Interactive and Adaptive Learning Content Authoring Framework for an M-Learning Toolkit

2021 ◽  
Author(s):  
Shakyani Jayasiriwardene ◽  
Dulani Meedeniya
Keyword(s):  
Adaptive Learning ◽  
Learning Content

Learning Nuggets for Cobot Education: A Conceptual Framework, Implementation, and Evaluation of Adaptive Learning Content

2021 ◽  
Author(s):  
Walter Mayrhofer ◽  
Steffen Nixdorf ◽  
Clara Fischer ◽  
Tanja Zigart ◽  
Christina Schmidbauer ◽  
...  
Keyword(s):  
Conceptual Framework ◽  
Adaptive Learning ◽  
Learning Content

The Construction of an Ontology-Based Ubiquitous Learning Grid

2011 ◽  
pp. 191-212
Author(s):  
Ching-Jung Liao ◽  
Chien-Chih Chou ◽  
Jin-Tan David Yang
Keyword(s):  
Learning Environment ◽  
Ubiquitous Computing ◽  
Adaptive Learning ◽  
Experimental Results ◽  
Background Information ◽  
Ubiquitous Learning ◽  
Ubiquitous Computing Environment ◽  
Java Programming ◽  
Learning Content ◽  
Information Awareness

The purpose of this study is to incorporate adaptive ontology into ubiquitous learning grid to achieve seamless learning environment. Ubiquitous learning grid uses ubiquitous computing environment to infer and determine the most adaptive learning contents and procedures in anytime, any place and with any device. To achieve the goal, an ontology-based ubiquitous learning grid (OULG) was proposed to resolve the difficulties concerning how to adapt learning environment for different learners, devices, places. OULG through ontology identifying and adapting in the aspects of domain, task, devices, and background information awareness, so that the adaptive learning content could be delivered. A total of 42 freshmen participate in this study for four months to learn Java programming. Both of pretesting and posttesting are performed to ensure that the OULG is useful. Experimental results demonstrate that OULG is feasibile and effective in facilitating learning.

Realization of Adaptive Learning Content Based on Learning Object and Domain Ontology

2010 ◽  
Vol 171-172 ◽  
pp. 527-530
Author(s):  
Xu Wei
Keyword(s):  
Information Technology ◽  
Adaptive Learning ◽  
New Technologies ◽  
Domain Ontology ◽  
Learning System ◽  
Learning Object ◽  
Modern Education ◽  
Learning Content ◽  
E Learning ◽  
Adaptive Content

With the evolution of information technology, E-learning has spread rapidly. Traditional E-learning has proved not fit requirement of modern education, new trend of developing the adaptive and customized E-learning system draws more and more attentions from researchers and practitioners. In this paper, we proposed an E-learning system which can provide adaptive content according to different situations of user. To achieve the adaptive E-learning system, two new technologies have been adopted by the system: learning object and domain ontology. Using these two technologies the system can provide intelligent learning content based on the user’s context, knowledge’s context. The paper also presents a scenario to demonstrate the step of production of adaptive learning content.

scholarly journals Learning Content Model: from Concept Structuring to Adaptive Learning

2021 ◽  
Vol 25 (1) ◽  
pp. 28-39
Author(s):  
J. V. Vainshtein ◽  
R. V. Esin ◽  
G. M. Tsibulsky
Keyword(s):  
Graph Theory ◽  
Adaptive Learning ◽  
Educational Process ◽  
Subject Domain ◽  
Research Issues ◽  
Content Model ◽  
Electronic Environment ◽  
Learning Content ◽  
E Learning ◽  
The Subject

The aim of the study. In modern conditions of changing the global “educational landscape”, the leading trend in building a new educational process management system is the personalization of the educational process in the electronic environment. New pedagogical technologies and innovative forms of organizing personalized learning in the electronic environment are developing, one of which is adaptive learning. The development of the structure and content of adaptive e-learning courses, the design and implementation of an educational strategy, teaching methods, and approaches to assessing results is determined by the model of its subject domain - the model of learning content. The aim of the study is to develop an approach to constructing the learning content model of an adaptive e-learning course that provides a formalized presentation of the educational material of the discipline and the construction of a logically based strategy for its study. Materials and methods. Methodological basis of research methods make up the logical-epistemological analysis and graph theory, and comparative analysis of psychological and pedagogical, scientific and methodical works, analysis of regulatory documents on research issues, professional and federal educational standards of higher education. Results. A feature of the author's approach is structuring of the subject domain in the form of a sequence of terms (training objects) of the learning content, studied in a certain order and presented in several versions of the presentation. The presented model for constructing the learning content of the academic discipline differs from the wellknown ones by the presence of logical ordering of concepts based on the integration of logic methods of concept analysis, using logical and epistemological methods for correlating the volume and content of concepts with the methods of graph theory and hypergraphs. The definition of educational objects of a tree (hypergraphic tree) of terms is obtained on the basis of a concept tree of discipline with a further determination of the sequence of their study, as well as the inclusion of a phenomenological and structural model in the content of the educational object, which allows to identify and disclose the essence of each studied concept within the framework of the subject domain of discipline. Conclusion. The proposed approach has been tested in the educational process of the program 09.03.02 – “Information systems and technologies” at the Siberian Federal University. Analysis of observations and evaluating the effectiveness of adaptive e-learning course in the educational process was carried out using the Kruskal-Wallis test by ranks. As a result of the experiment, it was revealed that at the end of the experiment, the control and experimental groups were statistically significantly different, which allowed us to conclude that the adaptive e-learning course developed in the educational process was effective. Adaptive e-learning courses, which are based on the approach proposed by the authors, made it possible to present educational content in the form of logically integral micro portions, which allow the adaptation of the educational environment to the individual characteristics of students. In the future, the proposed approach can contribute to development of personalized adaptive learning university ecosystems under digitalization formation.

Ontology-based Adaptive Dynamic e-Learning Map Planning Method for Conceptual Knowledge Learning

2016 ◽  
Vol 11 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Tsung-Yi Chen ◽  
Hui-Chuan Chu ◽  
Yuh-Min Chen ◽  
Kuan-Chun Su
Keyword(s):  
Adaptive Learning ◽  
Conceptual Knowledge ◽  
Pso Algorithm ◽  
Asynchronous Learning ◽  
Knowledge Map ◽  
Learning Needs ◽  
Adaptive Dynamic ◽  
Learning Content ◽  
E Learning ◽  
The Individual

E-learning improves the shareability and reusability of knowledge, and surpasses the constraints of time and space to achieve remote asynchronous learning. Since the depth of learning content often varies, it is thus often difficult to adjust materials based on the individual levels of learners. Therefore, this study develops an ontology-based adaptive dynamic knowledge concept e-learning mechanism that generates learning maps based on learner characteristics and guides learners effectively. To achieve this goal, this study proposes an adaptive dynamic concept e-learning navigation procedure, designs learning models based on the adaptive learning needs of learners, and develops knowledge map model and learning map model. Finally, this study designs adaptive dynamic concept learning map-planning algorithms based on the particle swarm optimization (PSO) algorithm. The learning maps generated by these algorithms meet the dynamic needs of learners by continually adjusting and modifying the learning map throughout the learning process. Adapting the adaptive learning content according to the dynamic needs of learners allows learners to receive more instruction in a limited period.

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