Uso de sistemas tutores inteligentes na compreensão de leitura

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Data

2009-11-28

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Universidade Federal de Goiás

Resumo

Brazilian students have achieved poor results in the National Student Performance Exam (ENADE) in 2006. ENADE has shown reading is badly cultivated among undergraduates. The low interest on reading is justified by the fact that most of students have jobs and are enrolled in evening courses, without enough time to studies. The current research proposes the use of intelligent tutoring systems to improve student reading comprehension. The main goal is to develop the technique of underlining among undergraduates to assist in the analysis of academic texts. Two groups of students, A and B, participated in data collection. The difference between the groups is the amount of exercises performed in each group. Students of Group A have received 20 exercises with four levels of difficulty. In Group B, an Artificial Neural Network, Multilayer Perceptron (MLP), decides the amount of exercises that the student must perform at each level of difficulty by controlling what is the next exercise after each exercise is finished. The approach used in Group B adapts to the characteristics of knowledge retention of each student. Therefore, the tutoring system adapts the degree of exercise difficulty to the student. Statistical data analysis has indicated significant differences between groups A and B.

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Citação

BORGES, Fabrícia Neres. Intelligent tutoring systems in reading comprehension. 2009. 93 f. Dissertação (Mestrado em Engenharia) - Universidade Federal de Goiás, Goiânia, 2009.