TCC - Bacharelado em Sistemas da Informação (Sede)
URI permanente para esta coleçãohttps://arandu.ufrpe.br/handle/123456789/427
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Item A utilização de Game Learning Analytics em um Serious Game voltado ao turismo(2020-11-05) Spinelli, Christian Rabelo do Nascimento; Cysneiros Filho, Gilberto Amado de Azevedo; http://lattes.cnpq.br/0534822491953359; http://lattes.cnpq.br/7006082986551649The digital games market has been consolidating in Brazil and its capacity to capture the attention of players allows games to be used educationally, with the development of Serious Games . Serious Games are games that are not only intended to entertain, but also to teach the player, including with regard to tourism. It aims to teach characteristics and customs of places for its inhabitants and tourists. The purpose of Game Learning Analytics is to gather information and analyze data from Serious Games for the purpose of improving its functionality and measuring learning. There are several ways to apply Game Learning Analytics to Serious Games and one of these ways is to use quizzes and mini games in parallel with the main game, within which approach the player should have a main mission in the game that encourages him to play and get resources to progress in the game as a result of having access to the learning mechanisms. From this approach, this article will describe the development of a Serious Games focused on tourism using Game Learning Analytics.Item Planejador de roteiros turísticos: uma aplicação do Problema do Caixeiro Viajante na cidade do Recife(2018) Bispo, Rodolfo César; Cysneiros Filho, Gilberto Amado de Azevedo; http://lattes.cnpq.br/0534822491953359A mobile application (proof of concept) has been developed providing route recommendations for tourists visiting Recife by walking. The tourist selects the points of interest (POI) he wants to visit and the application recommends a route. The tourist can choose the points of interest from a list of points and view them on a map. The application also provides detailed information on points of interest to aid in the choice. Three algorithms were implemented to recommend the route. The algorithms were compared in terms of execution time, impact on the total length of the route generated, memory and CPU usage. The Brute Force algorithm presented a skillful execution time in up to 8 chosen points. Nearest Neighbor moved away more and more of the optimal solution as the number of points increased,while its combination with 2-OPT resulted in an optimization of up to 50 minutes in the route duration.