Formação continuada e inclusão escolar de alunos com deficiência: concepções, sentimentos e práticas de educadores da rede municipal de ensino de Presidente Prudente-SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Autenticação biométrica de usuários em sistemas de E-learning baseada em reconhecimento de faces a partir de vídeo

Pós-graduação em Ciência da Computação - IBILCE

Ensino de gestão da capacidade e da empresa com o apoio do jogo Mercado Virtual no curso de Mestrado Integrado em Engenharia Industrial e Gestão da UMINHO/Azurém e no Programa de Pós-Graduação em Engenharia de Produção da FEB/Bauru/UNESP

O jogo de empresas Mercado Virtual foi desenvolvido para mediar o processo ensino-aprendizagem na área de tomada decisão e gestão de empresas e tem um banco de dados que armazena as decisões dos alunos. Os dados nele armazenados foram analisados em relação ao balanceamento de capacidade, objetivo de lucro e uso de recursos financeiros da empresa e foram encontradas incoerências entre os conteúdos pertinentes ao modelo e as decisões dos alunos. Elas foram classificadas como lacunas de aprendizado. Com o objetivo de analisar se as mesmas se repetem entre alunos do Programa de Mestrado Engenharia de Produção da UNESP de Bauru e Mestrado Integrado em Engenharia Industrial e Gestão da Uminho de Guimarães, Portugal, foram realizados dois experimentos, um em cada grupo. Para realizá-los utilizou-se o jogo Mercado Virtual e uma planilha de dimensionamento da empresa nos dois locais. A Sala de Estudos, os indicadores e o questionário de pesquisa da opinião foram utilizados somente em Portugal. Os resultados mostraram que o jogo é capaz de evidenciar as diferenças de domínio de conteúdo nos dois grupos e, também, que estas diferenças estão associadas aos projetos dos cursos. Sendo uma pesquisa exploratória, os experimentos foram realizados considerando-se somente os controles do jogo. Por isso, propõe-se a realização de pesquisas adicionais combinando controle sobre algumas das variáveis relacionadas do uso do jogo e atuação sobre aprendizagem dos alunos na forma de entrevistas e pesquisas não estruturadas. Conforme previsto, a pesquisa mostrou que os jogos podem ser utilizados com objetivos de aprendizagem mais amplos, considerando-se a avaliação indireta e cruzada sobre as decisões tomadas pelos alunos, como é o caso dos indicadores. Outra contribuição importante da pesquisa refere-se ao uso de jogos de empresas sob condições pouco controladas, ou seja, não houve...

Objetos de Aprendizagem como recurso pedagógico em contextos inclusivos: subsídios para a formação de professores a distância

This article aims to contribute to the process of inclusion of students with disabilities in regular schools by reporting the results of a survey that aimed to verify whether Learning Objects (LO) are efficient tools in constructing teaching and learning of subject content within the inclusive education context. Participant, tutor and trainer experiences of a distance learning Ministry of Education (MEC) course on Assistive Technology were analyzed. The course was offered to public schools teachers from all over the country. The course activities were recorded in a Virtual Learning Environment (VLE) called TelEduc, along with group reports of course participants. Three categories were selected for data analysis: a) interactivity and feedback from the team trainer; b) applicability of the content covered in the course, and c) new learning. The results showed that LO can promote the learning of subject content. Having been designed as educational resources to support teaching and learning, they can enhance educational inclusion of people with disabilities. As for the process of distance formation for teachers, the course contributed to consolidating sound and efficient training of participants by providing: a closer encounter with the world of technology, the possibility of integration of technology in the classroom; conducting theoretical and practical studies, appreciation of diversity and all students' potential; innovations in strategies and learning resources and reflective action.

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.

