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.

Higher education student engagement in times of pandemic: the role of e-learning system usability and teacher behavior

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Khalid Abed Dahleez ◽  
Ayman A. El-Saleh ◽  
Abrar Mohammed Al Alawi ◽  
Fadi Abdelmuniem Abdelfattah
Keyword(s):  
Higher Education ◽  
Student Engagement ◽  
Cognitive Engagement ◽  
Teacher Behavior ◽  
Learning System ◽  
Emotional Engagement ◽  
Education Student ◽  
Content Type ◽  
System Usability ◽  
E Learning

PurposeThis research examined the factors affecting several types of student engagement, namely agentic, behavioral, emotional and cognitive engagement. Specifically, it examined the effect of e-learning system usability on student engagement and explored teacher behavior's possible intervening impact on this relationship.Design/methodology/approachData were collected from 418 students studying at different specializations at Omani private academic institutions. This study employed a quantitative methodology and utilized the Smart-PLS for data analyses.FindingsThe findings showed that e-learning system usability influenced significantly and positively agentic, behavioral and cognitive engagement. However, the link between e-learning system usability and emotional engagement was not significant. Moreover, teacher behavior mediated the relationship between e-learning system usability and the four types of engagement.Originality/valueThis study improves one’s understanding of how the interaction of e-learning system usability and teacher behavior affects several aspects of student engagement. It also helps higher education administrators and policymakers by exploring the influential effects of e-learning systems usability and teacher behavior on facilitating students' engagement.

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.

A sustainable quality assessment model for the information delivery in E-learning systems

2018 ◽  
Vol 46 (1) ◽  
pp. 1-25 ◽  
Author(s):  
Shahid Farid ◽  
Rodina Ahmad ◽  
Mujahid Alam ◽  
Atif Akbar ◽  
Victor Chang
Keyword(s):  
Quality Assessment ◽  
State Of The Art ◽  
Statistical Tests ◽  
Information Delivery ◽  
Learning Systems ◽  
Learning System ◽  
Assessment Model ◽  
Content Type ◽  
E Learning

Purpose The purpose of this study is to propose a sustainable quality assessment approach (model) for the e-learning systems keeping software perspective under consideration. E-learning is becoming mainstream due to its accessibility, state-of-the-art learning, training ease and cost effectiveness. However, the poor quality of e-learning systems is one of the major causes of several failures reported. Moreover, this arena lacks well-defined quality assessment measures. Hence, it is quite difficult to measure the overall quality of an e-learning system effectively. Design/methodology/approach A pragmatic mixed-model philosophy was adopted for this study. A systematic literature review was performed to identify existing e-learning quality models and frameworks. Semi-structured interviews were conducted with e-learning experts following empirical investigations to identify the crucial quality characteristics of e-learning systems. Various statistical tests like principal component analysis, logistic regression, chi-square and analysis of means were applied to analyze the empirical data. These led to an adequate set of quality indicators that can be used by higher education institutions to assure the quality of e-learning systems. Findings A sustainable quality assessment model for the information delivery in e-learning systems in software perspective has been proposed by exploring the state-of-the-art quality assessment/evaluation models and frameworks proposed for the e-learning systems. The proposed model can be used to assess and improve the process of information discovery and delivery of e-learning. Originality/value The results obtained led to conclude that very limited attention is given to the quality of e-learning tools despite the importance of quality and its effect on e-learning system adoption and promotion. Moreover, the identified models and frameworks do not adequately address quality of e-learning systems from a software perspective.

An integrated framework for ERP system implementation

2017 ◽  
Vol 25 (1) ◽  
pp. 91-109 ◽  
Author(s):  
Kalinga Jagoda ◽  
Premaratne Samaranayake
Keyword(s):  
Enterprise Resource Planning ◽  
Critical Success Factors ◽  
Success Factors ◽  
Resource Planning ◽  
System Implementation ◽  
Erp Systems ◽  
Erp Implementation ◽  
Content Type ◽  
Erp System ◽  
Critical Success

