Software process modeling (SPM) is an important area of software engineering because it provides a basis for managing, automating, and supporting software process improvement (SPI). Teaching SPM is a challenging task, mainly because it lays great emphasis on theory and offers few practical exercises. Furthermore, as yet few teaching approaches have aimed at teaching SPM by introducing innovative features, such as games. The use of games has mainly been focused on other areas of software engineering, for example software project management. In an attempt to fill this gap, this paper describes a formal experiment carried out to assess the learning effectiveness of a serious game (DesigMPS), designed to support the teaching of SPM, and to compare game-based learning with a project-based learning method. In the DesigMPS game, the student models a software process from an SPI perspective, based on the Brazilian SPI model (MPS.BR). The results indicate that playing the game can have a positive learning effect and results in a greater degree of learning effectiveness than does the project-based learning instructional method.Index Terms-Project-based learning, serious game, software engineering education, software process modeling. software process, software quality, project management, CASE tools, software development environment and information systems.

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Develop new games without having to start from scratch has been made possible by using game engines, since they offer a number of specialized components and optimized functions which are common in games. However, one realizes that process simulation games have not taken advantage of these technologies. This paper aims to demonstrate the results of the development of a software process simulation component called Software Process Simulator Machine (SPSM), which focuses on help and motivate software process educational game development through the addressing of main generic requirements for process simulation software.

This paper presents research of an application of a latent semantic analysis (LSA) model for the automatic evaluation of short answers (25 to 70 words) to open-ended questions. In order to reach a viable application of this LSA model, the research goals were as follows: (1) to develop robustness, (2) to increase accuracy, and (3) to widen portability. The methods consisted of the following tasks: firstly, the implementation of word bigrams; secondly, the implementation of combined models of unigrams and bigrams using multiple linear regression; and, finally, the addition of an adjustment step after the score attribution taking into consideration the average of the words of the answers. The corpus was composed by 359 answers produced according to two questions from a Brazilian public university's entrance examination, which were previously scored by human evaluators. The results demonstrate that the experiments produced accuracy about 84.94 %, while the accuracy of the two human evaluators was about 84.93 %. In conclusion, it can be seen that the automatic evaluation technology shows that it is reaching a high level of efficiency.

A idéia por trás da atividade experimental é permitir aos estudantes atingirem uma maior autonomia intelectual. Para isso, o estudante deve perceber a importância do refletir após o fazer. Esse artigo discute o problema e propõe um sistema, que pode ser incorporado a Ambientes Virtuais de Aprendizagem para gerenciar as atividades apoiadas por esses ambientes. O sistema proposto permite definir processos do tipo “padrão” om atividades que são “instanciadas” para os cursos e conta também conta com uma ferramenta de avaliação automática de textos, que fornece, para o professor, indicadores que podem ser usados para agilizar o feedback para os estudantes.