Abstract

Abstract

Abstract
At present, the financial market is facing severe constraints arising by household bankruptcy, mortgage debtor defaults and over-indebtedness. It is a common belief that improving economic (and financial in specific) literacy will improve the awareness of individuals about complex issues surrounding them and their ability to take financial decisions. The lack of basic knowledge about the functioning of markets may have detrimental consequences, in particular higher exposure to credit and financial risk. In spite of these wider developments, the importance of economic literacy on the making financial decisions about credits has been scarcely explored in empirical terms. This paper contributes to this line of research. Our purpose is to empirically demonstrate the influence of economic literacy on the financial decision making process, and, consequently, on the ability to meet the contracts. We analyse the Portuguese case, a country about which there is scant empirical evidence on these matters, and we use an original database built under the Economicando project. We assess how much knowledge individuals have with respect to economics lato sensu (i.e. including aspects of financial literacy). We seek to understand the relationship between economic literacy and over-indebtedness. The study has been conducted under the research project Research project "Economicando" (PTDC/EGE-ECO/100923/2008), financed by FEDER funds through the Programa Operacional Fatores de Competitividade - COMPETE and by national funds through the FCT Fundacao para a Ciencia e Tecnologia.

Abstract
Several approaches have been applied to the task of algorithm selection. In this context, Meta-Learning provides an efficient solution by adopting a supervised strategy. Despite its promising results, Meta-Learning requires an adequate number of instances to produce a rich set of meta-examples. Recent approaches to generate synthetic or manipulated datasets have been adopted with success in the context of Meta-Learning. These proposals include the datasetoids approach, a simple data manipulation technique that generates new datasets from existing ones. Although such proposals can actually produce relevant datasets, they can eventually produce redundant, or even irrelevant, problem instances. Active Meta-Learning arises in this context to select only the most informative instances for meta-example generation. In this work, we investigate the Active Meta-Learning combined with datasetoids, focusing on using the Random forest algorithm in meta-learning. Our experiments revealed that it is possible to reduce the computational cost of generating meta-examples and obtain a significant gain in Meta-Learning performance.

Abstract
Contextual mobile games provide an important opportunity for learning and development by embedding a smooth form of learning in a game. They provide a rich, rewarding, relevant and multifaceted environment in which one can actually put theory into practice in a safe, simulated manner and learn at a far deeper level as a result. They also offer continuous feedback and cooperative team learning in an inquiry-based, authentic environment where players are motivated by rewards and new levels towards achieving game goals. This paper presents a novel development framework and methodology for contextual learning mobile games systems that enables learners to practice and enhance 21st century skills, while generating and playing mobile contextual games. Additionally, we discuss the main results obtained during this Intensive Programme (IP), by looking at the potential of our design approach, the software framework and the learning experience that was afforded to the students.

Abstract
The rapid and all-encompassing changes in regional and world wine markets have stimulated us to carry out this study. Accordingly, based on the competitiveness of an important Port wine producer in Portugal, this article analyzes a strategic alliance between this company and another important multinational one that is present in many different worldwide distribution markets. Basically, the article seeks to understand, on the one side, the impact of a strategic alliance on a small Port wine producer when becoming involved with a multinational company, and, on the other hand, to identify differences, before and after the alliance, to the markets where the small company was made present. This work is centered on a case study and involves the use of econometrics methodologies that analyze panel data, in order to grasp differences of strategic pre- and post-alliance actions. The conclusions are important, since they allow one to compare, on one hand, difference between the company's performance over two different time horizons. On the other hand, econometrics methods are robust, since they allow one to come to relational conclusions, keeping the case study in mind.