scholarly journals Deploying an e-Learning Environment in Zanzibar: A Short Guide

2020 ◽  
Author(s):  
Caspar Groeneveld ◽  
Elia Kibga ◽  
Tom Kaye
Keyword(s):  
Learning Environment ◽  
World Bank ◽  
Virtual Learning Environment ◽  
Learning System ◽  
Digital Content ◽  
Key Factors ◽  
The Third ◽  
Learning Platform ◽  
The World Bank ◽  
E Learning

In April 2020, the MoEVT and the World Bank approached the EdTech Hub to explore the feasibility of implementing a Virtual Learning Environment (VLE). The parties agreed on three deliverables to support this work. 1. A practical and actionable report analysing key factors to be considered in deploying an e-learning platform in Zanzibar. 2. A report documenting the process of sourcing appropriate digital content, aligning this content with the curriculum and populating the e-learning system accordingly. 3. An implementation plan to guide the deployment of an e-learning system in Zanzibar. This presentation deck is the third deliverable.

Authentic and Situated Learning with the Use of an Adaptive Search Engine and a QR-Code in Mobile Mode

2013 ◽  
Vol 4 (3) ◽  
pp. 19-30
Author(s):  
Orlando De Pietro
Keyword(s):  
Learning Environment ◽  
Knowledge Base ◽  
Search Engine ◽  
Situated Learning ◽  
Authentic Learning ◽  
Virtual Learning Environment ◽  
Qr Code ◽  
Adaptive Search ◽  
Learning Platform ◽  
E Learning

The paper presents a technique of interrogation, in mobile technology, of a knowledge base contained in an e-Learning platform. The query is done through the integrated use of an adaptive search engine (ASE) and QR codes. The QR-Code are used to label objects in real environments of cultural matter (eg: museums, art galleries, archaeological sites, etc.). These objects can then be analyzed in more detail during a real learning activity (situated learning and authentic learning). The knowledge base of the virtual learning environment (VLE), is interrogated through a mobile device (smartphone or tablet) which, through an appropriate decoder software, interprets the instructions contained in a QR label previously positioned on the object actually observed by the learner (eg, during a visit to a museum). ASE combines to the data contained in the QR-Code those relating to the user who performs the query (previously recognized via the log-in on the e-Learning platform), therefore, extracts information about the observed object, adapting to the profile of the user-learner. With the help of these tools the learner can expand his real learning experience, while interacting with a virtual learning environment. In this way, situated and authentic learning activities can be upgraded and virtualized, maturing a significative educational experience with the use of intuitive and user friendly digital tools.

Cloud Based e-Learning Platform: An Effective Virtual Learning Environment for Higher Education Institutions

2020 ◽  
Vol 17 (9) ◽  
pp. 4585-4592
Author(s):  
Nidhi Gupta ◽  
Neeraj Sharma ◽  
Sanjay Sood
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Developed Countries ◽  
Virtual Learning Environment ◽  
Learning System ◽  
Education Standards ◽  
Web Based ◽  
Learning Platform ◽  
E Learning ◽  
Teaching Learning

The teaching-learning process, especially in higher education has always been a matter of great concern in developing countries as it makes the nation’s youth capable and is a mainstay towards its development. With the introduction of ICT, it has become even more important to change the learning methodology using the latest technologies like e-Learning, m-Learning, Cloud Computing etc., to match with the education standards of developed countries. This aim of this paper is to provide an insight about the use of e-Learning and cloud computing in HEIs. The paper also discusses the various cloud based adoption technologies used for HEIs and illustrates the comparative analysis of the web based and cloud based e-Learning system.

scholarly journals Users-Centric Adaptive Learning System Based on Interval Type-2 Fuzzy Logic for Massively Crowded E-Learning Platforms

2016 ◽  
Vol 6 (2) ◽  
pp. 81-101 ◽  
Author(s):  
Khalid Almohammadi ◽  
Hani Hagras ◽  
Daniyal Alghazzawi ◽  
Ghadah Aldabbagh
Keyword(s):  
Fuzzy Logic ◽  
Learning Environment ◽  
Adaptive Learning ◽  
Learning System ◽  
Superior Performance ◽  
Teaching Models ◽  
Learning Platform ◽  
E Learning ◽  
Interval Type

