Work-in Progress: Development of an E-learning FPGA Platform Following the IEEE SA Std. 1876 - 2019 Standard for Networked Smart Learning Objects for Online Laboratories

2021 ◽  
pp. 3-9
Author(s):  
Marcelo Daniel Berejuck ◽  
Jhennifer Cristine Matias ◽  
Emilio Werner ◽  
Hamadou Saliah-Hassane
Keyword(s):  
Learning Objects ◽  
Work In Progress ◽  
Smart Learning ◽  
Online Laboratories ◽  
E Learning

Learning Object Model for Online Laboratories

2011 ◽  
pp. 514-527
Author(s):  
Habib Mir M. Hosseini ◽  
Keck Voon Ling ◽  
Bing Duan
Keyword(s):  
Learning Objects ◽  
Learning Systems ◽  
Learning Object ◽  
Object Model ◽  
Web Based ◽  
Course Content ◽  
Online Laboratories ◽  
E Learning ◽  
Text Images ◽  
Learning Concept

Online learning environments provide the students access to the course content at any time and from anywhere. Most of the existing e-Learning systems are designed for content-based subjects that deliver course content such as text, images, video, audio, and simulation to the student through the Internet. In recent years, several online or remote laboratories have been developed to bring the e-Learning concept to the lab-based courses. These systems, mainly web-based, allow students to conduct real laboratory experiment, as opposed to computer simulations, from anywhere and at any time. In this chapter, we introduce a model for providing lab-based lessons as Learning Objects. The Learning Object model has been widely used in content-based e-Learning systems. We then propose a learning management system framework which helps students to remotely access the lab-based learning objects. We will also present some experimental results and implementations.

Learning Object Model for Online Laboratories

2011 ◽  
pp. 768-784 ◽  
Author(s):  
Habib Mir M. Hosseini ◽  
Keck Voon Ling ◽  
Bing Duan
Keyword(s):  
Learning Objects ◽  
Learning Systems ◽  
Learning Object ◽  
Object Model ◽  
Web Based ◽  
Course Content ◽  
Online Laboratories ◽  
E Learning ◽  
Text Images ◽  
Learning Concept

Online learning environments provide the students access to the course content at any time and from anywhere. Most of the existing e-Learning systems are designed for content-based subjects that deliver course content such as text, images, video, audio, and simulation to the student through the Internet. In recent years, several online or remote laboratories have been developed to bring the e-Learning concept to the lab-based courses. These systems, mainly web-based, allow students to conduct real laboratory experiment, as opposed to computer simulations, from anywhere and at any time. In this chapter, we introduce a model for providing lab-based lessons as Learning Objects. The Learning Object model has been widely used in content-based e-Learning systems. We then propose a learning management system framework which helps students to remotely access the lab-based learning objects. We will also present some experimental results and implementations.

Toward a Hybrid Recommender System for E-learning Personnalization Based on Data Mining Techniques

2018 ◽  
Vol 2 (4) ◽  
pp. 271 ◽  
Author(s):  
Outmane Bourkoukou ◽  
Essaid El Bachari
Keyword(s):  
Learning Style ◽  
Recommender System ◽  
Adaptive Learning ◽  
Learning Objects ◽  
Research Field ◽  
Learning System ◽  
K Nearest Neighbors ◽  
E Learning ◽  
Hybrid Recommender System ◽  
Hybrid Recommender

Personalized courseware authoring based on recommender system, which is the process of automatic learning objects selecting and sequencing, is recognized as one of the most interesting research field in intelligent web-based education. Since the learner’s profile of each learner is different from one to another, we must fit learning to the different needs of learners. In fact from the knowledge of the learner’s profile, it is easier to recommend a suitable set of learning objects to enhance the learning process. In this paper we describe a new adaptive learning system-LearnFitII, which can automatically adapt to the dynamic preferences of learners. This system recognizes different patterns of learning style and learners’ habits through testing the psychological model of learners and mining their server logs. Firstly, the device proposed a personalized learning scenario to deal with the cold start problem by using the Felder and Silverman’s model. Next, it analyzes the habits and the preferences of the learners through mining the information about learners’ actions and interactions. Finally, the learning scenario is revisited and updated using hybrid recommender system based on K-Nearest Neighbors and association rule mining algorithms. The results of the system tested in real environments show that considering the learner’s preferences increases learning quality and satisfies the learner.

