Abstract
E-Learning, much like any other communication processes, has been significantly shaped by technological evolution. In its original form, e-Learning aimed to bring the education closer to people, making it more modular and personalized. However, in reality, we observe that it represents a separation between student and teacher, simplifying this relationship to the exchange of "text-based messages", leaving aside all the important contextual richness of the classroom. We are addressing this issue by devising a contextual layer for e-Learning platforms. Particularly, in this paper we describe a solution to convey information about the level of stress of the students so that the teacher can take better and more informed decisions concerning the management of the learning process.

Abstract
Stress is a highly complex, subjective and multidimensional phenomenon. Nonetheless, it is also one of our strongest driving forces, pushing us forward and preparing our body and mind to tackle the daily challenges, independently of their nature. The duality of the effects of stress, that can have positive or negative effects, calls for approaches that can take the best out of this biological mechanism, providing means for people to cope effectively with stress. In this paper we propose an approach, based on mouse dynamics, to assess the level of stress of students during online exams. Results show that mouse dynamics change in a consistent manner as stress settles in, allowing for its estimation from the analysis of the mouse usage. This approach will allow to understand how each individual student is affected by stress, providing additional valuable information for educational institutions to efficiently adapt and improve their teaching processes.

Abstract
Having knowledge about social interactions as a basis for informed decision support in situations of conflict can be determinant. However, lower attention is given to the social network interpretation process in conflict management approaches. The main objective of the work presented here is to identify how the parties' social networks correlate to their negotiation performance and how this can be formalized. Therefore, an experiment was set up in which was tried to streamline all the relevant aspects of the interaction between the individual and its environment that occur in a rich sensory environment (where the contextual modalities were monitored). This research explicitly focuses on the idea that an Ambient Intelligence system can create scenarios that augment the possibilities of reaching a positive outcome taking into account the role of contextualized social relationships in various conflict management strategies.

Abstract
In this busy society of ours people push their limits to work better and more in order to remain competitive with their peers. Nonetheless, working longer hours does not necessarily improves productivity nor performance. In order to prevent the negative consequences of this increasing trend, the evolution of performance throughout the day of work should be more closely monitored. This could avoid undesirable states or even breakdowns, which have social and economical implications. In this work we measure user performance through their interaction with the computer. We monitor its evolution during a day of work and how different types of music may increase or decrease its natural daily degradation. We conclude that the relationship between types of music and its effects is not universal and depends, among other things, on the musical profile of the individual. A prototype for a distributed music recommendation service is presented that suggests musics at an individual and group level, based on user musical profiles and objectives.

Abstract
Nowadays, our lifestyle can lead to a scatter of focus, especially when we attend to several tasks in parallel or have to filter the important information from all the remaining one. In the context of a computer this usually means interacting with several applications simultaneously. Over the day, this significant demand on our brain results in the emergence of fatigue, making an individual more prone to distractions. Good management of the working time and effort invested in each task, as well as the effect of breaks at work, can result in better performance and better mental health, delaying the effects of fatigue. This paper presents a non-intrusive and non-invasive method for measuring distraction and fatigue in an individual and in a group of people. The main aim is to allow team managers to better understand the state of their collaborators, thus preparing them to take better decisions concerning their management.

Abstract
Mental fatigue is a concern for a range of reasons, including its negative impact on productivity and quality of life in general. The maximal working capacity and performance of an individual, whether physical or mental, generally also decreases as the day progresses. The loss of these capabilities is associated with the emergence of fatigue, which is particularly visible in long and demanding tasks or repetitive jobs. However, good management of working time and of the effort invested in each task, as well as the effect of breaks at work can result in better performance and better mental health, delaying the effects of fatigue. In this paper a model and prototype are proposed to detect and monitor fatigue, based on behavioral biometrics (Keystroke Dynamics and Mouse Dynamics). Using this approach, the aim is to develop leisure and work context-aware environments that may improve quality of life and individual performance, as well as productivity in organizations. © Springer International Publishing Switzerland 2016.