Abstract Technological advancements within the educational sector and online learning promoted portable data-based adaptive techniques to influence the developments within transformative learning and enhancing the learning experience. However, many common adaptive educational systems tend to focus on adopting learning content that revolves around pre-black box learner modelling and teaching models that depend on the ideas of a few experts. Such views might be characterized by various sources of uncertainty about the learner response evaluation with adaptive educational system, linked to learner reception of instruction. High linguistic uncertainty levels in e-learning settings result in different user interpretations and responses to the same techniques, words, or terms according to their plans, cognition, pre-knowledge, and motivation levels. Hence, adaptive teaching models must be targeted to individual learners’ needs. Thus, developing a teaching model based on the knowledge of how learners interact with the learning environment in readable and interpretable white box models is critical in the guidance of the adaptation approach for learners’ needs as well as understanding the way learning is achieved. This paper presents a novel interval type-2 fuzzy logic-based system which is capable of identifying learners’ preferred learning strategies and knowledge delivery needs that revolves around characteristics of learners and the existing knowledge level in generating an adaptive learning environment. We have conducted a large scale evaluation of the proposed system via real-word experiments on 1458 students within a massively crowded e-learning platform. Such evaluations have shown the proposed interval type-2 fuzzy logic system’s capability of handling the encountered uncertainties which enabled to achieve superior performance with regard to better completion and success rates as well as enhanced learning compared to the non-adaptive systems, adaptive system versions led by the teacher, and type-1-based fuzzy based counterparts.

scholarly journals Deploying an e-Learning Environment in Zanzibar: Feasibility Assessment

2020 ◽  
Author(s):  
Caspar Groeneveld ◽  
Elia Kibga ◽  
Tom Kaye
Keyword(s):  
Learning Environment ◽  
Virtual Learning Environment ◽  
Ministry Of Education ◽  
Feasibility Assessment ◽  
The World Bank ◽  
The Status ◽  
E Learning ◽  
Short And Long Term ◽  
Ict Infrastructure

The Zanzibar Ministry of Education and Vocational Training (MoEVT) and the World Bank (the Bank) approached the EdTech Hub (the Hub) in April 2020 to explore the feasibility of implementing a Virtual Learning Environment (VLE). The Hub was requested to focus primarily on the deployment of a VLE in lower secondary education, and this report consequently focuses primarily on this group. The report is structured in four sections: An introduction to provide the background and guiding principles for the engagement with a short overview of the methodology applied.  An analysis of the Zanzibar education system with a particular focus on elements relevant to deploying a VLE. This includes the status of ICT infrastructure, and a summary of the stakeholders who will play a role in using or implementing a VLE.  A third section that discusses types of VLEs and content organisation, and their applicability to the Zanzibar ecosystem.  A conclusion with recommendations for Zanzibar, including short- and long-term steps. In this collaboration with Zanzibar’s MoEVT, the Hub team sought to understand the purpose of the proposed VLE. Based on discussions and user scenarios, we identified two main education challenges a VLE may help to resolve. In the short term, students cannot go to school during the COVID-19 crisis, but need access to educational content. There is content, but no flexible and versatile platform to disseminate content to all students. In the long term, a mechanism to provide students with access to quality, curriculum-aligned content in school, or remotely, is required.

scholarly journals Enhancing Student Engagement in VLE Platform: Student Perceptions Towards Programming Course Learning Resources

2021 ◽  
Vol 58 (1) ◽  
pp. 5607-5612
Author(s):  
Abu Hassan Darusman, Yuhanis Omar
Keyword(s):  
Student Engagement ◽  
Learning Environment ◽  
Student Perceptions ◽  
Teaching And Learning ◽  
Preliminary Investigation ◽  
Virtual Learning Environment ◽  
Learning Resources ◽  
Learning Platform ◽  
E Learning ◽  
Level Of Motivation

For many years, e-learning is one of the topics of interest among academia. The increase of wireless devices and smartphone usage as the current technology and platform to access internet services plays an important role in e-learning to be used in teaching and learning activities. Virtual Learning Environment (VLE) is a web-based system designed to facilitate e-learning with various elements in it. However, one of the biggest challenges in implementing e-learning with an efficient and effective learning resources component is the lack of motivation and student engagement in using it continuously. Therefore, the objective of this study is to obtain the students' perceptions as well as suggestions about learning resources in VLE that can be used to raise their level of motivation and engagement in the e-learning environment. This paper aims to discuss the findings of preliminary investigation related to the elements or characteristics of learning resources that can fulfill the need of the students in their studies at university. This study used a qualitative approach by interviewing a group of 60 students to; (1) obtain students’ perceptions on the existing learning resources, (2) identify the issues or challenges in using the existing learning resources, and (3) record the suggestions that can be considered to improve the learning resources in VLE to make them motivated and engaged to the e-learning platform continuously.  The results in a form of suggestions can be used as a guideline for academia to improve their learning resources.

