. From early age, athletes relentlessly practise exercises until they can flawlessly perform them before an audience and a panel of judges. Technology can potentially support rhythmic gymnasts’ training by monitoring gymnasts’ exercises and providing feedback on their execution. However, the limited understanding of the training nuances in Rhythmic Gymnastics restricts the development of technologies to support training. Drawing on the observation of training sessions and on interviews with athletes and coaches, this paper uncovers how coaches personalise feedback timing, type, form, format, and quantity, to adapt it to the gymnasts’ skill level and type of exercise. Taking stock of our findings, we draw out five implications that can inform the design of systems to support feedback in Rhythmic Gymnastics training.

The underrepresentation of women in Computer Science and Engineering is a pervasive issue, impacting the enrolment and graduation rates of female students as well as the presence of women in leadership positions in academia and industry. The European Network For Gender Balance in Informatics (EUGAIN) COST action seeks to share data, experiences, best practices, and lessons from failures, and to provide actionable tools that may contribute to the advancement of gender balance in the field. This paper summarises results from the Ph.D./Postdoc to Professor workgroup that were gathered in two booklets of best practices. Specifically, we introduce the Equality Maturity Model (EMM), a conceptual tool aimed at supporting organisations in measuring how they are doing concerning equality and identifying potential areas of improvement and that was inspired by both booklets.

This study proposes an Ontology for Computer Science (CS) students' profiles. This Student model will represent information about the CS student and will be created by extracting constructs and variables from applied questionnaires. The literature presents several instruments that analyze the student's profile and performance in STEM and Computer Science. Some questionnaires were used to determine the profile of CS students to extract constructs and variables such as (a) Sociodemographic and economical; (b) Personality Type; c) Academic performance in secondary education; d) Learning experiences; f) Attitudes toward Programming; g) Science Motivation. h) Parental/Social Support. Our overarching research question of this study is to answer: How can we build an ontology for the computer science student profile that identifies the main factors that motivated him/her to choose a course in this area? This study will build the proposed ontology using the Ontology Development 101 methodology. The proposed ontology will be validated with real-world data and intended to develop case studies to administer internationally validated questionnaires to university students enrolled in Computer Science Major-related courses in public universities. The expected results are to know and trace the profile of CS students (female and male) since secondary education to promote better actions that increase the interest of secondary school students, mainly girls, in the IT area. Thus, this work intends to build an Ontology of CS Students as part of a recommendation system that will make suggestions for actions that encourage more students to pursue a career in Computer Science and then, be able to increase the supply of IT professionals in the market: workforce, especially women.

Serious games are a category of games which purpose extends beyond entertainment. Among these, we find a specific type of games, exergames, which aim to promote physical activity. Despite the positive influence of exergames on their users, players often stop playing them after a short period of time, losing the positive benefits of gameplay. It is in this context, that the need to better understand the experience and the opinions of players emerges. To grasp what users feel and (dis)like is key so that games can be redesigned and improved to fit users preferences. This work proposes to analyse users' comments from YouTube, using Natural Language Processing techniques, to extract knowledge on usability, user experience and perceived impacts on health, in particular on quality of life, that could inform the redesign of the game thereafter. This paper is a work in progress that reports on preliminary work that explores users opinions about the Just Dance game. In mining users' opinions, the process of annotation of usability, user experience and quality of life dimensions is based on a pre-established vocabulary. Each extracted opinion is annotated with the concepts present in the opinion, using an approach that is based on the English dictionary lexicon in conjunction with sentiment analysis. The results obtained are then displayed on a dashboard, where the data extracted from the previously collected user comments can be viewed, analysed, and explored.

Studio-based learning (SBL) is a pedagogy that encompasses collaborative active learning strategies focusing on creativity, peer learning, and problem-solving. The iterative design procedures and critique sessions are the primary learning practices of SBL, which relays to a need to have effective communication between instructors and students. Due to this, we designed a Telegram chatbot using the TextIt to facilitate some of the interactions that are common in SBL. In this preliminary study, students’ acceptance of chatbot was investigated based on the Technology Acceptance Model (TAM) using a mix-method approach. Preliminary results indicated positive acceptance and intention to use chatbots due to ease of use, mobile accessibility, human-like communications, and privacy in communicating and providing feedback.

While guidelines for designing websites and iTV applications for older adults exist, no previous work has suggested how to best design TV user interfaces (UIs) that are accessible to older adults. Building upon pertinent guidelines from related areas, this paper presents thirteen recommendations for designing UIs for TV applications for older adults. These recommendations are the result of iterative design, testing, and development of a TV-based health system for older adults that aims to provide a holistic solution to improve quality of life for older adults with chronic conditions by fostering their autonomy and reducing hospitalization costs. The authors' work and experience shows that widely known UI design guidelines unsurprisingly apply to the design of TV-based applications for older adults, but acquire a crucial importance in this context.

Public transport networks (PTNs) are difficult to use when the user is unfamiliar with the area she is traveling to, as shown by a user survey that we present in this paper. This is true for both infrequent users (including visitors) and regular users who need to travel to areas with which they are not acquainted. In these situations, adequate on-trip navigation information can substantially ease the use of public transportation and be the driving factor in motivating travelers to prefer it over other modes of transportation. However, estimating the localization of a user is not trivial, although it is critical for providing relevant information. In this paper, we propose the use of an electronic ticketing infrastructure of a PTN operator for positioning within the context of the PTN to give on-trip personalized navigation cues. To our knowledge, this is an innovative contribution that has not been described or deployed, to date, elsewhere. We assess relevant design issues for a modular cost-efficient user-friendly on-trip navigation service that uses position sensors and present the details of a proof-of-concept prototype running in our laboratory. We also present and analyze the results of a user survey on the usefulness of the service and its acceptance by users.