Transition is the adequate term for characterising contemporary societies. Norms and values are in transit, led by a technological revolution, which is, in itself, the tip of the iceberg of millenary social and cultural changes. Heidegger, one of the leading philosophers of the twentieth century, captured this tension between social change and innovative technology and showed that the Western civilisation was captive of ontological instances whose role was already pin-pointed by Greek Antiquity philosophy but which went underground with Modernity. The product of Heidegger’s work was a revolution in Western thought, which found echoes across all areas of society. Taking Husserl’s call for “back to the things themselves”, Heidegger’s impact has empowered the calls for more sustainable and resilient societies. Sustainability models, with its three pillars of environmental, economic and social sustainability, are directly dependent upon the role of technology and of information science in shaping current patterns of production and consumption in contemporary societies. Industrial, academic and political discourses already voice such taken for granted assumptions. Nevertheless, it is crucial to clarify and to highlight the links between economic evolution and progress, social change and the catalysing role of technology, taken as an enabler of human action.

This article argues that games give rise to ludic modes of operation and these modes spread throughout digital society. So,digital is not reduced to different ways of producing and distributing content, it reconfigures the production of knowledge. The text is organized in 2 parts: the first one shows how the development of the graphical user interface (GUI) was inspired by games as a way to make the GUI more interactive and playful. Since ludic and interactive practices dialogue with theories that decentralize the human and reason, the second part, seeks in the cognitive sciences a complex and transdisciplinary theoretical approach that dialogues with ludic and the production of knowledge.

The intuitive interaction between humans and computers is a field of research that has been investigated in recent years. The use of different types of sensors, such as motion sensors, touch, etc., have provided great strides in this area. However, according to the specificity of each sensor, the cost for developing some applications it is often infeasible. Currently with greater access to image capture devices and computers with enough processing capability, you can identify interaction without the need for special devices. Thus, this work has as main objective the proposal for a model as an alternative to using real sensors, in this case, touch sensors for human-machine interaction. As validation of the proposed model was developed an application that makes possible the interaction between the user and the image projected by an image projector. For this, we used the techniques of artificial intelligence and processing images, which allowed to identify relevant information from the scene (targets), isolating them through the use of image segmentation, and finally, the use of the term histogram to identify whether or not there was interaction.

Stress evaluation is nowadays gaining an increasing importance in a time in which inter-individual competition continuously pushes us to be better. Indeed, in the workplace, in the academia or in many other contexts there is increasing pressure for better performance, which pushes us forward but also wears us out. This phenomenon has been studied from many different angles, including psychology, medicine or occupational dynamics. In a medical or biological context, stress is a physical, mental, or emotional factor that causes bodily or mental tension, which can cause or influence the course of many medical conditions including psychological conditions such as depression and anxiety. In these cases, individuals are under an increasing demand for performance, driving them to be under constant pressure, and consequently to present variations in their levels of stress. To mitigate this condition, this paper proposes to add a new dimension in human–computer interaction through the development of a distributed multi-modal framework approach entitled X3S, which aims to monitor and assess the psychological stress of computer users during high-end tasks, in a non-intrusive and non-invasive way, through the access of soft sensors activity (e.g. task performance and human behaviour). This approach presents as its main innovative key the capacity to validate each stress model trained for each individual through the analysis of cortisol and stress assessment survey data. Overall, this paper discusses how groups of medical students can be monitored through their interactions with the computer. Its main aim is to provide a stress marker that can be effectively used in large numbers of users and without inconvenience

Self-regulated learning (SRL) significantly influences students' learning behaviors and academic performance. However, research has focused on "between-person" differences, neglecting "within-person" variability. Traditional SRL assessments rely on self-reports, which fail to capture fine-grained behavioral changes (such as hourly variations). We propose a novel approach using mobile sensing to assess SRL through within-person variability. We use passive sensing data from the phones of 211 university students to explore this relationship. To assess behavioral variability, we focus on five sensing behaviors—physical activity, social interactions, sleep, location, and app usage data—and calculate four within-person variability features: standard deviation, circadian rhythm, regularity index, and flexible regularity index. Our findings reveal significant associations between these variability features and self-reported SRL skills, particularly in dimensions such as environment structuring, time management, and help seeking. This research provides new insights into assessing SRL and offers a theoretical foundation for future personalized interventions in educational settings.

The worldwide pandemic caused by Covid-19 accelerated the digitisation of several services, usually performed uniquely offline before the isolation period enforced by the virus. Among these services are online medical consultations. This work looked into the possibility of using mobile devices to monitor a patient's health and provide medical help after contamination by the covid virus - a period referred to as long-covid. This project aimed to design a self-reporting mobile application (Careswitch) that could help long-covid patients cope with this new condition by monitoring and sharing their physical and mental symptoms and, at the same time, benefit from the contact with a doctor. A User-Centred Design approach that included interviews, a comparative analysis of similar applications, and usability testing was the basis of a design process where the needs and goals of the users were always front and center. After analysing the data collected during User Research, it was possible to translate the gathered insights into features of a high-fidelity interactive prototype of an application that has the potential to offer personalized care to long-covid patients.

This dissertation addresses the usability improvement of a graphical user interface that allows query formulation without using textual query languages, such as SQL. This visual tool, called Aggregates, is provided on the OutSystems Low-Code Development Platform, to formulate data queries, through interaction and manipulation of visual components. Since Aggregates do not support all the existing functionalities of SQL, the OutSys- tems Platform allows users to build queries using this textual query language. Nonethe- less, by evaluating customers’ SQL queries, it was revealed that a considerable subset of the queries written in SQL could have been formulated using the visual tool. The users’ interviews and the results of the SQL queries evaluation have foreseen that the cause of the reduced acceptance of the visual approach, could be the existing usability problems on the interface. Furthermore, the interface is inadequate to build more complex queries, which involve more entities and conditions. Through an iterative design process, this dissertation includes the design, implemen- tation, and evaluation of prototypes with different fidelity levels. The aim is to optimize the effectiveness and efficiency of the process where users communicate to the system what data they intend to extract from the database. Moreover, the readability and com- prehension improvement of the query visual representation is intended, reducing the time and the effort required to understand what data will be gathering from the database. The final implemented interface is currently incorporated on the OutSystems Platform to accelerate the query formulation process without harming the learnability of the system.