scholarly journals Artificial Intelligence Visual Metaphors in E-Learning Interfaces for Learning Analytics

2020 ◽  
Vol 10 (20) ◽  
pp. 7195
Author(s):  
Valentina Franzoni ◽  
Alfredo Milani ◽  
Paolo Mengoni ◽  
Fabrizio Piccinato
Keyword(s):  
Artificial Intelligence ◽  
Learning Analytics ◽  
Learning Objects ◽  
Learning Object ◽  
Visual Metaphor ◽  
Design Quality ◽  
Visual Metaphors ◽  
Tag Cloud ◽  
E Learning ◽  
Learning Management

This work proposes an innovative visual tool for real-time continuous learners analytics. The purpose of the work is to improve the design, functionality, and usability of learning management systems to monitor user activity to allow educators to make informed decisions on e-learning design, usually limited to dashboards graphs, tables, and low-usability user logs. The standard visualisation is currently scarce, and often inadequate to inform educators about the design quality and students engagement on their learning objects. The same low usability can be found in learning analytics tools, which mostly focus on post-course analysis, demanding specific skills to be effectively used, e.g., for statistical analysis and database queries. We propose a tool for student analytics embedded in a Learning Management System, based on the innovative visual metaphor of interface morphing. Artificial intelligence provides in remote learning immediate feedback, crucial in a face-to-face setting, highlighting the students’ engagement in each single learning object. A visual metaphor is the representation of a person, group, learning object, or concept through a visual image that suggests a particular association or point of similarity. The basic idea is that elements of the application interface, e.g., learning objects’ icons and student avatars, can be modified in colour and dimension to reflect key performance indicators of learner’s activities. The goal is to provide high-affordance information on the student engagement and usage of learning objects, where aggregation functions on subsets of users allow a dynamic evaluation of cohorts with different granularity. The proposed visual metaphors (i.e., thermometer bar, dimensional morphing, and tag cloud morphing) have been implemented and experimented within academic-level courses. Experimental results have been evaluated with a comparative analysis of user logs and a subjective usability survey, which show that the tool obtains quantitative, measurable effectiveness and the qualitative appreciation of educators. Among metaphors, the highest success is obtained by Dimensional morphing and Tag cloud transformation.

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

scholarly journals From Cognitive Landscapes to Digital Hyperscapes

2003 ◽  
Vol 4 (2) ◽  
Author(s):  
Jose Bidarra ◽  
Ana Dias
Keyword(s):  
Learning Styles ◽  
Learning Management Systems ◽  
Learning Objects ◽  
Management Systems ◽  
Digital Information ◽  
Cognitive Profiles ◽  
E Learning ◽  
Learning Management ◽  
Key Terms ◽  
Massive Information

<P> The widespread diffusion of e-Learning in organizations has encouraged the discovery of more effective ways for conveying digital information to learners, for instance, via the commonly called Learning Management Systems (LMS). A problem that we have identified is that cognitive variables and pedagogical processes are rarely taken into consideration and sometimes are confused with the mere use by learners of “diversified” hypermedia resources. Within the context of widespread dissemination of multimedia content that has followed the emergence of massive information resources, we discuss the need for more powerful and effective learner-centered tools capable of handling all kinds of design configurations and learning objects. </p> <P class=abstract><B>Key Terms: </B>cognitive profiles, learning styles, mind mapping, multimedia and hypermedia content, hyperscapes, e-Learning, learning objects, Learning Management Systems (LMS).</P>

PERSONALISASI MATEMATIS DALAM E-LEARNING MELALUI LEARNING MANAGEMENT SYSTEM

2020 ◽  
Vol 12 (34) ◽  
Author(s):  
Euis Setiawati
Keyword(s):  
Management System ◽  
Learning Management System ◽  
Rapid Development ◽  
Mathematics Learning ◽  
Descriptive Analysis ◽  
Scientific Paper ◽  
Learning Objects ◽  
New Paradigm ◽  
E Learning ◽  
Learning Management

The rapid development of science and technology has not fully brought a new paradigm in learning mathematics, seen by a large number of internet users only limited to the use of social media in every circle. The purpose of writing this scientific paper is to describe elearning as a way of learning built by the Learning Management System (LMS), and how this system can play a role in personalizing mathematical concepts. The research method used is descriptive analysis by collecting data, compiling or classifying, analyzing, and interpreting several types of software commonly used in e-learning. The results of the analysis show that mathematical personalization can occur by utilizing the features contained in the topics of LMS and is very useful for building learning objects that are suitable to overcome various didactic obstacles in mathematics learning, encourage more semiotic coordination in presentations, and avoid bad classroom practices during mathematics learning. Personalization through LMS can also produce different didactic abilities by considering the profiles of students.  Keywords: personalization, mathematics, e-learning, learning management system.

