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





Author(s):  
Vasiliki Demertzi ◽  
Konstantinos Demertzis

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.



Author(s):  
Hiran Nonato M. Ferreira ◽  
Taffarel Brant-Ribeiro ◽  
Rafael D. Araujo ◽  
Fabiano A. Dorca ◽  
Renan G. Cattelan


Author(s):  
Dominik Jednoralski ◽  
Erica Melis ◽  
Sergey Sosnovsky ◽  
Carsten Ullrich


Author(s):  
Peter Brusilovsky ◽  
Vincent P. Wade ◽  
Owen Conlan

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.



Author(s):  
Valerie J. Shute ◽  
Diego Zapata-Rivera


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