Learning Repository Adaptability in an Agent-Based University Environment

Abstract

Automated e-Learning Systems (AeLS) are fundamental to contemporary educational concepts worldwide. It has become a standard not only in support to the formal curriculum, but containing social platform capabilities, gamification elements and functionalities fostering communities of experts, also for faster knowledge dissemination. Additionally, AeLSs support internal communications and customizable analytics and methodologies to quickly identify learning performance, which in turn can be used as feedback to implement adaptability in tailoring the content management to meet specific individual needs. The volume of fast growing AeLS content of supplement material and exchanged communication combined with the already huge material archived in the university libraries is enormous and needs sophisticated managing through electronic repositories. Such integration of content management systems (CMS) present challenges which can be solved optimally with the use of distributed management implemented through agent-based systems. This paper depicts a successful implementation of an Integrated Intelligent Agent Based University Information System (IABUIS).

Supporting Education in Math Sciences With a Low-Budget LMS Sakai

“…At the Faculty of Natural Sciences and Mathematics in 2007 was successfully implemented a commercial ORACLE iLearning LMS platform and the educational system for learning mathematics and informatics MATHEIS [6], [10] has been successfully integrated into this platform and migrated into Open Source LMS Sakai [7], [8]. This e-learning environment (Sakai) was chosen from a selected list of few Open Source LMSs on a bases of literature made comparisons (ATutor, dotLRN, Ilias, Moodle and Sakai) and survey we have done in order to select appropriate load balancing and scaling LMS capable to incorporate e-content math standards and tools (like OpenMath, MathML, LaTex, WIRIS, etc.).…”

“…The Personalized Content Viewing Agent (PCVA) is responsible for the adaptive interaction and adaptive content/course delivery. All three agents collaborate among them sharing distributed agent knowledge and learning rules [7]. The Mediator is responsible for the student learning model, database of the student's grades, degree levels, preferences, abilities, aptitudes, etc.…”

A Primer of a Sensor Calibration Procedure for Embedded Applications

“…to provide adaptation to individual student needs for steeper learning curves. Such AeLMS (Adaptive eLMS) have proved to be very successful in improving overall University education quality [1,2]. Some efforts in this field are Virtual Laboratories to make lab equipment and simulation engines accessible to students in cases when such is remote or in deficit [3,4,5,6].…”