Purpose The purpose of this paper is to propose an alternative integrated approach based on the stage-gate method to implement enterprise resource planning (ERP) systems which will enhance the effectiveness of ERP projects. Design/methodology/approach A literature review was conducted on ERP system implementation and its effectiveness. The need for improving implementation approaches and methodologies was examined. Based on the insights gained, a conceptual framework for ERP system implementation is presented by combining the state-gate approach with the pre-implementation roadmap. Findings The proposed framework aims to enhance the overall ERP implementation outcomes, ensuring critical success factors and eliminating common causes of failures. A pre-implementation roadmap is identified as a key element for eliminating many causes of failure including lack of organisations’ readiness for ERP. The post-implementation stage can be used for further improvements to the system through internal research and development. Research limitations/implications The development of the framework is an attempt to contribute to improving ERP implementation. This research is expected to motivate researchers to work in this area, and it will be beneficial to practicing managers in the identification of opportunities for improvements in ERP systems. Case studies will be valuable to refine and validate the proposed model. Originality/value This paper explores research in a needy area and offers a framework to help researchers and practitioners in improving ERP implementation. This framework is expected to reduce the implementation project duration, strengthen critical success factors and minimise common problems of ERP implementation projects.

Will personalized e-Learning increase deep learning in higher education?

2019 ◽  
Vol 47 (1) ◽  
pp. 53-63 ◽  
Author(s):  
María Consuelo Sáiz-Manzanares ◽  
César Ignacio García Osorio ◽  
José Francisco Díez-Pastor ◽  
Luis Jorge Martín Antón
Keyword(s):  
Higher Education ◽  
Student Satisfaction ◽  
Learning Outcomes ◽  
Teaching Practice ◽  
Learning Management Systems ◽  
Learning System ◽  
Management Systems ◽  
Content Type ◽  
E Learning ◽  
Learning Management

PurposeRecent research in higher education has pointed out that personalized e-learning through the use of learning management systems, such as Moodle, improves the academic results of students and facilitates the detection of at-risk students.Design/methodology/approachA sample of 124 students following the Degree in Health Sciences at the University of Burgos participated in this study. The objectives were as follows: to verify whether the use of a Moodle-based personalized e-learning system will predict the learning outcomes of students and the use of effective learning behaviour patterns and to study whether it will increase student satisfaction with teaching practice.FindingsThe use of a Moodle-based personalized e-learning system that included problem-based learning (PBL) methodology predicted the learning outcomes by 42.3 per cent, especially with regard to the results of the quizzes. In addition, it predicted effective behavioural patterns by 74.2 per cent. Increased student satisfaction levels were also identified through the conceptual feedback provided by the teacher, arguably because it facilitated a deeper understanding of the subject matter.Research limitations/implicationsThe results of this work should be treated with caution, because of the sample size and the specificity of the branch of knowledge of the students, as well as the design type. Future studies will be directed at increasing the size of the sample and the diversity of the qualifications.Originality/valueLearning methodology in the twenty-first century has to be guided towards carefully structured work from the pedagogic point of view in the learning management systems allowing for process-oriented feedback and PBL both included in personalized e-learning systems.

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.

Adaptation algorithms for selecting personalised learning experience based on learning style and dyslexia type

2019 ◽  
Vol 53 (2) ◽  
pp. 189-200 ◽  
Author(s):  
Aisha Yaquob Alsobhi ◽  
Khaled Hamed Alyoubi
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning Experience ◽  
Assistive Technologies ◽  
Learning Systems ◽  
Learning System ◽  
Fixed Cost ◽  
Learning Material ◽  
Content Type ◽  
E Learning