scholarly journals New Weighted Clustering Approach to Map and Prioritise Learning Knowledge Objects towards Learning Approaches

2016 ◽  
Vol 11 (06) ◽  
pp. 28
Author(s):  
Sai Sabitha ◽  
Deepti Mehrotra ◽  
Abhay Bansal
Keyword(s):  
Management System ◽  
Learning Experience ◽  
Learning Management System ◽  
Feature Space ◽  
Learning Objects ◽  
Learning Approaches ◽  
Course Content ◽  
E Learning ◽  
Knowledge Objects ◽  
Learning Management

To have a unique learning experience and a high learning impact, diverse courses should be incorporated in e-Learning. Learning Management System, a tool in e-Learning manages and delivers content to users. Learning Objects (LO), the course content is the fundamental unit of Learning Management System. Knowledge Object of Knowledge Management System can also be a viable resource in technology supported learning. A learning scenario for a given learner has to be identified. The course content (LO) has to match their learning skills. Data mining techniques can be widely used to find similar objects and K-Mean clustering technique can be used to produce more consistent clusters. The clusters can have strong and similar concepts of Learning Knowledge Objects. A new algorithm, a weighted cosine distance that gives real-valued distances between instances which further modifies the structure of the feature space is used for prioritising objects in clusters. These objects can be further mapped to learning approaches of the users. An experiment is conducted by using Learning and Knowledge Objects to understand the effectiveness of the weighted measure, thereby a personalized holistic learning environment is provided to the learners.

M-Learning through Semantically Annotated Learning Objects and Ontologies

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Reshmy Krishnan
Keyword(s):  
Semantic Web ◽  
Learning Process ◽  
Rapid Development ◽  
Learning Objects ◽  
Learning System ◽  
Learning Object ◽  
Mobile Technologies ◽  
Rich Medium ◽  
Object Structure ◽  
E Learning

Number of mobile subscriptions has increased tremendously due to rapid development of mobile technologies. The performance and accessibility of the e-learning process can be enhanced through mobile devices which is called m-learning. M-learning makes learning resources available anywhere and anytime, provide strong search capabilities, and offers easy interaction features to the learners. M-learning also points the opportunity for interoperability than existing e-learning system. The integration of semantic web in m-learning can improve the efficiency of searching for learning objects and reduce the time and cost of learning process. Semantic web can be integrated with the help of ontologies and learning objects in semantic web. They offer rich medium to assist m-learning via semantic annotated learning objects and shared repositories. Two types of ontologies, such as learning object content ontology and learning object structure ontology are used in this system. These ontologies facilitate the reuse, sharing and retrieval of relevant learning objects which are the backbone of m-learning.

Ontologies in Intelligent Learning Systems

2012 ◽  
pp. 31-48
Author(s):  
Boryana Deliyska ◽  
Peter Manoilov
Keyword(s):  
Semantic Web ◽  
Learning Process ◽  
Learning Objects ◽  
Learning Systems ◽  
Learning Object ◽  
Structural Learning ◽  
Principal Role ◽  
Web Resources ◽  
Human Tutor ◽  
E Learning

The intelligent learning systems provide a direct customized instruction to the learners without intervention of human tutor on the base of Semantic Web resources. The principal role ontologies play in these systems is as an instrument for modeling learning process, learner, learning objects, and resources. In the chapter, a variety of relationships and conceptualizations of ontologies used in the intelligent learning systems are investigated. The utilization of domain and application ontologies in learning object building and knowledge acquisition is represented. The conceptualization of domain ontologies in e-learning is presented by the upper levels of its taxonomies. Moreover, a method and an algorithm intended for generation of application ontologies of structural learning objects (curriculum, syllabus, topic plan, etc.) are developed. Examples of curriculum and syllabus application ontologies are given. Further these application ontologies are used for structural learning object generation.

