Optimizing Learning Path Selection through Memetic Algorithms

被引:15
作者
Acampora, Giovanni [1 ]
Gaeta, Matteo [2 ]
Loia, Vincenzo [1 ]
Ritrovato, Pierluigi [2 ]
Salerno, Saverio [2 ]
机构
[1] Univ Salerno, Dipartimento Matemat & Informat, I-84084 Salerno, Italy
[2] Univ Salerno, Dipartimento Ingn Informaz Matemat Appl, I-84084 Salerno, Italy
来源
2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8 | 2008年
关键词
D O I
10.1109/IJCNN.2008.4634354
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
e-Learning is a critical support mechanism for industrial and academic organizations to enhance the skills of employees and students and, consequently, the overall competitiveness in the new economy. The remarkable velocity and volatility of modern knowledge require novel learning methods offering additional features as efficiency, task relevance and personalization. The main aim of adaptive e-Learning is to support content and activities, personalized to specific needs and influenced by specific preferences of the learner. This paper describes a collection of models and processes for adapting an e-Learning system to the learner expectations and to formulate objectives in a dynamic intelligent way. Precisely, our proposal exploits ontological representations of learning environment and a memetic optimization algorithm capable of generating the best learning presentation in an efficient and qualitative way.
引用
收藏
页码:3869 / +
页数:2
相关论文
共 15 条
[1]  
ACAMPORA G, 2007, P IEEE INT C EV COMP
[2]  
ALBANO G, 2007, J KNOWLEDGE LEARNING, V3, P209
[3]   E-learning: a model and process proposal [J].
Albano, Giovannina ;
Gaeta, Matteo ;
Salerno, Saverio .
INTERNATIONAL JOURNAL OF KNOWLEDGE AND LEARNING, 2006, 2 (1-2) :73-88
[4]  
ALEXAKOS CE, 2006, INTEGRATING E LEARNI, V13
[5]  
[Anonymous], 1989, 826 CALTECH
[6]  
CHEN W, P 6 INT C COMP ED, P41
[7]  
CRAMPES M, 2000, P 11 ACM HYP HYP, P191
[8]  
Dawkins R., 2016, SELFISH GENE
[9]  
Eklund J., 2003, E LEARNING EMERGING
[10]  
El Alami N, 2007, LECT NOTES ARTIF INT, V4693, P58