Video games in the classrooms: implications of a disruptive innovation to develop the Multiple Intelligences

The present study aims to identify the framework of personal, organizational and technical variables that contribute to the viability and successful of innovative educational practices with video games within the school context to enhance the multiple intelligences. For this purpose, advantage was taken on the information previously collected through a questionnaire about the views, thoughts and experiences of a group of teachers of childhood and primary education (N=25) who voluntarily participated in a blended training activity from Center of Teachers (CEFIRE) of Valencia, around a community of practice aimed at promoting and advising projects for implementing educational video games in the classroom. The mixed methodology adopted has allowed the following: a) describe the relationship between their degree of development and daily use made of ICT in the classroom, their level of familiarity with video games,  their previous experience to integrate them for educational purposes..., and their participation in projects that focus on game-based learning; b) conduct content analysis of the opinions and thoughts expressed in a forum for teachers on innovation on and methodological strategies adopted reflected in a virtual board; and c) develop a SWOT analysis: Strengths, Weaknesses, Opportunities and Threats inherent in the implementation of experience with video games in the classroom. Among the conclusions, it is highlighted that, even though most did not have specific training or enough technological resources and the planning and implementation of innovation required them a great investment of time, their personal interest, the support given by members of the online community of practice, helped to encourage their activity, along with receptivity, positive attitude and high motivation of students with the experience. These aspects have been crucial to promote successful innovative practices with video games.

Combining multiple prioritized knowledge bases by negotiation.

Recently, several belief negotiation models have been introduced to deal with the problem of belief merging. A negotiation model usually consists of two functions: a negotiation function and a weakening function. A negotiation function is defined to choose the weakest sources and these sources will weaken their point of view using a weakening function. However, the currently available belief negotiation models are based on classical logic, which makes them difficult to define weakening functions. In this paper, we define a prioritized belief negotiation model in the framework of possibilistic logic. The priority between formulae provides us with important information to decide which beliefs should be discarded. The problem of merging uncertain information from different sources is then solved by two steps. First, beliefs in the original knowledge bases will be weakened to resolve inconsistencies among them. This step is based on a prioritized belief negotiation model. Second, the knowledge bases obtained by the first step are combined using a conjunctive operator which may have a reinforcement effect in possibilistic logic.

Forma y transgresión: el discurso del arte

El arte, en sus diferentes campos, desarrolla un tipo de discurso que nada tiene que ver con el de otros ámbitos. Se vale de combinaciones de elementos diversos, normalmente pertenecientes a lenguajes convencionales, para elaborar un enunciado único y nuevo, donde una idea encuentra finalmente su forma. El contenido y la estructura se fusionan en un punto indisoluble. En este artículo se plantean las búsquedas de paradigmas clásicos de la forma artística y una reflexión al respecto desde el ámbito de las Artes Visuales. Se parte de la consideración que durante muchos siglos se tenía de la representación o imitación de la realidad no solo como vehículo de la expresión sino como la finalidad del arte. Se continua por el foco que la Transgresión de Dadá estableció en aquellas formas artísticas que buscan una conmoción emocional para que la creación alcance los territorios íntimos del receptor. Por último, se explica el fundamental hallazgo de Duchamp de señalar que es el propio discurso de la obra el que proporciona un nuevo pensamiento al mundo.

Feature Selection for Pose Invariant Lip Biometrics

For the first time in this paper the authors present results showing the effect of out of plane speaker head pose variation on a lip biometric based speaker verification system. Using appearance DCT based features, they adopt a Mutual Information analysis technique to highlight the class discriminant DCT components most robust to changes in out of plane pose. Experiments are conducted using the initial phase of a new multi view Audio-Visual database designed for research and development of pose-invariant speech and speaker recognition. They show that verification performance can be improved by substituting higher order horizontal DCT components for vertical, particularly in the case of a train/test pose angle mismatch.

ASR emotional speech: Clarifying the issues and enhancing performance

There are multiple reasons to expect that recognising the verbal content of emotional speech will be a difficult problem, and recognition rates reported in the literature are in fact low. Including information about prosody improves recognition rate for emotions simulated by actors, but its relevance to the freer patterns of spontaneous speech is unproven. This paper shows that recognition rate for spontaneous emotionally coloured speech can be improved by using a language model based on increased representation of emotional utterances. The models are derived by adapting an already existing corpus, the British National Corpus (BNC). An emotional lexicon is used to identify emotionally coloured words, and sentences containing these words are recombined with the BNC to form a corpus with a raised proportion of emotional material. Using a language model based on that technique improves recognition rate by about 20%. (c) 2005 Elsevier Ltd. All rights reserved.

AdaBoost Multiple Feature Selection and Combination for Face Recognition

Gabor features have been recognized as one of the most successful face representations. Encouraged by the results given by this approach, other kind of facial representations based on Steerable Gaussian first order kernels and Harris corner detector are proposed in this paper. In order to reduce the high dimensional feature space, PCA and LDA techniques are employed. Once the features have been extracted, AdaBoost learning algorithm is used to select and combine the most representative features. The experimental results on XM2VTS database show an encouraging recognition rate, showing an important improvement with respect to face descriptors only based on Gabor filters.