An Automatic and Dynamic Knowledge Assessment Module for Adaptive Educational Systems

2017 ◽  
Author(s):  
Hiran Nonato M. Ferreira ◽  
Taffarel Brant-Ribeiro ◽  
Rafael D. Araujo ◽  
Fabiano A. Dorca ◽  
Renan G. Cattelan
Keyword(s):  
Knowledge Assessment ◽  
Educational Systems ◽  
Adaptive Educational Systems

scholarly journals Evaluating and improving adaptive educational systems with learning curves

2010 ◽  
Vol 21 (3) ◽  
pp. 249-283 ◽  
Author(s):  
Brent Martin ◽  
Antonija Mitrovic ◽  
Kenneth R. Koedinger ◽  
Santosh Mathan
Keyword(s):  
Learning Curves ◽  
Educational Systems ◽  
Adaptive Educational Systems

scholarly journals A Hybrid Adaptive Educational eLearning Project based on Ontologies Matching and Recommendation System

2020 ◽  
Author(s):  
Vasiliki Demertzi ◽  
Konstantinos Demertzis
Keyword(s):  
Recommendation System ◽  
Learning System ◽  
Educational Systems ◽  
Learning Needs ◽  
Pedagogical Strategies ◽  
Substantive Content ◽  
Teaching Content ◽  
Adaptive Educational Systems ◽  
Educational Conditions ◽  
Content Based Filtering

The implementation of teaching interventions in learning needs has received considerable attention, as the provision of the same educational conditions to all students, is pedagogically ineffective. In contrast, more effectively considered the pedagogical strategies that adapt to the real individual skills of the students. An important innovation in this direction is the Adaptive Educational Systems (AES) that support automatic modeling study and adjust the teaching content on educational needs and students' skills. Effective utilization of these educational approaches can be enhanced with Artificial Intelligence (AI) technologies in order to the substantive content of the web acquires structure and the published information is perceived by the search engines. This study proposes a novel Adaptive Educational eLearning System (AEeLS) that has the capacity to gather and analyze data from learning repositories and to adapt these to the educational curriculum according to the student skills and experience. It is a novel hybrid machine learning system that combines a Semi-Supervised Classification method for ontology matching and a Recommendation Mechanism that uses a hybrid method from neighborhood-based collaborative and content-based filtering techniques, in order to provide a personalized educational environment for each student.

scholarly journals From Learning Objects to Adaptive Content Services for E-Learning

2008 ◽  
pp. 243-261 ◽  
Author(s):  
Peter Brusilovsky ◽  
Vincent P. Wade ◽  
Owen Conlan
Keyword(s):  
Learning Objects ◽  
Learning Systems ◽  
Educational Systems ◽  
Next Generation ◽  
Distributed Architecture ◽  
E Learning ◽  
Adaptive Educational Systems ◽  
New Generation ◽  
The Way ◽  
Adaptive Content

This paper argues that a new generation of powerful E-learning systems could start on the crossroads of two emerging fields: courseware re-use and adaptive educational systems. We argue for a new distributed architecture for E-learning systems based on the idea of adaptive reusable content services. This paper discusses problems that have to be solved on the way to the new organization of E-learning and reviews existing approaches and tools that are paving the way to next generation E-learning systems. It also presents two pioneer systems - APeLS and KnowledgeTree that have attempted to develop a new service-based architecture for adaptive E-learning.

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