Abstract
This paper describes a quantitative study for the validation of the Wagnild and Young's Resilience Scale ® to Information Systems Students. Individual resilience can be described as the person's ability to deal with problems, overcome obstacles, or resist the pressure caused by adverse situations, without entering into rupture. Therefore, resilience can have a significant role in students' education. However, little is known about the determinants that might undermine the resilience level of students, as well as which could affect their mental status and wellbeing, thus requiring new research efforts. This paper shows that Wagnild and Young's Resilience Scale ® is suitable for Information Systems Students: Perseverance, Self-Reliance, Equanimity, Meaningfulness and Existential Aloneness, emerged as main themes from the principal components analysis, as in the original study by Wagnild and Young suggested. Additionally, it is demonstrated that health have influence in the individual resilience. © 2018 The Authors. Published by Elsevier Ltd..

Abstract
More and more technological advances offer new paradigms for training, allowing novel forms of teaching and learning to be devised. A widely accepted prediction is that computing will move to the background, weaving itself into the fabric of our everyday living spaces and projecting the human user into the foreground. This forecast turns out to be an opportunity for human-computer interaction as a way to monitor and assess the user’s stress levels during high-risk tasks. The main effects of stress are increased physiological arousal, somatic complaints, mood disturbances (anxiety, fear and anger) and diminished quality of working life (e.g. reduced job satisfaction). To mitigate these problems, it is necessary to detect stressful users and apply coping measures to manage stress. Human-computer interaction could be improved by having machines naturally monitor their users’ stress, in a non-invasive and non-intrusive way. This article discusses the development of a random forest classifier with the goal of enabling the assessment of high school students’ stress during academic exams, through the analysis of mouse behaviour and decision-making patterns. © Springer Nature Switzerland AG 2019.

Abstract
Demographic changes are leading to a growing older population (>65 years), with repercussions on age-related conditions. From a Computer Science perspective, this also means that there will soon be a significant number of users with changes in perceptual and motor skill capacities. The goal of this work is to develop an environment to support the preservation of memory and functional capacities of the elderly. Health professionals will be able to set up and personalize immersive and realistic scenarios with high ecological validity composed of visual, auditory, and physical stimuli. Patients will navigate through and interact with these scenarios and stimulate memory functions by later recalling distinct aspects of the different exercises of the tool. The long-term goal is to build a behavioral model of how older users interact with technology. © Springer Nature Switzerland AG 2019.

Abstract
The recognition of emotions in spoken words is one of the most important aspects in human communication and social relationships. Traditional approaches to the study of vocal emotional recognition involve instructing listeners to choose which one of several words describing emotion categories best characterize linguistically neutral utterances or vocalizations uttered by actors portraying various emotional states. To this end, generic experiment control software is usually used, which has some disadvantages. In this paper, we present a system that digitalizes the whole process involved in understanding how people perceive and understand vocal emotions, improving data collection, processing and analysis. Moreover, this system provides a new group of features that allows a more comprehensive characterization of the behavioral dimension underlying vocal emotional recognition. In this paper we describe this system and analyze the relationship between emotional perception, gender, age and Human-Computer Interaction.

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