Towards Adaptive E-Learning using Decision Support Systems

Abstract

Abstract-The significance of personalization towards learners' needs has recently been agreed by all web-based instructional researchers. This study presents a novel ontology semantic-based approach to design an e-learning Decision Support System (DSS) which includes major adaptive features. The ontologically modelled learner, learning domain and content are separately designed to support personalized adaptive learning. The proposed system utilise captured learners' models during the registration phase to determine learners' characteristics. The system also tracks learner's activities and tests during the learning process. Test results are analysed according to the Item Response Theory in order to calculate learner's abilities. The learner model is updated based on the results of test and learner's abilities for use in the adaptation process. Updated learner models are used to generate different learning paths for individual learners. In this study, the proposed system is implemented on the "Fraction topic" of the mathematics domain. Experimental test results indicated that the proposed system improved learning effectiveness and learner's satisfaction, particularly in its adaptive capabilities.

Um Método Baseado na Teoria da Resposta ao Item para Avaliação e Feedback Automático no Contexto de Educação Digital

“…Contudo, os trabalhos encontrados abordam os tópicos de maneira isolada ou a TRI com um dos tópicos mencionados. Entre os trabalhos encontrados há os de Chen e Duh (2008); Yarandi, Jahankhani, e Tawil (2013); Rajamani e Kathiravan (2013); El Falaki, El Faddouli, Idrissi, e Bennani (2013).…”

“…Por sua vez, o trabalho de Yarandi et al (2013) lida com sistemas de aprendizagem eletrônica (e-learning) apresentando uma abordagem diferente do que se tem pesquisado na literatura, pois os sistemas atuais adotam o conceito de aprendizagem estática, ou seja, os estudantes recebem o mesmo conteúdo independentemente do perfil que possuam. Assim, Yarandi et al (2013) propõem um sistema de tomada de decisão que use a aprendizagem adaptativa para identificar os estilos de aprendizagem, habilidades e conhecimento prévio dos estudantes, com a finalidade de determinar de maneira dinâmica conteúdos educacionais que se adéquem as necessidades de cada aluno.…”

MAGAM: A Multi-Aspect Generic Adaptation Model for Learning Environments

“…It was evaluated in an English vocabulary course with 22 learners and showed positive results on the learners' performance. As another example, the system proposed by Yarandi et al [18] adapts the learning path based on learners' knowledge model and the presentation based on their learning styles, abilities and preferences. These systems are not easily generalizable, as they are specific to the combined aspects and their related adaptation techniques.…”

Decision Support System for Learning Disabilities Children in Detecting Visual-Auditory-Kinesthetic Learning Style

“…Lately, DSS technology has been positively applied to many decision-making problems in numerous disciplines, including education [8]. DSS as part of e-learning systems can analyze data in users' profiles and allow the learners to select optimized learning paths based on previous learning information about learners [9]. Individuals with learning disabilities possibly will have dissimilar problems from each other.…”