"Adaptive and intelligent e-learning systems: how to improve learning process by using intelligent hypermedia networks" Presentation at ITEA-2013, IRTC, Kyiv, Ukraine http://itea-conf.org.ua/2013/

1. ADAPTIVE AND INTELLIGENT ELEARNING SYSTEMS: HOW TO
IMPROVE LEARNING PROCESS
BY USING INTELLIGENT
HYPERMEDIA NETWORKS
Armando Benito, Juan Ramón
Fernández, Julián González, Juan José
Prieto
Tecnalia Research & Innovation, Madrid,
Spain
15 November 2013

2. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS
Content
• Objectives
• System Architecture
• Domain Server Architecture
• Inter - Domain Server Architecture
• Algorithms and techniques
• Uses Cases
•ENAMIA
• ALZHERAPHY
• E -Learning Courses
• Conclusions
• Acknowledgements

3. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS
Objectives
• Adaptive and intelligent e-learning systems
• Improve learning process by using intelligent hypermedia
networks

4. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS – System Architecture
Architecture definition
• Architecture based on client-server architecture
• Two automatic learning levels
• Domain level learning
• Inter-domain learning level
• One server for each different domain and another server for the
inter domain learning level
• The learning mechanisms will be modeled as agents

5. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS– System Architecture
Domain Server Architecture
• Objective: Adapt the system to each student so that the
learning process should be improved

6. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS – System Architecture
Domain Server Architecture.
• The most relevant components used to achieve the main
objective of this domain are the following:
• Content Homogenization Agent
• Hypermedia Content Classifier Agent
• Knowledge association Agent
• Knowledge generator agent
• User behavior analyzer agent
• User behavior trend analyzer and monitoring agent
• E-learning module

7. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS – System Architecture
Inter - Domain Server Architecture
• Objective: Find out common behavior patterns of students
from different domains

8. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS – System Architecture
Inter - Domain Server Architecture Agents
• The following agents implement their own hypermedia
content repository in order to store knowledge that must be
accessible from every domain:
• Knowledge retrieval and homogenization agent
• Optimizer Agent
• Knowledge Search Agent
• Monitoring and Predicting Agent

9. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS – System Architecture
Algorithms and techniques
• The agents could be implemented with the following
techniques:
• Extraction, Load and Transform processes.
• Artificial Intelligence and Data mining algorithms:
• Decision Trees
• Neural networks
• Clustering algorithms
• Temporal Series
• Linear regression
• Sequence analysis algorithms
• Genetic Algorithms

10. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS – Use Case
ENAMIA:
• Virtual Education System with the capability to manage different
domains and keep a continuous students assessments and their
progress
• By using this architecture is possible to integrate different domains.
• Health: ALZHERAPHY
• Learning: Languages courses and Pre - school education
courses

11. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS – Use Case
• ENAMIA Architecture
Inter – Domain Server (ENAMIA)
Inter – Domain Server (ENAMIA)
Client Interface
Domain
Manageme
nt
Domain Servers Interface
Knowledge
Search Agent
Knowledge
Retrieval and
Homogenization
Agent
Optimizer
Agent
Monitoring and
Forecasting
Agent
Agent Interaction
Data Access Layer
Hypermedia Data
Server Domain (E-Learning)
Server Domain (E-Learning)
Domain Server (AZHERAPY)
Domain Server (AZHERAPY)
Client Interface
Inter – Domain Server
Interface
Client management
Network Node Management
Client interface
Inter – Domain Server
Interface
Client Management
Network Node Interface
E - Learning
(Languages and
pre-school
education)
Health
(ALZHERAPY)
Intelligent Agents
Intelligent Agents
Data Access Layer
Data Access Layer
Hypermedia Data
Hypermedia Data
Teacher
Patient
Doctor
Student

12. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS – Use Case
ALZHERAPHY:
• This system is intended to help people who suffer from Alzheimer by doing
memory exercises
• The patient is guided by a virtual tutor
• The system is used by doctors to get information online about patients
evolution
• The exercises are adapted to each patient in order to improve their memory
• Implemented by using the Domain Server Architecture:
• Multimodal access for the users (videos, images and 3D avatars).
• Pattern recognition

13. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS – Use Case
Learning Languages and pre – school education Domain
• The aim of this domain is to facilitate the process of creating e –
learning systems. By using this system e-learning courses can be
created easily. In addition, the learning techniques and algorithms
will be applied automatically.
• Implemented by using the Domain Server Architecture:
• Multimodal access for the users
• Pattern recognition
• Content management
• Schedule management

14. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS – Conclusion
Conclusion
The current e-learning systems have many advantages. However, with
the addition of intelligent systems that analyze students behavior the
current learning systems can be improved by adapting it to each user.
The detected behavior patterns will help decision makers to optimize
education procedures.

15. ADAPTIVE AND INTELLIGENT E-LEARNING SYSTEMS
Acknowledgements:
This work has been funded by the Future Internet II project
(ETORTEK 2011 program, Basque Government)

16. Contact information:
Armando Benito
armando.benito@tecnalia.com
Juan José Prieto
jjose.prieto@tecnalia.com
Julián González
julian.gonzalez@tecnalia.com
Juan Ramón Fernandez
jramon.fernandez@tecnalia.com
C/ Velázquez, 64-66 2º dcha
28001 Madrid
(Spain)
Tlf.: +34 946 430 850
www.tecnalia.com