Sins of omission: Critical informatics perspectives on privacy in e‐learning systems in higher education

2021 ◽  
Author(s):  
Britt Paris ◽  
Rebecca Reynolds ◽  
Catherine McGowan
Keyword(s):  
Higher Education ◽  
Learning Systems ◽  
E Learning

E-Learning and the Semantic Web

2015 ◽  
pp. 66-100 ◽  
Author(s):  
Raadila Bibi Mahmud Hajee Ahmud-Boodoo
Keyword(s):  
Higher Education ◽  
Semantic Web ◽  
Success Factors ◽  
Comprehensive Analysis ◽  
Learning Systems ◽  
Education Sector ◽  
Learning Models ◽  
Semantic Web Technology ◽  
Critical Success ◽  
E Learning

A number of 3.0 e-learning systems have been proposed in the literature to capture the numerous benefits that the Semantic Web has to offer to the higher education sector. These 3.0 e-learning systems identify some essential Semantic Web characteristics that are either discussed as stand-alone factors or tend to revolve around the complexities of the Semantic Web technology and its implementation, often disregarding users' needs. Conversely, a comprehensive analysis of e-learning models for higher education in the literature revealed several Critical Success Factors (CSFs) that are relevant to the Semantic Web but often overlooked in 3.0 e-learning models. Consequently, this chapter provides an overview of the CSFs of e-learning relevant to 3.0 e-learning systems as well as an overview of the main Semantic Web characteristics for e-learning to define a new and combined set of 3.0 e-learning characteristics that will holistically represent 3.0 e-learning systems capturing the needs and expectations of users. The new initial 3.0 e-learning model proposed is evaluated within the higher education sector in Mauritius.

Harnessing Cloud Computing Services for E-Learning Systems in Higher Education

2019 ◽  
Vol 15 (2) ◽  
pp. 18-30
Author(s):  
Abderrahim El Mhouti ◽  
Mohamed Erradi
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Learning Systems ◽  
Learning And Teaching ◽  
Computing Services ◽  
E Learning ◽  
Cloud Computing Services ◽  
Learning Platforms ◽  
Basic Infrastructure ◽  
Common Architecture

The use of e-learning suggests the use of ICT to enhance the quality of learning and teaching. However, many higher education institutions, does not have e-learning platforms, resources and infrastructure necessary to implement this type of training. This is due to the need for high cost of basic infrastructure and applications challenges related projects it has to face. This article puts forward an overview on what is the current state of the use of cloud computing in e-learning in higher education context, where the use of computers is increasingly intensive. The article analyzes e-learning systems challenges and trends, the convenience of cloud computing for e-learning and the key benefits of e-learning on the cloud. The article exposes also some application solutions using cloud computing in e-learning for higher education, by presenting the most common architecture that has been adopted. Finally, this article discusses issues related to the implementation of cloud-based e-learning systems and presents some potential ways to overcome them.

An m-learning framework for ERP systems in higher education

2014 ◽  
Vol 11 (4) ◽  
pp. 287-301 ◽  
Author(s):  
Brenda Scholtz ◽  
Mando Kapeso
Keyword(s):  
Higher Education ◽  
Success Factors ◽  
Theoretical Framework ◽  
Learning Systems ◽  
Learning System ◽  
Erp Systems ◽  
Content Type ◽  
Erp System ◽  
E Learning ◽  
Learning Projects

Purpose – The purpose of this paper is to investigate the factors of m-learning approaches which can be used for enterprise resource planning (ERP) system training and to propose a theoretical framework for m-learning of ERP systems. Design/methodology/approach – A literature review of several theories relating to success factors for mobile learning (m-learning) and electronic learning (e-learning) are analysed and a theoretical framework of success factors for m-learning of ERP systems is proposed. Two field studies are undertaken to identify the features of e-learning and m-learning systems which users enjoyed and which related to the factors identified in the theoretical framework. The technology acceptance model (TAM) was used to evaluate the acceptance, usefulness and perceived ease of use (PEOU) of the two systems evaluated in the field study, the openSAP e-learning application and the SAP Learn Now m-learning application. Findings – The results confirmed several of the theoretical elements identified in the framework and the m-learning system was rated positively for PEOU and perceived usefulness (PU). The findings confirmed other studies showing the importance of the quality of course content in e-learning and m-learning projects. Research limitations/implications – The empirical study was limited to a small number of participants in higher education. However, a deeper understanding of the factors influencing m-learning for ERP systems was obtained. Practical implications – The study provides a valuable practical contribution because the framework can be used in the improved design of an ERP m-learning approach, which in turn can lead to an improvement in ERP training and education programmes and ultimately ERP project success. Originality/value – Several studies propose the use of m-learning systems. However, research related to the factors impacting on m-learning projects for ERP system training is limited. The paper presents original work and the results provide a valuable contribution to several theories of m-learning.

E-Learning and the Semantic Web

2016 ◽  
pp. 24-55
Author(s):  
Raadila Bibi Mahmud Hajee Ahmud-Boodoo
Keyword(s):  
Higher Education ◽  
Semantic Web ◽  
Success Factors ◽  
Comprehensive Analysis ◽  
Learning Systems ◽  
Education Sector ◽  
Learning Models ◽  
Semantic Web Technology ◽  
Critical Success ◽  
E Learning

A number of 3.0 e-learning systems have been proposed in the literature to capture the numerous benefits that the Semantic Web has to offer to the higher education sector. These 3.0 e-learning systems identify some essential Semantic Web characteristics that are either discussed as stand-alone factors or tend to revolve around the complexities of the Semantic Web technology and its implementation, often disregarding users' needs. Conversely, a comprehensive analysis of e-learning models for higher education in the literature revealed several Critical Success Factors (CSFs) that are relevant to the Semantic Web but often overlooked in 3.0 e-learning models. Consequently, this chapter provides an overview of the CSFs of e-learning relevant to 3.0 e-learning systems as well as an overview of the main Semantic Web characteristics for e-learning to define a new and combined set of 3.0 e-learning characteristics that will holistically represent 3.0 e-learning systems capturing the needs and expectations of users. The new initial 3.0 e-learning model proposed is evaluated within the higher education sector in Mauritius.

Harnessing Cloud Computing Services for E-Learning Systems in Higher Education

2021 ◽  
pp. 1466-1480
Author(s):  
Abderrahim El Mhouti ◽  
Mohamed Erradi
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Learning Systems ◽  
Learning And Teaching ◽  
Computing Services ◽  
E Learning ◽  
Cloud Computing Services ◽  
Learning Platforms ◽  
Basic Infrastructure ◽  
Common Architecture

The use of e-learning suggests the use of ICT to enhance the quality of learning and teaching. However, many higher education institutions, does not have e-learning platforms, resources and infrastructure necessary to implement this type of training. This is due to the need for high cost of basic infrastructure and applications challenges related projects it has to face. This article puts forward an overview on what is the current state of the use of cloud computing in e-learning in higher education context, where the use of computers is increasingly intensive. The article analyzes e-learning systems challenges and trends, the convenience of cloud computing for e-learning and the key benefits of e-learning on the cloud. The article exposes also some application solutions using cloud computing in e-learning for higher education, by presenting the most common architecture that has been adopted. Finally, this article discusses issues related to the implementation of cloud-based e-learning systems and presents some potential ways to overcome them.

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