PurposeThrough harnessing the benefits of the internet, e-learning systems provide flexible learning opportunities that can be delivered at a fixed cost at a time and place to suit the user. As such, e-learning systems can allow students to learn at their own pace while also being suitable for both distance and classroom-based learning activities. Adaptive educational hypermedia systems are e-learning systems that employ artificial intelligence. They deliver personalised online learning interventions that extend electronic learning experiences beyond a mere computerised book through the use of intelligence that adapts the content presented to a user according to a range of factors including individual needs, learning styles and existing knowledge. The purpose of this paper is to describe a novel adaptive e-learning system called dyslexia adaptive e-learning management system (DAELMS). For the purpose of this paper, the term DAELMS will be employed to describe the overall e-learning system that incorporates the required functionality to adapt to students’ learning styles and dyslexia type.Design/methodology/approachThe DAELMS is a complex system that will require a significant amount of time and expertise in knowledge engineering and formatting (i.e. dyslexia type, learning styles, domain knowledge) to develop. One of the most effective methods of approaching this complex task is to formalise the development of a DAELMS that can be applied to different learning styles models and education domains. Four distinct phases of development are proposed for creating the DAELMS. In this paper, we will discuss Phase 3 which is the implementation and some adaption algorithms while in future papers will discuss the other phases.FindingsAn experimental study was conducted to validate the proposed generic methodology and the architecture of the DAELMS. The system has been evaluated by group of university students studying a Computer Science related majors. The evaluation results proves that when the system provide the user with learning materials matches their learning style or dyslexia type it enhances their learning outcomes.Originality/valueThe DAELMS correlates each given dyslexia type with its associated preferred learning style and subsequently adapts the learning material presented to the student. The DAELMS represents an adaptive e-learning system that incorporates several personalisation options including navigation, structure of curriculum, presentation, guidance and assistive technologies that are designed to ensure the learning experience is directly aligned with the user's dyslexia type and associated preferred learning style.

scholarly journals The research trends in recommender systems for e-learning

2019 ◽  
Vol 14 (1) ◽  
pp. 12-27
Author(s):  
Jiemin Zhong ◽  
Haoran Xie ◽  
Fu Lee Wang
Keyword(s):  
Learning Outcomes ◽  
Recommender Systems ◽  
Learning Systems ◽  
Learning System ◽  
Future Research ◽  
Content Type ◽  
Evaluation Indicator ◽  
Recommendation Algorithms ◽  
E Learning ◽  
Key Indicators

Purpose A recommendation algorithm is typically applied to speculate on users’ preferences based on their behavioral characteristics. The purpose of this paper is to provide a systematic review of recommendation systems by collecting related journal articles from the last five years (i.e. from 2014 to 2018). This paper aims to study the correlations between recommendation technologies and e-learning systems. Design/methodology/approach The paper reviews the relevant articles using five assessment aspects. A coding scheme was put forward that includes the following: the metrics for the e-learning system, the evaluation metrics for the recommendation algorithms, the recommendation filtering technology, the phases of the recommendation process and the learning outcomes of the system. Findings The research indicates that most e-learning systems will adopt the adaptive mechanism as a primary metric, and accuracy is a vital evaluation indicator for recommendation algorithms. In existing e-learning recommender systems, the most common recommendation filtering technology is hybrid filtering. The information collection phase is an important process recognized by most studies. Finally, the learning outcomes of the recommender system can be achieved through two key indicators: affections and correlations. Originality/value The recommendation technology works effectively in closing the gap between the information producer and the information consumer. This technology could help learners find the information they are interested in as well as send them a valuable message. The opportunities and challenges of the current study are discussed; the results of this study could provide a guideline for future research.

scholarly journals Investigating a theoretical framework for e-learning technology acceptance

2020 ◽  
Vol 10 (6) ◽  
pp. 6484 ◽  
Author(s):  
Barween Al Kurdi ◽  
Muhammad Alshurideh ◽  
Said A. Salloum
Keyword(s):  
University Students ◽  
Technology Acceptance ◽  
Theoretical Framework ◽  
Ease Of Use ◽  
Learning Systems ◽  
Perceived Usefulness ◽  
Learning System ◽  
Learning Technology ◽  
Perceived Ease Of Use ◽  
E Learning

E-learning has gained recognition and fame in delivering and distributing educational resources, and the same has become possible with the occurrence of Internet and Web technologies. The research seeks to determine the factors that influence students' acceptance of E-learning and to find out the way these factors determine the students' intention to employ E-learning. A theoretical framework was developed based on the technology acceptance model (TAM). To obtain information from the 270 university students who utilized the E-learning system, a questionnaire was formulated. The results revealed that “social influence, perceived enjoyment, self-efficacy, perceived usefulness, and perceived ease of use” are the strongest and most important predictors in the intention of and students towards E-learning systems. The outcomes offer practical implications for practitioners, lawmakers, and developers in effective E-learning systems implementation to improve ongoing interests and activities of university students in a virtual E-learning atmosphere, valuable recommendations for E-learning practices are given by the research findings, and these may turn out to be as guidelines for the efficient design of E-learning systems.

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