Atendimento Educacional Especializado: análise do índice de evasão de professores em curso de pós-graduação, na modalidade a distância

This research aims to investigate the possible causes for the dropout of participants under instruction in distance courses. Data gathered from the Specialization Course in Specialized Educational Support Services - SES, sponsored by the Department for Continuing Education, Literacy and Diversity of the Ministry of Education - SECAD / MEC - and the Open University of Brazil – OUB, will be analyzed. The objective of the course is to graduate teachers who work in classrooms equipped with multifunctional resources in regular schools to give specialized educational support for students with special educational needs marked by disabilities, global development disorders and high abilities/highly gifted students. In order to analyze dropout data in the first semester of the ongoing course, a sample of 1349 participants enrolled in the distance course was considered; 216 of these had their enrollment cancelled on request or because they stopped accessing the Virtual Learning Environment - VLE / Teleduc Platform showing no interest in the course. However, the information below aims to present and discuss only the tabulated data of the 98 participants who requested to have their enrollment officially cancelled by submitting the online dropout term. The findings showed the main reasons for dropping out were personal problems, lack of time to commit to an ongoing distance course, difficulty using ICT and the tools available in the VLE. The research also highlighted the importance of developing digital inclusion initiatives as well as on-site supporting poles as a way to soften the barriers of technological accessibility and the dropout rate in this kind of courses.

Luz, câmera, flashes: uma compreensão sobre a disciplina de prática de ensino de matemática a distância

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Curso de capacitação para líderes, voluntários, profissionais e gestores de comunidades terapêuticas: o conhecimento em relação ao álcool, crack e outras drogas

Pós-graduação em Saúde Coletiva - FMB

Um estudo sobre as possíveis causas de evasão no curso de Licenciatura em Pedagogia da UAB – UFSCAR em um Polo Presencial do Interior Paulista: percepção dos alunos

Pós-graduação em Educação Escolar - FCLAR

The Effects Improving Student Discourse Has on Learning Mathematics

In this action research study of my 8th grade mathematics classroom, I investigated how improving student discourse affects learning mathematics. I conducted this study because I wanted to give students more opportunities to develop and share their ideas with their peers as well as with me. My idea was to create a learning environment that encouraged students to voice their opinions. In order to do so, I needed to reassure and model with my students that they were in a classroom where it was safe to take risks, and they should feel comfortable sharing their ideas. By facilitating activities for students to complete in groups, asking students to prepare work to share with the class, and offering more opportunities for students to work with each other on discovering and exploring math skills being presented, I set the tone for abundant student discourse to take place in the mathematics classroom. I discovered that students became more comfortable with math skills the more opportunities they had to discuss the ideas in various settings. I also found that as the study went on, students discovered the importance of being able to share their mathematical ideas and valued the ability to verbalize their thoughts with others. As a result of this study, I plan to continue offering many opportunities for students to work in groups as well as to share their ideas with the class.

Awareness of Daylighting on Student Learning in an Educational Facility

This study examines how awareness of the interior architecture of a building, specifically daylighing, affects students academic performance. Extensive research has proven that the use of daylighting in a classroom can significantly enhance students’ academic success. The problem statement and purpose of this study is to determine if student awareness of daylighting in their learning environment affects academic performance compared to students with no knowledge of daylighting. Research and surveys in existing and newly constructed high schools were conducted to verify the results of this study. These design ideas and concepts could influence the architecture and design industry to advocate construction and building requirements that incorporate more sustainable design teaching techniques.

THE VIRTUAL ENVIRONMENT OF A RESEARCH GROUP: THE TUTORS' PERSPECTIVE

The Grupo de Estudos e Pesquisas de Tecnologia da Informacao nos Processos de Trabalho em Enfermagem (Study and Research Group for Information Technology in the Nursing Working Processes, GEPETE) has the purpose of producing and socializing knowledge in information technology and health and nursing communication, making associations with research groups in this field and promoting student participation. This study was performed by the group tutors with the objective to report on the development of the virtual learning environment (VLE) and the tutors' experience as mediators of a research group using the Moodle platform. To do this, a VLE was developed and pedagogical mediation was performed following the theme of mentoring. An initial diagnosis was made of the difficulties in using this technology in interaction and communication, which permitted the proposal of continuing to use the platform as a resource to support research activities, offer lead researchers the mechanisms to socialize projects and offer the possibility of giving advice at a distance.

