Interface gráfica no contexto de teoria dos jogos sob a forma de Java Apples

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Media Education and Brazilian Educational Policies for the Enhancement of Learning

As media education concepts and practices have been disseminated and strengthened in European countries and Americas, the policies responsible for that expansion remain little known, particularly in countries where the achievements have been recently noted. That is the case for Brazil, where there have been new opportunities for media education, considered as a valuable resource to help accomplish goals of the educational system. This paper looks into the contribution of media education to the enhancement of teaching and learning in the context of innovations brought by recent policies of the Brazilian Ministry of Education. After educational reform programmes which brought the opportunity for emerging fields such as media education, we produced teaching material and conducted a series of workshops with students and teachers from state secondary schools. By reading and producing multimedia information about local public services available to young people, pupils learned about democracy, citizenship, civic engagement, media language, and identity. Lessons from our experiment are discussed against the backdrop of education policies being implemented to ameliorate harsh conditions resulting from the recent economic crisis. We suggest that media education can help by creating a learning environment in which the students become aware of the value of educational attainments.

The Acting in Group of Teachers as Possibility of Resignification of the Interpretation about the Writing Language

Front of the possibility of acting with the teachers who teach in schools of Early Childhood Education for children aged six years, about the re-siginification of the understanding of writing language and of the importance of the child in this age group establish a positive relationship with this mode of language, was developed in 2011, a project linked to the Teaching of UNESP titled “Depathologization learning of the writing and inclusive education: reflections and actions of the teacher of Early Childhood Education”. This project aims to identification of the actions, in the classroom, of the patologization and subsequent implementation of actions depathologization writing by teachers’ actions, considering the increasingly early systematization of formal education of this kind of language in kindergarten. To this end, procedures that characterize the collaborative methodology are adopted. Throughout the methodological course, the engagement of the teachers, of the coordination and of the direction was valued, which seemed to favor both the formation, as the maintenance of the group, were very important aspects to ensure the interaction between its members and the common interest in the reflection about the topic in question. This paper focuses attention on whether thematic axes highlight during the initial survey of the expectations of teachers subsequently addressed in theoretical and reflective meetings leading up to identification of actions the patologization and/or of the proposition of the actions despatologizadoras of the learning of the writing, and in what refers to the way they are addressed.

Deep learning architecture for gesture recognition

Pós-graduação em Engenharia Mecânica - FEG

Combined active and semi-supervised learning using particle walking temporal dynamicscombined active and semi-supervised learning using particle walking temporal dynamics

Both Semi-Supervised Leaning and Active Learning are techniques used when unlabeled data is abundant, but the process of labeling them is expensive and/or time consuming. In this paper, those two machine learning techniques are combined into a single nature-inspired method. It features particles walking on a network built from the data set, using a unique random-greedy rule to select neighbors to visit. The particles, which have both competitive and cooperative behavior, are created on the network as the result of label queries. They may be created as the algorithm executes and only nodes affected by the new particles have to be updated. Therefore, it saves execution time compared to traditional active learning frameworks, in which the learning algorithm has to be executed several times. The data items to be queried are select based on information extracted from the nodes and particles temporal dynamics. Two different rules for queries are explored in this paper, one of them is based on querying by uncertainty approaches and the other is based on data and labeled nodes distribution. Each of them may perform better than the other according to some data sets peculiarities. Experimental results on some real-world data sets are provided, and the proposed method outperforms the semi-supervised learning method, from which it is derived, in all of them.

ARBOT: augmented reality system for teaching logic algorithmic

This article purposes the ARBot, a system that has as main objective the presentation of concepts of logic for students of elementary and secondary education. The system was developed using the technology known as Augmented Reality (AR), which allows complement the actual environment where the user is, by adding virtual objects. In this scenario the RA created from a virtual game interface is used, through which cognitive challenges are presented. To solve these challenges, users must set up three-dimensional virtual characters using visual language. As a result it follows that, in a playful way, concepts of algorithms and programming are assimilated by users. In addition, the system enables two users to interact in a cooperative game mode. In cooperative mode, the system focuses on collaborative learning, since it allows users to jointly solve the cognitive challenge presented by the system.

Writing Motivation of Students with Specific Language Impairments

This study was designed to compare the writing motivation of students with specific language impairments with their non-disabled peers. Due to the cognitive and linguistic demands of the writing process, students with language impairments face unique difficulties during the writing process. It was hypothesized that students with specific language impairments will be more likely to report lower levels of perceived writing competence and be less autonomously motivated to write. Students in grades 3-5 in 11 schools (33 with specific language impairments, 242 non-disabled peers) completed self-report measures, designed from a Self-Determination Theory perspective, which measured the degree that students are intrinsically motivated to write as well as their perceived writing competence. Statistical analyses showed that (1) students with specific language impairments reported lower levels of perceived writing competence and autonomous writing motivation; (2) SLI status was a significant predictor of perceived writing competence after spelling, grade, and gender were controlled; and (3) when spelling, grade, and gender were controlled, perceived writing competence was a significant predictor of autonomous writing motivation, but SLI status was not. The results of this study are expected to inform the current understanding of the relationship between language ability and writing motivation in students with specific language impairments, as well as the design of future writing interventions.

