Cristiano Grijó Pitangui

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This paper presents, for discrete data, a new crossover operator to be used together with the Natural Coding. This new operator, differently of the already existing one, beyond possessing high speed of application, explores the search space in the same way that the crossover operator used when the binary representation is adopted. Additionally, this work(More)
The evolution of distance education was by the popularization of information and communication technologies, the most important aspect in a Adaptive and Intelligent System for Education, is its ability to adapt to the characteristics of each student. This paper presents a proposal for automatic detection and correction of learning styles (EA) using an(More)
One of the current challenges is to develop computational technologies that are able to respond properly to the teaching and learning methods. For this to occur, it is essential that virtual environments provide adequate content, and are dynamic and adaptable to the needs and interests of students. This papper proposes a probabilistic approach, combines the(More)
This paper aims to make a comparative study of new approaches to automatic and dynamic modeling of learning styles in adaptive and intelligent educational systems. We proposes modifications to the Student and Pedagogical Models. We achieved on average an improvement 6.1 % in the performance evaluation of the student and an average reduction of 68.3 % in the(More)
The academic performance prediction can be very useful for Educational Institutions in order to help them to take pedagogical decisions that can help students. In this work, we present experiments using Moodle data, Time Series and the Feature Selection Wrapper approach, since, to best of our knowledge, this method to reduce the number of features have not(More)
This paper presents an analysis and survey of publications in the field of Educational Data Mining published by several researchers at events and journals in the period from 2011 to 2016. The purpose of this research is to identify and present what is being researched in performance prediction area using mining relationships and clustering. The work(More)