Evaluasi Aksesibilitas Learning Object Berdasarkan Web Content Accessibility Guidelines 2.0

2017 ◽  
Vol 9 (2) ◽  
pp. 67-71
Author(s):  
Herru Darmadi ◽  
Yan Fi ◽  
Hady Pranoto
Keyword(s):  
Learning Objects ◽  
Authoring Tool ◽  
Learning Object ◽  
Web Content ◽  
Web Browser ◽  
E Learning ◽  
Index Terms ◽  
Accessibility Guidelines ◽  
Content Accessibility

Learning Object (LO) is a representation of interactive content that are used to enrich e-learning activities. The goals of this case study were to evaluate accessibility and compatibility factors from learning objects that were produced by using BINUS E-learning Authoring Tool. Data were compiled by using experiment to 30 learning objects by using stratified random sampling from seven faculties in undergraduate program. Data were analyzed using accessibility and compatibility tests based on Web Content Accessibility Guidelines 2.0 Level A. Results of the analysis for accessibility and compatibility tests of Learning Objects was 90% better than average. The result shows that learning objects is fully compatible with major web browser. This paper also presents five accessibility problems found during the test and provide recommendation to overcome the related problems. It can be concluded that the learning objects that were produced using BINUS E-learning Authoring Tool have a high compatibility, with minor accessibility problems. Learning objects with a good accessibility and compatibility will be beneficial to all learner with or without disabilities during their learning process. Index Terms—accessibility, compatibility, HTML, learning object, WCAG2.0, web

Learning objects management and evaluatio in an e-learning environment

1970 ◽  
Vol 6 (2) ◽  
Author(s):  
Hugo Rego ◽  
Tiago Moreira ◽  
Francisco José García-Peñalvo
Keyword(s):  
Knowledge Management ◽  
Learning Environment ◽  
Learning Process ◽  
Group Learning ◽  
Learning Objects ◽  
Authoring Tools ◽  
Learning Platform ◽  
E Learning ◽  
Teaching Learning ◽  
Educational Contents

The main aim of the AHKME e-learning platform is to provide a system with adaptive and knowledge management abilities for students and teachers. This system is based on the IMS specifications representing information through metadata, granting semantics to all contents in the platform, giving them meaning. In this platform, metadata is used to satisfy requirements like reusability, interoperability and multipurpose. The system provides authoring tools to define learning methods with adaptive characteristics, and tools to create courses allowing users with different roles, promoting several types of collaborative and group learning. It is also endowed with tools to retrieve, import and evaluate learning objects based on metadata, where students can use quality educational contents fitting their characteristics, and teachers have the possibility of using quality educational contents to structure their courses. The learning objects management and evaluation play an important role in order to get the best results in the teaching/learning process.

Augmented Reality in Online Teacher Traning for Digital Competence

2021 ◽  
Vol LXIV (5) ◽  
pp. 503-519
Author(s):  
Evgenia Goranova ◽  
◽  
Valentina Voinohovska ◽  
Keyword(s):  
Augmented Reality ◽  
Learning Objects ◽  
Variable Component ◽  
Qr Code ◽  
Digital Learning ◽  
Digital Competence ◽  
Video Information ◽  
Field Independent ◽  
E Learning ◽  
Teacher Traning

The article presents an approach applied in the online training of pre-service teachers to acquire digital competence. The content of the concept of ‘digital competence’ in its sustainable and variable component is clarified. The understanding of ‘augmented reality’ to e-learning objects is presented. Two forms of ‘augmented reality’ have been proposed to visualize video information to a clarified concept. The first one is presented via a QR code for quick access and applicable for mobile learning. The other is provided by icons and is applicable to e-learning with a computer. It is believed that ‘augmented reality’ can differentiate students’ online learning according to the field-dependent and field-independent cognitive style and their preferences on the use of different digital learning devices.

scholarly journals When is a Learning Object not an Object: A first step towards a theory of learning objects

2002 ◽  
Vol 3 (2) ◽  
Author(s):  
Mike Sosteric ◽  
Susan Hesemeier
Keyword(s):  
Economies Of Scale ◽  
Learning Objects ◽  
Short Term ◽  
Object A ◽  
Smart Learning ◽  
Smart Learning Environments ◽  
Adequate Definition ◽  
Definition Of ◽  
Conceptual Confusion

<p> For some, “learning objects" are the “next big thing” in distance education promising smart learning environments, fantastic economies of scale, and the power to tap into expanding educational markets. While learning objects may be revolutionary in the long term, in the short term, definitional problems and conceptual confusion undermine our ability to understand and critically evaluate the emerging field. This article is an attempt to provide an adequate definition of learning objects by (a) jettisoning useless theoretical links hitherto invoked to theorize learning objects, and (b) reducing the definition of learning objects to the bare essentials. The article closes with suggestions for further research and further refinement of the definition of learning objects. </P>

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