scholarly journals An Integrated Model to Enhance Virtual Learning Environments with Current Social Networking Perspective

2018 ◽  
Vol 13 (09) ◽  
pp. 252 ◽  
Author(s):  
Kashif Laeeq ◽  
Zulfiqar Ali Memon
Keyword(s):  
Learning Environment ◽  
Social Networking ◽  
Social Networking Sites ◽  
Virtual Learning ◽  
Integrated Model ◽  
Virtual Learning Environment ◽  
Web Based ◽  
Learning Platform ◽  
Web Based Learning ◽  
E Learning

A Virtual Learning Environment (VLE) is an accumulation of incorporated soft-ware components, empowering the administration of web-based learning (online learning, e-learning). The quality of VLE is indispensable for the accomplishment of e-learning goals and responsible to engage students during web based learning. The attributes of existing VLES does not completely meet with the requirements of today’s e-learning. Consequently, decreases students’ interest, participation and engagement with web-based e-learning. In contrast, the learners’ engagement and participation are higher in social networking sites (SNS). For this reason, many researchers believe that the inclusion of features, similar to SNSs, in VLE may in-crease its effectivity. The goal of this research article is to investigate existing e-learning platform and make a room for SNSs and online tools for e-learning. The paper proposes an integrated model to enhance existing e-learning environment by incorporating the strength of SNSs and other potential tools with VLEs. This re-search article will provide a good direction and new thoughts for the researchers of technology supported learning-domain.

scholarly journals Adaptive Virtual Learning Environment based on Learning Styles for Personalizing E-learning System: Design and Implementation

2020 ◽  
Vol 8 (6) ◽  
pp. 3398-3406
Keyword(s):  
Learning Environment ◽  
Learning Styles ◽  
User Interfaces ◽  
Adaptive Learning ◽  
Architectural Design ◽  
Virtual Learning ◽  
Virtual Learning Environment ◽  
Learning System ◽  
Course Content ◽  
E Learning

Most virtual learning environment fails to recognize that students have different needs when it comes to learning. With the evolving characteristics and tendencies of students, these learning environments must provide adaptation and personalization features for adaptive learning materials, course content and navigational designs to support student’s learning styles. Based from the data mining results of learner behavioral features of five hundred seven (507) tertiary students, an accurate model for classification of student’s learning styles were derived using J48 decision tree algorithm. The model was implemented in a prototype using a framework and a proposed system architectural design of an adaptive virtual learning environment. The study resulted in the development of an adaptive virtual learning environment prototype where learner’s preferences are dynamically diagnosed to intelligently personalize the course content design and user interfaces for them.

The Construction of a Personalised and Social U-Learning Environment for Third Level Education

2012 ◽  
Vol 2 (3) ◽  
pp. 45-56
Author(s):  
Olapeju Latifat Ayoola ◽  
Eleni Mangina
Keyword(s):  
Learning Environment ◽  
Learning Environments ◽  
Adaptive Learning ◽  
Learning Experience ◽  
Learning System ◽  
Ubiquitous Learning ◽  
The Third ◽  
Learning Platform ◽  
The University ◽  
Ubiquitous Learning Environment

This paper presents a ubiquitous learning (u-learning) system, the “Personalised Ubiquitous Learning Platform” (PULP), which integrates collaborative and social learning for the enhancement of the third level educational learning experience. University College Dublin (UCD) provides its students with managed learning environments (MLEs) and adaptive learning via UCD Horizon which enables students to take different courses from different colleges throughout the university. The main objective of this platform is to complement the current MLEs with a single supported intelligent and personalised ubiquitous learning environment that will promote and make provisions for adaptive and collaborative learning, human computer interaction on mobile and desktop clients anywhere and anytime. The system aims to enhance the students’ learning experience in third level educational environment by employing personalisation techniques such as the agent-oriented recommendation technique to engage students and help them access the content material for their studies.

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