Title :
Selection and sequencing constraints for personalized courses
Author :
Sterbini, Andrea ; Temperini, Marco
Author_Institution :
Univ. of Roma La Sapienza, Rome, Italy
Abstract :
The LECOMPS framework, for personalized and adaptive e-learning, is recalled. Its enhancements, regarding the selection and sequencing optimization algorithms that can be applied, are shown. Such enhancements are discussed, both in terms of their implementation and with respect to their effectiveness: basing on a stated learner´s model (the present state of knowledge, and learning styles of the individual learner), and on a definition of course aims (Target Knowledge), we apply the various selection and sequencing algorithms and compare the results; different courses are produced, corresponding to different personalization requirements, that can possibly occur, also in combination.
Keywords :
computer aided instruction; educational courses; learning (artificial intelligence); adaptive e-learning; constraint selection; constraint sequencing; learner model; learning objective; learning style; optimization algorithm; personalized course; Adaptation model; Algorithm design and analysis; Conferences; Context; Electronic learning; Optimization; Sorting; Adaptive e-learning; Learning Objectives; Learning Objects Sequencing Algorithms;
Conference_Titel :
Frontiers in Education Conference (FIE), 2010 IEEE
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4244-6261-2
Electronic_ISBN :
0190-5848
DOI :
10.1109/FIE.2010.5673146
