Pro-Active Multi-Agent System in Virtual Education
Victoriya Repka, Vyacheslav Grebenyuk, Katheryna Kliushnyk · InTech eBooks · 2011
As virtual education becomes more and more widespread, its' application provides a unique opportunity for us to develop new applications in adaptive or intelligent agent technology.Adaptive or intelligent agent technologies allow education methods to be identified on a case-by-case basis, and undertaken regardless of location, time, age and life lifelong.There are many different distant education (DE) models developed to take into account modern tendencies of distributed system ideas and intelligent agent technology.The last strengthens the ontological features of DE system and move up the users from passive knowledge recipient role into active actors in the educational process.Therefore the main priority for the development of a modern virtual education system is to provide each student with an individual program, and to allow them to choose courses to fit their level of knowledge as well as make information searchable in accordance to the query criteria and within existing user skill sets.New methods and methodologies are being developed to s o l v e t h i s p r o b l e m , a s w e l l a s m a n y o t h e r s a s s o c i a t e d w i t h v i r t u a l e d u c a t i o n , d i s t a n t education, and e-learning.An adaptation to a learner's personal interests, characteristics and goals is a key challenge in e-learning.In this chapter we discuss the architecture of web-based learning systems that addresses the learners' need for activities and content based on their preferences and equally considers the designer's and tutor's needs for the efficiency.The system aims to develop new methods and services for pro-active and adaptive e-learning.Proactive means the system involves acting in advance of a future situation, rather than just reacting.It means taking control and making things happen rather than just adjusting to a situation or waiting for something to happen.Adaptive means the learners are provided with a learning design that is adapted to their personal characteristics, interests and goals as well as the current context.Currently, two approaches to adaptation are common within e-learning.In the first, dominated by a strong tradition in instructional design, a team produces a detailed design of content, interaction and presentation.Within the design different options may be worked out for different learners based on user data, e.g.level, interest or learning style.The options for adaptation are prepared at design time and require limited, if any, interaction of tutors at runtime.The second approach is based on the assumption that author and tutor is the same www.intechopen.com Multi-Agent