The current research is situated on context of teacher support in Virtual Learning Environments (VLE), specifically related to decision-making process. The knowledge about student performance is fundamental to solve pedagogical challenges and to define different ways in teaching and learning. Following this trend, VLE provides extra information by reports, graphs and interface's alert. However, there is demand of statistical tools to support the teacher decisions, because the learning analysis is limited to frequency analysis. This paper discusses an analytical approach to deal with e-learning data. Our focus is to identify groups of learners based on their answers. Therefore, this paper pointed out some main objectives: understand profiles of answers in order to guide a student to future learning activities, and identify which criteria, in each group, is the most relevant for the tutor's help. Several techniques are useful for e-learning issues. However, we focus in Educational Data Mining (EDM) methodology. Our paper selected data of an English e-learning course from PSLC repository for case study in validation step. Preprocessing techniques of EDM were applied on selected dataset. Initially, we removed incomplete, noisy and inconsistent data of sample. After the preprocessing, we executed two steps: clustering and prediction analysis. Firstly, we executed the clustering process, because we needed to identify student's group based on their answers. After understanding the groups, we predicted behaviors of students on each cluster, which were defined in the last step. In our research, it defines that the prediction will use a regression methodology, and the clustering will execute K-means algorithm. The study identified five student's groups based on their answer, such as Expert, Good, Regular, Bad and Criticism answers. Consequently, the prediction analysis defined that the score of tutor's help ("Avg Assistance Score") is the most interesting factor for our investigation. The approach executed the Stepwise Backward Regression, which is a semi-automated process of building a model by successively adding or removing variables based solely on the t-statistics of their estimated coefficients. Thus, other result is that the presence of the variables "Incorrect" and "Correct First Attempts" belongs to three regression models obtained by the approach. This work's findings presents knowledge about answers profiles of VLE students in two main perspectives. First, it analyzes the usage of Open Learning Data to characterize behavioral profiles of answers using multivariate analysis techniques. Second, our analysis contributes to expand present knowledge about how student performance changes the teacher decisions in VLE. This approach tends to be a useful tool in analytical process when the VLE system does not provide statistical tools.
Serious games são jogos computacionais que tem como principal característica ensinar aspectos específicos de disciplinas ou treinar habilidades operacionais e comportamentais. Esses jogos unem a diversão dos videogames convencionais com processos decisórios do jogador, sistemas de avaliação e planejamento pedagógico a fim de criar um ambiente de aprendizado envolvente. Essas características ampliam as possibilidades de atuação desses jogos e, por isso, chamam a atenção de outras áreas do conhecimento. Nesse sentido, merecem destaque os projetos em parceria com os profissionais da Saúde que tem contribuído de forma significativa no treinamento, educação e informação de profissionais e pacientes. Neste contexto da multidisciplinaridade nos serious games que este artigo apresenta uma metodologia utilizada no planejamento de um jogo voltado para mães, com intuito de ensinar e informar sobre conceitos relacionados à saúde bucal de bebês. Esta concepção foi baseada na avaliação da Abordagem de Comunicação, que se refere a uma série de informações importantes na
This work aimed to study a sintered Ni-doped ZnO dilute magnetic semiconductor synthesized by means of a combustion reaction and to evaluate the effect of doping and sintering in the band gap and magnetic properties of the material. X-ray diffraction showed the formation of the ZnO semiconductor phase and also the formation of a second-phase characterized as a solid solution of nickel-zinc oxide. The hysteresis curves showed the success in creating ferromagnetism with doping and the effect of sintering in the remanent magnetization and coercive field values, yet both systems were able to maintain its ferromagnetic behavior. The UV-vis analysis indicated the value of the band gap continued as a semiconductor material, although it has been narrowed. Scanning electron microscopy was used in a complementary way to evaluate the morphology and its effects on magnetic properties.
RESUMO:Os serious games têm se destacado pela adição de aspectos lúdicos ao processo educacional, motivando e auxiliando o aprendizado por meio de jogos. Neste contexto, a inteligência do jogo, composta a partir de modelos de decisão, constitui-se elemento desafiador e motivador do jogador. Para o presente estudo, observou-se que os conceitos básicos relacionados à saúde e higiene bucal predominam nos serious games para Odontologia, e as crianças são o público-alvo principal destes jogos. A carência na exploração da temática saúde bucal em bebês em jogos foi abordada neste trabalho a partir do desenvolvimento de um serious game. A concepção do jogo "Uma Aventura na Floresta da Dentolândia" permitiu verificar a necessidade de considerar a temática e o público-alvo no processo de desenvolvimento de serious games. A pesquisa realizada também permitiu verificar as amplas possibilidades para uso de serious games aplicados à área de saúde.Palavras-chave: jogos, serious games, odontologia, odontopediatria, educação ABSTRACT: The serious games have been highlighted by the addition of playful aspects to the educational process, motivating and assisting learning through games. In this context, the game intelligence, comprised from decision models, consists of challenging and motivating element for
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