Development of an Adaptive Learning System (original) (raw)

Ontology in Adaptive Learning Environment

Advances in Intelligent Systems and Computing, 2012

Adaptive e-learning systems can be defined as systems offering personalized solutions to suit individual learners' needs. Thus personalized solutions are built with respect to different kinds of adaptation which are content and navigation. The goal of such adaptive environments is not to make learning material accessible but to improve learning by adapting navigation, interaction and content. For this aim, it was necessary to investigate the learner profile and activities modelling. Actually, with new kinds of adaptation induced by mobility needs of learner, the learner profile modelling have to be adapted. We propose a more exhaustive learner model which we call "learner context". Thus, in adaptive learning systems, an adequate modelling approach must be proposed and integrated with respect to learning reusability and interoperability. In this respect, semantic Web technologies especially ontology seem to be an efficient modeling approach and can be used to take adaptation decisions. we intend to explore how ontologies can harmonize different aspects of an adaptive e-learning system. Such ontologies could be used to assist designers and authors in the modelling of contextualized learning or even to directly generate such experiences themselves.

Modelling The Learner Model Based Ontology In Adaptive Learning Environment

Journal of Disruptive Learning Innovation (JODLI), 2019

Currently, the online learners are increasingly demanding more personalized learning since the web technology, and the learners have individual features of characteristics such as learning goals, experiences, interests, personality traits, learning styles, learning activities, and prior knowledge. A personalized learning process requires an adaptive learning system (ALS). In order to adapt, a learner model is required. Thus, modelling the learner model in an adaptive system environment is a key point to success in recommending the learner. The ontology-based approach was used to model the adaptive learning model in this research. Ontology is a graph structure that consists of a collection of contexts, relationships, and models which related to contexts. The ontology of the learner model enables to produce a description of learner’s properties which contains important information about domain knowledge, learning performance, interests, preference, goal, tasks, and personal traits.K...

A Framework for the Generation of Adaptive Courses Based on Semantic Metadata

Multimedia Tools and Applications, 2005

Our approach proposes the creation and management of adaptive learning systems by combining component technology, semantic metadata, and adaptation rules. A component model allows interaction among components that share consistent assumptions about what each provides and each requires of the other. It allows indexing, using, reusing, and coupling of components in different contexts powering adaptation. Two adaptive learning strategies are proposed: course-based and goals-based. These strategies use rules to rewrite user query and user model. In this way, it is possible both searching components developing concepts not appearing in the user query but related with user goals and inferring user knowledge that is not explicit in user model.

Designing lesson content in adaptive learning environments

2006

Online learning is widely spreading and adaptive learning environments are increasing its potentials. We present a scenario of adapting learning content towards individual student characteristics taking into consideration his/her learning style type and subject matter motivation level. We use an ontology based student model for storing student information. The scenario of designing lesson content tailored to individual student needs is presented as a cross section of learning style and motivation level, based on the learning object's educational metadata. Our future work will be to provide experiment and to test our proposed guidelines in order to get feedback on how learners see the adaptive learning environments tailored to their individual learning style and motivation characteristics.

A novel adaptive learning management system using ontology

2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS), 2015

The success of web technologies has prompted a developing consideration on e-learning activities. Notwithstanding, most current e-Learning systems give static web-based learning with the goal that learners get to the same learning contents through the web, regardless of individual learners profiles. These learners may have altogether different learning foundations, information levels, learning styles, and capacities. The 'one size fit all' in an e-Learning frameworks is unmistakably a commonplace issue. To defeat this impediment and build powerful learning, versatile and customized learning is as of now a dynamic examination range. This paper propose a novel approach for designing and implementing adaptive learning management system based on ontology and semantic web technologies by offering a tailored model which represents the different activities that should be completed by learner. It offers a framework that is based on both learning styles and ontology to address the impact of student behavior.

Adaptive courseware model for intelligent e-learning systems

This paper describes an Adaptive Courseware Tutor – an intelligent tutoring system based on stereotypes, Bayesian networks and Bloom's knowledge taxonomy. The main feature of our approach is the automatization of learning object generation and courseware adaptivity in every stage of learning and teaching process. The student module is enhanced by double stereotypes based on student's knowledge level and on Bloom's knowledge taxonomy, as well as, by Bayesian networks. The tutor module is responsible for the automatic generation of courseware elements, their dynamic selection and sorting, as well as their adaptive presentation using templates for statements and questions. In order to evaluate the model's effectiveness, a controlled experiment with a large sample was conducted.

The role of interactive learning objects in an adaptive e-learning system

This paper presents the ADAPT project, a distance adaptative learning platform whose domain application is, in an initial phase, for digital systems. This LMS (Learning Management System) makes use of some Artificial Intelligence (AI) models and techniques has the ability to adapt course contents to the learning preferences of each student. The followed approaches include Case-Based Reasoning, Educational Adaptive Systems, Intelligent Tutoring Systems, Link-Mining and Evolutionary Computation. Through theses techniques this platform enables: The Capture of students performance and learning style, cases of success and failure and the correspondent appropriateness of the learning content of each profile; The automatic learning, based on the paths of better performance also on success and failure cases, is generated. This paper focuses on the description of the use of alternative representations of the content, in order to accommodate the different learning styles of students. However, an e-learning system to be successful should motivate the student through pedagogic and interactive techniques. So, in this work we gave special attention to the use of interactive animations through appropriate metaphors leading to a better understanding of the students, especially those who have a kinesthetic profile.

Towards an Adaptive Learning Environment Supported by Ontologies

Being proficient in a foreign language is an important differential for people who aim better position on nowadays world. This work addresses the issue of modeling the Japanese Language Proficiency Test (JLPT) domain through an ontology. The ontology was developed in the attempt to provide options for personalized learning oriented to the context, based on some relevance principles. The presented ontology was submitted to evaluators to assure its consistency.

A Gradually Developing Adaptive Tutoring System as the Course Progresses

Distance Learning and Education--International Proceedings of Computer Science and Information Technology, 2011

Abstract. Adaptive Educational Systems are able to alter the online course as per the needs of each student based upon online tests. These systems require a lot of time and effort required to design and build such courses. This paper offers a practical adaptive system that is automatically built as instructors upload their adaptive lessons and tests to the online site. The system asks the instructor to associate multiple choice questions that are incorrect with error pattern names and to associate the error patterns with lessons students need to ...