Reinforcement Lernen mit Regularisierungsnetzwerken

Die Arbeit behandelt das Problem der Skalierbarkeit von Reinforcement Lernen auf hochdimensionale und komplexe Aufgabenstellungen. Unter Reinforcement Lernen versteht man dabei eine auf approximativem Dynamischen Programmieren basierende Klasse von Lernverfahren, die speziell Anwendung in der Künstlichen Intelligenz findet und zur autonomen Steuerung simulierter Agenten oder realer Hardwareroboter in dynamischen und unwägbaren Umwelten genutzt werden kann. Dazu wird mittels Regression aus Stichproben eine Funktion bestimmt, die die Lösung einer "Optimalitätsgleichung" (Bellman) ist und aus der sich näherungsweise optimale Entscheidungen ableiten lassen. Eine große Hürde stellt dabei die Dimensionalität des Zustandsraums dar, die häufig hoch und daher traditionellen gitterbasierten Approximationsverfahren wenig zugänglich ist. Das Ziel dieser Arbeit ist es, Reinforcement Lernen durch nichtparametrisierte Funktionsapproximation (genauer, Regularisierungsnetze) auf -- im Prinzip beliebig -- hochdimensionale Probleme anwendbar zu machen. Regularisierungsnetze sind eine Verallgemeinerung von gewöhnlichen Basisfunktionsnetzen, die die gesuchte Lösung durch die Daten parametrisieren, wodurch die explizite Wahl von Knoten/Basisfunktionen entfällt und so bei hochdimensionalen Eingaben der "Fluch der Dimension" umgangen werden kann. Gleichzeitig sind Regularisierungsnetze aber auch lineare Approximatoren, die technisch einfach handhabbar sind und für die die bestehenden Konvergenzaussagen von Reinforcement Lernen Gültigkeit behalten (anders als etwa bei Feed-Forward Neuronalen Netzen). Allen diesen theoretischen Vorteilen gegenüber steht allerdings ein sehr praktisches Problem: der Rechenaufwand bei der Verwendung von Regularisierungsnetzen skaliert von Natur aus wie O(n**3), wobei n die Anzahl der Daten ist. Das ist besonders deswegen problematisch, weil bei Reinforcement Lernen der Lernprozeß online erfolgt -- die Stichproben werden von einem Agenten/Roboter erzeugt, während er mit der Umwelt interagiert. Anpassungen an der Lösung müssen daher sofort und mit wenig Rechenaufwand vorgenommen werden. Der Beitrag dieser Arbeit gliedert sich daher in zwei Teile: Im ersten Teil der Arbeit formulieren wir für Regularisierungsnetze einen effizienten Lernalgorithmus zum Lösen allgemeiner Regressionsaufgaben, der speziell auf die Anforderungen von Online-Lernen zugeschnitten ist. Unser Ansatz basiert auf der Vorgehensweise von Recursive Least-Squares, kann aber mit konstantem Zeitaufwand nicht nur neue Daten sondern auch neue Basisfunktionen in das bestehende Modell einfügen. Ermöglicht wird das durch die "Subset of Regressors" Approximation, wodurch der Kern durch eine stark reduzierte Auswahl von Trainingsdaten approximiert wird, und einer gierigen Auswahlwahlprozedur, die diese Basiselemente direkt aus dem Datenstrom zur Laufzeit selektiert. Im zweiten Teil übertragen wir diesen Algorithmus auf approximative Politik-Evaluation mittels Least-Squares basiertem Temporal-Difference Lernen, und integrieren diesen Baustein in ein Gesamtsystem zum autonomen Lernen von optimalem Verhalten. Insgesamt entwickeln wir ein in hohem Maße dateneffizientes Verfahren, das insbesondere für Lernprobleme aus der Robotik mit kontinuierlichen und hochdimensionalen Zustandsräumen sowie stochastischen Zustandsübergängen geeignet ist. Dabei sind wir nicht auf ein Modell der Umwelt angewiesen, arbeiten weitestgehend unabhängig von der Dimension des Zustandsraums, erzielen Konvergenz bereits mit relativ wenigen Agent-Umwelt Interaktionen, und können dank des effizienten Online-Algorithmus auch im Kontext zeitkritischer Echtzeitanwendungen operieren. Wir demonstrieren die Leistungsfähigkeit unseres Ansatzes anhand von zwei realistischen und komplexen Anwendungsbeispielen: dem Problem RoboCup-Keepaway, sowie der Steuerung eines (simulierten) Oktopus-Tentakels.