Valuing Learning Objects Shared in an Online Community

2014 ◽  
pp. 529-549
Author(s):  
Jacqueline Guzmán ◽  
Regina Motz ◽  
Alberto Rodrigues da Silva
Keyword(s):  
Social Network ◽  
Online Community ◽  
Learning Objects ◽  
Learning Object ◽  
Learning Platform ◽  
E Learning ◽  
The Creation

In this chapter, the authors analyze and discuss how the activity inside a social network impacts on the value of a Learning Object (LO) used in a collaborative e-learning platform. Recent works propose metrics for measuring LO reusability based on a variety of approaches. In this work, they combine and extend these approaches in order to design a valuation strategy which helps to identify the usage of LOs inside a social network. Their proposal is to identify the factors that are relevant for the valuation of a LO and determine which of them can be computed automatically from its context of usage, the level of success of its authors and its metadata. The authors’ analysis was performed on a particular social network called LOP (LO Poll) system, which strongly motivates the creation and collaborative valuation of LOs. They present preliminary conclusions obtained from an experiment performed in order to analyze the feasibility of the proposal.

A Low-Cost Learning Object Repository for Egyptian Teachers

2013 ◽  
pp. 307-321
Author(s):  
Alaa Sadik
Keyword(s):  
Low Cost ◽  
Learning Objects ◽  
Learning Object ◽  
Web Based ◽  
Learning Programs ◽  
E Learning ◽  
Learning Object Repository ◽  
User Groups ◽  
Arabic Speaking ◽  
Quality Learning

Within the last five years, governments and education authorities worldwide have developed and implemented approaches to facilitate access to a wide range of quality digital resources and reduce the costs of production. This chapter reports on a study which invited school teachers and university academics in Egypt, as a developing and Arabic-speaking country, to cooperate in establishing a learning object repository to store, locate, and share quality learning objects for class teaching and e-learning programs. The proposed solution is originally a vendor hosted web-based groupware, file management, and sharing system that meets the basic criteria of instructional learning object repositories called eStudio. Motivators and inhibitors to using the repository, factors that determine locating, using, and sharing learning objects within the repository and their qualities are assessed to help in developing repositories that demonstrate an understanding of the existing needs and the work practices of Egyptian teachers and other user groups.

scholarly journals Generation of reusable learning objects from digital medical collections: An analysis based on the MASMDOA framework

2021 ◽  
Vol 27 (1) ◽  
pp. 146045822097758
Author(s):  
Félix Buendía ◽  
Joaquín Gayoso-Cabada ◽  
José-Luis Sierra
Keyword(s):  
Medical Students ◽  
Medical Knowledge ◽  
Learning Objects ◽  
Instructional Materials ◽  
Learning Object ◽  
User Profiles ◽  
Knowledge Sources ◽  
Reusable Learning Objects ◽  
E Learning ◽  
Learning Platforms

Learning Objects represent a widespread approach to structuring instructional materials in a large variety of educational contexts. The main aim of this work consists of analyzing the process of generating reusable learning objects followed by Clavy, a tool that can be used to retrieve data from multiple medical knowledge sources and reconfigure such sources in diverse multimedia-based structures and organizations. From these organizations, Clavy is able to generate learning objects that can be adapted to various instructional healthcare scenarios with several types of user profiles and distinct learning requirements. Moreover, Clavy provides the capability of exporting these learning objects through standard educational specifications, which improves their reusability features. The analysis proposed is conducted following criteria defined by the MASMDOA framework for comparing and selecting learning object generation methodologies. The analysis insights highlight the importance of having a tool to transfer knowledge from the available digital medical collections to learning objects that can be easily accessed by medical students and healthcare practitioners through the most popular e-learning platforms.

scholarly journals Platforms for Online Learning: A Product Specification

2020 ◽  
Vol 7 (3) ◽  
pp. 112
Author(s):  
Gerardo Quiroz Vieyra ◽  
Luis Fernando Muñoz González
Keyword(s):  
Artificial Intelligence ◽  
Information And Communication Technologies ◽  
Content Management ◽  
Learning Objects ◽  
Management Systems ◽  
Current Status ◽  
Cognitive Computing ◽  
Information And Communication ◽  
E Learning ◽  
Learning Platforms

Learning Management Systems (LMS) or Learning Content Management Systems (LCMS) are the core of e-learning platforms and have evolved according to the development of new information and communication technologies. In this type of software there are many products on the market, some developed by the institutions themselves (in-house), others are free and open source software (FOSS) and others are more commercial, varying in functionality and technology, but almost always adhering to the standards used in e-learning so that learning objects fulfill their purpose of being usable and reusable. This paper introduces you to current LMS / LCMS, main functions, distinctive features, related standards, and their current status. Then there is a presentation of Machine Learning as a branch of Artificial Intelligence and Cognitive Computing as a fusion discipline between computation, cognition, psychology and artificial intelligence, to end in a proposal for the incorporation of these technologies in a new generation of e-learning platforms, all in an integrated framework of interoperability and governance.

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