Abstract
Novel input modalities such as touch, tangibles or gestures try to exploit human's innate skills rather than imposing new learning processes. However, no work has been reported that systematically evaluates how these interfaces influence users' performance, that is, assesses if one interface can be more or less appropriate for interaction regarding: (1) different age groups; and (2) different basic tasks, as content insertion or manipulation. This work presents itself as an exploratory evaluation about whether or not the users' efficiency is indeed influenced by different input modalities and age. We conducted a usability evaluation with 60 subjects to understand how different interfaces may influence the speed and accuracy of three specific age groups (children, young adults and older-adults) when dealing with a basic content insertion task. Four input modalities were considered to perform the task (keyboard, touch, tangibles and gestures) and the methodology was based on usability testing (speed, accuracy and user preference). Overall, results show that there is a statistically significant difference in speed of task completion between the age groups, and there may be indications that the type of interface that is used can indeed influence efficiency in insertion tasks, and not so much other factors like age. Also, the study raises new issues regarding the "old" mouse input versus the "new" input modalities. © 2016 ACM.

Abstract
The recent advances made in human-computer interaction have allowed us to manipulate digital contents exploiting recognitionbased technologies. However, no work has been reported that evaluates how these interfaces influence the performance of different user groups. With the appearance of multiple sensors and controllers for hand gesture recognition, it becomes important to understand if these groups have similar performance levels concerning gestural interaction, and if some sensors could induce better results than others when dealing with users of different age brackets. In this respect, it could also be important to realize if the device's sensor accuracy in terms of hand / full body recognition influences interaction performance. We compare two gesturesensing devices (Microsoft Kinect and Leap Motion) using Fitts' law to evaluate target acquisition performances, with relation to users' age differences. In this article, we present the results of an experiment implemented to compare the groups' performance using each of the devices and also realize which one could yield better results. 60 subjects took part in this study and they were asked to select 50 targets on the screen as quickly and accurately as possible using one of the devices. Overall, there was a statistically significant difference in terms of performance between the groups in the selection task. On the other hand, users' performance showed to be rather consistent when comparing both devices side by side in each group of users, which may imply that the device itself does not influence performance but actually the type of group does. © 2015 ACM.

Abstract
With the thriving of different natural interaction paradigms-such as gesture-based interfaces-it becomes important to understand how these novel interfaces can influence users' performance when it comes to their age. Recent advances made in human-computer interaction allow us to manipulate digital contents more intuitively; however, no work has yet been reported that systematically evaluates how gestural interfaces may influence the performance of different user groups. Different optical sensors, which allow human body acquisition with reliable accuracy, have been released, and with the appearance of such controllers for gesture recognition, it becomes important to understand if different age-related groups display similar performance levels concerning gestural interaction, or, on the other hand, if specific sensors could induce better results than others when dealing with users of different age brackets. In this article, we compare two gesture-sensing devices (Microsoft Kinect and Leap Motion) using the Fitts' law model to evaluate target acquisition performance, with relation to three user groups: children, young adults and older adults. This case study involved 60 participants that were asked to perform a simple continuous selection task as quickly and accurately as possible using one of the devices for gestural recognition. Indeed, performance results showed statistically significant differences among the age groups in the selection task accomplished. However, when considering the users' performance with regard to both input devices compared side by side, there were no significant differences in each group of users. We believe this situation could imply that the device itself might not have influenced the users' performance, but actually the users' age might. The participants feedback was interesting on account of their behaviors and preferences: Although there are no significant differences in performance, there could be when it comes to user preference.

Abstract
Navigation through immersive virtual environments is a key concept for virtual reality as it allows users to explore those environments. Therefore, it is important to understand virtual reality navigation interfaces and their impact on the users' experience. This paper presents an objective performance evaluation of two types of navigation: natural (real walking and walk-in-place) vs. unnatural (gamepad). Steering Law was the objective performance metric chosen since it captures the relationship between the time to travel a path and the difficulty of that path. In addition to performance, subjective metrics were also considered, namely the feeling of presence, cybersickness and user satisfaction. The experiments consisted of having participants complete a series of paths with different indexes of difficulty and the time that a participant took to walk each path was measured. Overall results show that the navigation through real walking yielded better results when it comes to performance, cybersickness, and user satisfaction than the walk-in-place and gamepad navigation interfaces.

Abstract
Dyscalculia is a specific neurological affliction that disrupts a person's ability to understand and manipulate numbers. We intend to develop a serious game for children who attend primary school (up to 4th grade) and whose purpose is making the learning of basic mathematics (simple arithmetic) easier, by introducing specific mathematical problems and educational games that stimulate memory, among other aspects. To that end, we undertook a straightforward and preliminary evaluation of the serious game developed and present its results. Indeed, we believe that the findings of our pilot case study can be useful to determine some perceptions that may be vital to understanding the problems with teaching mathematics and the issues students face in this regard.

Abstract
Mobile devices, as smartphones and tablets, have presented an exponential growth, being part of our everyday life, particularly considering children [1]. Their daily habits are undoubtedly influenced by technology and the applications they use can affect socialization and learning processes [2]. Specifically, games are the most popular type of applications and have the potential to change attitudes and behaviours. Emphasizing the importance of this area, we decided to create a serious game that stimulates the children' responsibility for taking care of pets while they play, called My Buddy. In this paper, we present the development and assessment process of a 3D serious game, where the user is asked to interact with a pet and nurture it. The interface was developed based on the universal design philosophy, presenting itself attractive to children without disabilities, but also accessible to children with visual or motor disabilities. As such, we present a multimodal interface based on touch and speech commands. The game was tested in terms of usability, with a heuristic evaluation, and the results obtained highlight the potential of such interfaces.