3 resultados para clusterizing of learning activities

em Universidade do Minho


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Dissertação de mestrado integrado em Psicologia

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The health industry has always used natural products as a rich, promising, and alternative source of drugs that are used in the health system. Propolis, a natural resinous product known for centuries, is a complex product obtained by honey bees from substances collected from parts of different plants, buds, and exudates in different geographic areas. Propolis has been attracting scientific attention since it has many biological and pharmacological properties, which are related to its chemical composition. Several in vitro and in vivo studies have been performed to characterize and understand the diverse bioactivities of propolis and its isolated compounds, as well as to evaluate and validate its potential. Yet, there is a lack of information concerning clinical effectiveness. The goal of this review is to discuss the potential of propolis for the development of new drugs by presenting published data concerning the chemical composition and the biological properties of this natural compound from different geographic origins.

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Forming suitable learning groups is one of the factors that determine the efficiency of collaborative learning activities. However, only a few studies were carried out to address this problem in the mobile learning environments. In this paper, we propose a new approach for an automatic, customized, and dynamic group formation in Mobile Computer Supported Collaborative Learning (MCSCL) contexts. The proposed solution is based on the combination of three types of grouping criteria: learner’s personal characteristics, learner’s behaviours, and context information. The instructors can freely select the type, the number, and the weight of grouping criteria, together with other settings such as the number, the size, and the type of learning groups (homogeneous or heterogeneous). Apart from a grouping mechanism, the proposed approach represents a flexible tool to control each learner, and to manage the learning processes from the beginning to the end of collaborative learning activities. In order to evaluate the quality of the implemented group formation algorithm, we compare its Average Intra-cluster Distance (AID) with the one of a random group formation method. The results show a higher effectiveness of the proposed algorithm in forming homogenous and heterogeneous groups compared to the random method.