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Since its inception, Vehicular Ad hoc Networks (VANETs) have been attracting much attention from both academia and industry. As for other wireless networking areas, scientific advancements are mainly due to the employment of simulation tools and mathematical models. After surveying 283 papers published in the last decade on vehicular networking, we pinpoint the main studied topics as well the most employed tools, pointing out the changes in research subject preference over the years. As a key contribution, we also evaluate to what extent the research community has evolved concerning the principles of credibility in simulation-based studies, such as repeatability and replicability, comparing our results with previous studies.

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In this paper we propose a set of mobility metrics, which are employed in the generation of supervised classification learning methods through the decision tree algorithm, with the goal to recognize user movement patterns in mobile ad hoc networks. Hundreds of scenarios produced by several well-known mobility models were employed for training and testing the supervised algorithms. The most suitable classification model showed an accuracy of 99.20 % and Kappa index of 0.991, which indicates a high level of agreement between the classification model and real classification.

To minimize difficulties in programming learning, new pedagogical strategies were proposed. Robomind is an example, this educational software promotes learning through play. This study aims to provide statistical evidence about the pedagogical effectivity of this tool, through an experiment with 65 students from technical high school. Statistical test did not found significant result (p-value <0.05) in the learning outcomes among the group of students exposed to the intervention with Robomind and the non-intervention group. Effect size calculation resulted in r = 0.08. On the other hand, the tool proved to be adequate to avoid student evasion.Resumo. Com o objetivo de minimizar as dificuldades no processo de ensino e aprendizagem de programação, novas estratégias pedagógicas foram propostas. O Robomindé um exemplo, esse software educacional promove o aprendizado por meio do lúdico. Este trabalho busca oferecer evidências estatísticas sobre a efetividade dessa ferramenta, por meio de um experimento com 65 estudantes do ensino técnico integrado ao ensino médio. Os cálculos estatísticos não identificaram diferenças, estatisticamente significantes (p-value <0.05), nos resultados de aprendizado entre o grupo de estudantes expostosà intervenção com o Robomind e o grupo sem intervenção. O cálculo do tamanho de efeito resultou em um r = 0.08. Por outro lado, a ferramenta se mostrou adequada para minimizar evasões dos estudantes.