Critical behavior in a cross-situational lexicon learning scenario

The associationist account for early word learning is based on the co-occurrence between referents and words. Here we introduce a noisy cross-situational learning scenario in which the referent of the uttered word is eliminated from the context with probability gamma, thus modeling the noise produced by out-of-context words. We examine the performance of a simple associative learning algorithm and find a critical value of the noise parameter gamma(c) above which learning is impossible. We use finite-size scaling to show that the sharpness of the transition persists across a region of order tau(-1/2) about gamma(c), where tau is the number of learning trials, as well as to obtain the learning error (scaling function) in the critical region. In addition, we show that the distribution of durations of periods when the learning error is zero is a power law with exponent -3/2 at the critical point. Copyright (C) EPLA, 2012

Word sense disambiguation via high order of learning in complex networks

Complex networks have been employed to model many real systems and as a modeling tool in a myriad of applications. In this paper, we use the framework of complex networks to the problem of supervised classification in the word disambiguation task, which consists in deriving a function from the supervised (or labeled) training data of ambiguous words. Traditional supervised data classification takes into account only topological or physical features of the input data. On the other hand, the human (animal) brain performs both low- and high-level orders of learning and it has facility to identify patterns according to the semantic meaning of the input data. In this paper, we apply a hybrid technique which encompasses both types of learning in the field of word sense disambiguation and show that the high-level order of learning can really improve the accuracy rate of the model. This evidence serves to demonstrate that the internal structures formed by the words do present patterns that, generally, cannot be correctly unveiled by only traditional techniques. Finally, we exhibit the behavior of the model for different weights of the low- and high-level classifiers by plotting decision boundaries. This study helps one to better understand the effectiveness of the model. Copyright (C) EPLA, 2012

The place of (explicit) grammar within the methods and approaches of foreign language teaching: in the north, in the centre or on the margins?

This article analyzes the role that has been attributed to grammar throughout the history of foreign language teaching, with special emphasis on methods and approaches of the twentieth century. In order to support our argument, we discuss the notion of grammar by proposing a conceptual continuum that includes the main meanings of the term which are relevant to our research. We address as well the issue of "pedagogical grammar" and consider the position of grammar in the different approaches of the "era of the methods" and the current "post-method condition" in the field of language teaching and learning. The findings presented at the end of the text consist of recognizing the central role that grammar has played throughout the history of the methods and approaches, where grammar has always been present by the definition of the contents' progression. The rationale that we propose for this is the recognition of the fact that the dissociation between what is said and how it is said can not be more than theoretical and, thus, artificial.

Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.

Investigation of auditory processing disorder and language impairment using the speech-evoked auditory brainstem response

This study investigated whether there are differences in the Speech-Evoked Auditory Brainstem Response among children with Typical Development (TD), (Central) Auditory Processing Disorder (C) APD, and Language Impairment (LI). The speech-evoked Auditory Brainstem Response was tested in 57 children (ages 6-12). The children were placed into three groups: TD (n = 18), (C)APD (n = 18) and LI (n = 21). Speech-evoked ABR were elicited using the five-formant syllable/da/. Three dimensions were defined for analysis, including timing, harmonics, and pitch. A comparative analysis of the responses between the typical development children and children with (C)APD and LI revealed abnormal encoding of the speech acoustic features that are characteristics of speech perception in children with (C)APD and LI, although the two groups differed in their abnormalities. While the children with (C)APD might had a greater difficulty distinguishing stimuli based on timing cues, the children with LI had the additional difficulty of distinguishing speech harmonics, which are important to the identification of speech sounds. These data suggested that an inefficient representation of crucial components of speech sounds may contribute to the difficulties with language processing found in children with LI. Furthermore, these findings may indicate that the neural processes mediated by the auditory brainstem differ among children with auditory processing and speech-language disorders. (C) 2012 Elsevier B.V. All rights reserved.

Network-based stochastic semisupervised learning

Semisupervised learning is a machine learning approach that is able to employ both labeled and unlabeled samples in the training process. In this paper, we propose a semisupervised data classification model based on a combined random-preferential walk of particles in a network (graph) constructed from the input dataset. The particles of the same class cooperate among themselves, while the particles of different classes compete with each other to propagate class labels to the whole network. A rigorous model definition is provided via a nonlinear stochastic dynamical system and a mathematical analysis of its behavior is carried out. A numerical validation presented in this paper confirms the theoretical predictions. An interesting feature brought by the competitive-cooperative mechanism is that the proposed model can achieve good classification rates while exhibiting low computational complexity order in comparison to other network-based semisupervised algorithms. Computer simulations conducted on synthetic and real-world datasets reveal the effectiveness of the model.

Computer game-based and traditional learning method: a comparison regarding students’ knowledge retention

Abstract Background Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Methods Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students’ prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students’ performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Results Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. Conclusions The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students’ short and long-term knowledge retention.

Interactive application in spanish sign language for a public transport environment

[ES] En este trabajo se presenta el diseño de una herramienta multimedia que traduce a la lengua de signos españolas los mensajes de avisos que puede proporcionar un sistema de megafonía. El objetivo del trabajo es proporcionar una herramienta que mejore la inclusión social de las personas con discapacidades auditivas. Con este propósito, se han seleccionado el entorno y los mensajes de audio habituales en un aeropuerto para desarrollar este proyecto piloto. Por último, los audios se han traducido a lengua de signos españolas sintetizando un avatar usando la técnica de animación de rotoscopía a partir de la grabación en vídeo de un traductor. Los resultados finales han sido evaluados por personas sordas.