Abstract
In an idea generation meeting, the facilitator role is essential to obtain good results. Also the emotional context of the meeting partially determines the (un) success of the meeting, being it of idea generation or decision selection. So the facilitator needs to obtain and process this information in order to assist the participants to reach their goals in different processes of decision making. In this paper is proposed a multi-agent framework able to be used in the support of persons in a affective context-aware and ubiquitous group decision process. Insights of the context-aware model are provided. It allows the gathering of certain typical variables of the affective context (emotions and mood) and transform those values in advises to the facilitator.

Abstract

Abstract
Serious games are games where the entertainment aspect is not the most relevant motivation or objective. TimeMesh is an online, multi-language, multiplayer, collaborative and social game platform for sharing and acquiring knowledge of the history of European regions. As such it is a serious game with educational characteristics. This article evaluates the use of TimeMesh with students of 13 and 14 years-old. It shows that this game is already a significant learning tool about European citizenship.

Abstract
This paper presents a modeling environment (ME) developed for a Domain Specific Language (PARADIGM) which aims to support the construction of models to be used in the context of Model Based GUI Testing (MBGT). It starts by briefly presenting PARADIGM which aims to increase the level of abstraction of the models and promote reuse in order to diminish the effort in building models for MBGT. Afterwards, it describes the architecture of the ME, how the constraints of the language are enforced within the ME to ensure the consistency of the models built, the test case configuration of the model elements, the test case generation algorithm and how the ME can be extended/adapted to include additional features.

Abstract
User Interface (UI) patterns are used extensively in the design of today's software. UI patterns embody commonly recurring solutions that solve common GUI design problems, such as "login," "file-open," and "search." Yet, testing of GUIs for functional correctness has largely ignored UI patterns. This paper formalizes the notion of a Pattern-Based Graphical User Interface (GUI) Testing method (PBGT) for systematizing and automating the GUI testing process. The space of all possible interactions with a GUI is typically very large. PBGT presents a new methodology to sample the input space using " UI Test Patterns," that embody commonly recurring solutions to test GUIs. Our empirical studies show that the PBGT methodology is effective in revealing faults in fielded GUIs.

Abstract
English is by far the most used language on the web. In some domains, the existence of less content in the users' native language may not be problematic and even help to cope with the information overload. Yet, in domains such as health, where information quality is critical, a larger quantity of information may mean easier access to higher quality content. Query translation may be a good strategy to access content in other languages, but the presence of medical terms in health queries makes the translation process more difficult, even for users with very good language proficiencies. In this study, we evaluate how translating a health query affects users with different language proficiencies. We chose English as the non-native language because it is a widely spoken language and it is the most used language on the web. Our findings suggest that non-English-speaking users having at least elementary English proficiency can benefit from a system that suggests English alternatives for their queries, or automatically retrieves English content from a non-English query. This awareness of the user profile results in higher precision, more accurate medical knowledge, and better access to high-quality content. Moreover, the suggestions of English-translated queries may also trigger new health search strategies.