Eurico Carrapatoso

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. © 2017 Springer-Verlag Berlin Heidelberg

Abstract

Abstract
PCMAT (Mathematics Collaborative Learning Platform) is a collaborative adaptive learning tool based on progressive assessment for Mathematics in Basic Schools. The learning platform is based on a constructivist approach, assessing the user knowledge and presenting contents and activities adapted to the characteristics and learning style of the student. The intelligent behavior of such platform depends on the existence of a tentative description of the student - the student model (SM). The contents of this model and the student most prominent learning style are used by a domain and interaction model to select the most appropriate response to student actions. The SM is used to select the more appropriate learning object according to the student learning stage. However, this selection demands for the access to metadata describing the contents of the learning object. This need leaded to the application of a standard to describe the learning objects (LO). The authoring of LO corresponds to one major maintenance costs present in these applications. PCMAT is able to generate several instances of the same learning object through the parameterization of some features of the learning object. The platform is also able to process student responses in natural language. This project shows how techniques from Adaptive Hypermedia System (AHS) field can improve e-learning based systems in a basic school environment. © Springer-Verlag Berlin Heidelberg 2013.

Abstract
Vários desenvolvimentos têm sido verificados, recentemente, em áreas como os sistemas de recomendação, desenvolvimento Web, redes sociais, concepção de interfaces e sistemas de informação geográfica. Conjugá-los pode proporcionar uma experiência superior à soma das suas contribuições no que diz respeito à satisfação do utilizador. Este artigo oferece uma discussão da aplicação do conjunto destas inovações ao e-tourism, mais concretamente na construção de uma plataforma Web de informação geográfica que possa ser adaptada a qualquer região turística. Como caso de estudo mostra-se também a sua utilização na Região do Douro. A plataforma Web construída como proof of concept agrega informação geográfica proveniente de fontes dispersas e heterogéneas, compreendendo eventos, notícias, rotas e pontos de interesse (POI). Esta plataforma contempla ainda um motor de recomendações e conta adicionalmente com a possibilidade dos utilizadores poderem contribuir conteúdos como parte da comunidade.

Abstract