Kotevski, Aleksandar (2017) Adaptive system for providing recommendations based on tags in e-learning. PhD thesis, Goce Delcev University, Stip.
Preview |
Text
AleksandarKotevski_PhD.pdf Download (4MB) | Preview |
Abstract
The development of an increasing number of systems for e-learning used as part of the educational process from one site, and the growing number of users and data from the other site, are just some of the reasons that actualized the need of personalization of the e-learning systems based on the users’ needs, their habits, learning styles, their prior knowledge and so on. The modern systems for e-learning tend to develop techniques for increasing their intelligence and adaptability in order to increase their efficiency and productivity. The effectiveness of e-learning, in particular, is based on their ability to adapt based on the users’ needs and to display the most adequate content for users based on their educational goals and their learning styles. On the other hand, searching for useful learning context in a large dataset without some techniques or tools for content filtering and recommendations is almost impossible and leads to inefficient learning process. Therefore, there is a practical need for personalized systems for e-learning or to adapt the system to the users’ needs, their habits and learning styles. The need for personalization of the e-learning systems occurs primarily because of the users’ differences - they have different learning styles, different prior knowledge and goals and so on. Intelligent learning systems represent improvement and updating of computer learning. Their basically purpose is to present the most adequate materials that is adapted to the users’ needs. They use a model of individual characteristics of the user (goals, preferences, knowledge) in order to adjust their operations. The user model can be created by examining, monitoring of the user interactions or by requesting answers from the users. Intelligent web-based learning systems are focused on improving the quality of services and for the precise and appropriate selection of content. In addition, they deliver contents to users that are most appropriate and meet their needs and users do not search through a large archive of learning materials, but through a limited number of materials selected based to their requirements, age, experience, previous content and needs. Moreover, the data is delivered in a format acceptable to the users’ learning style and users got recommendations for useful learning materials. Additional significant feature of intelligent systems for e-learning is the ability to adapt and change their functions and operations based on the reaction of users.
| Item Type: | Thesis (PhD) |
|---|---|
| Subjects: | Natural sciences > Computer and information sciences |
| Divisions: | Faculty of Computer Science |
| Depositing User: | Sladzana Dimiskov |
| Date Deposited: | 01 Mar 2017 15:15 |
| Last Modified: | 01 Mar 2017 15:15 |
| URI: | https://eprints.ugd.edu.mk/id/eprint/17574 |
Actions (login required)
 |
View Item |