DocumentCode :
2242934
Title :
Auto-Adaptive Questions in E-Learning System
Author :
Lazcorreta, Enrique ; Botella, Federico ; Fernández-Caballero, Antonio ; Gascuena, Jose M.
Author_Institution :
Operations Res. Center, Univ. Miguel Hernandez de Elche
fYear :
2006
fDate :
5-7 July 2006
Firstpage :
270
Lastpage :
274
Abstract :
All books entitled "Learn ... with 1000 exercises" have in common the same basic principle. They aim to supply enough material to students so that they may better understand the studied subject, starting from their own practice. If there is no instructor who helps students during the reading of the book, the students will not be able to understand the subject, as the excessive amount of information provided in this kind of books does not enable learners to pursue the learning goals. There is a great boom in e-learning through the so-called intelligent tutoring systems, excellent virtual instructors which guide their learners through the reading of such kinds of books and help their learners to classify all the exercises and recommend them which ones to solve first. Nowadays instructors and teachers are entrusted to produce these books and to classify all exercises, whatever implies an overload to teachers. In this work we introduce a scalable system that only requires teachers to write the questions and their answers. The system will classify and manage all the questions. So the teacher will obtain, with the minimal effort, hundreds of exercises at the end of the course (and for future courses) which will reinforce individually his students
Keywords :
intelligent tutoring systems; auto-adaptive questions; e-learning system; intelligent tutoring systems; virtual instructors; Books; Computer science; Electronic learning; Information retrieval; Intelligent systems; Operations research; Proposals; Rhythm; Technology management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Learning Technologies, 2006. Sixth International Conference on
Conference_Location :
Kerkrade
Print_ISBN :
0-7695-2632-2
Type :
conf
DOI :
10.1109/ICALT.2006.1652422
Filename :
1652422
Link To Document :
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