scholarly journals Are university teachers ready to use and adopt e-learning system? An empirical substantiation during COVID–19 pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Soumendra Kumar Patra ◽  
Bijaya Kumar Sundaray ◽  
Durga Madhab Mahapatra
Keyword(s):  
Information And Communication Technologies ◽  
Structural Equation ◽  
Online Teaching ◽  
Learning Systems ◽  
Learning System ◽  
Online Questionnaire ◽  
Content Type ◽  
Technological Support ◽  
University Teachers ◽  
E Learning

Purpose To overcome the spread of the noble coronavirus, the lockdown was imposed on March 25, 2020 by the Government of India which adversely affected the education system in the country and changed the traditional classroom teaching to online teaching. This paper aims to explore the factors encouraging university teachers to use and adopt e-learning systems during the COVID-19 pandemic and to find out the major challenges faced by them in adopting e-learning systems in Odisha, an Indian State. Design/methodology/approach The population of this study was teachers of different universities in Odisha, India. An online questionnaire was administered to collect data from the teachers of the state who were involved in the e-learning system for taking their online classes during the COVID-19 situation. During the study 610 valid responses were processed for data analysis. The results of the analysis were presented through factor analysis, t-test and structural equation model. Findings The findings revealed three major factors as user-friendly, convenient and performance encouraged teachers to use and adopt e-learning systems. The results also identified major challenges such as accessibility to the internet, information and communication technologies literacy and skills and technological support, faced by university teachers in adopting e-learning systems. Research limitations/implications The findings of the study have suggested that the university authorities can develop an effective e-learning system to support their teachers for the continuance of education and learning opportunities. The insights of this study can help the regulatory authorities of higher education to redesign policy and infrastructure for promoting effective e-learning systems. Originality/value Many studies have been conducted in relation to e-learning during COVID-19. However, this is a unique study that identifies supporting factors and addresses the challenges faced by university teachers in adopting an e-learning system.

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 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.

scholarly journals A Model for e-Learning Systems Success: Systems, Determinants, and Performance

2017 ◽  
Vol 12 (10) ◽  
pp. 4 ◽  
Author(s):  
Ismail M. Romi
Keyword(s):  
Information And Communication Technologies ◽  
Learning Systems ◽  
Learning System ◽  
Learning Context ◽  
Learner Performance ◽  
Learning Success ◽  
Proposed Model ◽  
System Components ◽  
E Learning ◽  
And Performance

E-learning is used by higher education institutions and corporate training institutes as a means of solving performance problems, and the accessibility to educational technology which considered as vital for acquisition and dissemination of knowledge to students, as well as interaction between instructors and students. To determine technological solutions for those institutions, an analysis to the literature, and related theories have been conducted depending on the context impact to e-learning system, as well as the interrelationship between e-learning system components and its impact on learner performance. The main findings show that e-learning system is composed of four components, mainly; the instructor, learner, course, and information and communication technologies (ICT), in addition to the context determinants of e-learning system success. The current study, proposed a model for e-learning success, which incorporates eight factors, mainly; e-learning context that include individual, institutional, and environmental determinants to e-learning success. In addition to e-learning components which include instructor, learner, course, and ICT. As well as the learner performance, that aims to measure e-learning success. The proposed model was designed to integrate prior research in the area of e-learning, where it adds set of determinants to e-learning systems success, and find out the best fit of e-learning system components. Moreover, educational institutions can use this proposed model.

How does task-technology fit influence cloud-based e-learning continuance and impact?

2019 ◽  
Vol 61 (4) ◽  
pp. 480-499 ◽  
Author(s):  
Yung-Ming Cheng
Keyword(s):  
Structural Equation ◽  
Educational Institution ◽  
Perceived Usefulness ◽  
Learning System ◽  
Equation Modeling ◽  
Comprehensive University ◽  
Content Type ◽  
E Learning ◽  
Task Technology Fit ◽  
Perceived Impact

Purpose According to expectation–confirmation model (ECM) and task-technology fit (TTF) model, the purpose of this paper is to examine the role of TTF in students’ cloud-based e-learning continuance and evaluate whether TTF affects students’ perceived impact on learning of the cloud-based e-learning system within the educational institution. Design/methodology/approach Sample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 500 questionnaires were distributed in the campus, and 391 (78.2 percent) usable questionnaires were analyzed using structural equation modeling in this study. Findings This study’s results verified that both task characteristics and technology characteristics affected students’ perceived TTF, which significantly contributed to their perceived usefulness, confirmation and satisfaction with the cloud-based e-learning system, and these in turn directly or indirectly led to their continuance intention of the system and perceived impact on learning; essentially, the results strongly supported the research model integrating ECM and TTF model via positioning key constructs as the drivers with all hypothesized links being significant. Originality/value This study contributes to an understanding of the TTF in explaining students’ cloud-based e-learning continuance that is difficult to explain with only their utilitarian perception of the cloud-based e-learning system, and further places considerably more emphasis upon students’ perceived impact on learning greatly driven by their TTF in the system. Thus, this study’s empirical evidence on incorporating ECM and TTF model can shed light on the outcome for cloud-based e-learning continuance and enhance better understanding of a richer post-adoption model.

Embracing educational disruption: a case study in making the shift to a remote learning environment

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ida Fatimawati Adi Badiozaman ◽  
Hugh John Leong ◽  
Wallace Wong
Keyword(s):  
Professional Development ◽  
Online Teaching ◽  
Teaching And Learning ◽  
Online Teaching And Learning ◽  
Content Type ◽  
Technological Support ◽  
Self Reports ◽  
E Learning ◽  
Professional Development Needs ◽  
The Impact

PurposeAs an institution that has invested in e-learning infrastructure and technology for e-learning delivery, Swinburne University of Technology Sarawak conducted The Digital Educator Series as a means of embracing this educational disruption. In particular, this paper reports on the first three courses held under the Digital Educator Series that aims to equip teachers with practical and effective online teaching to school teachers in Sarawak. While the training is still in effect, preliminary results are shared, and implications for practice and recommendations for further research are considered.Design/methodology/approachApproximately 136 questionnaires containing close-and open-ended items were distributed to the teacher participants of the Digital Educator Series. Close-ended items were designed to gather general information about their perceptions of online teaching and learning. Items were constructed to gather insights on familiarity with online teaching and learning, perceived usefulness of platforms such as Microsoft Teams and Google Classrooms. The open-ended items were designed to gather information on areas of improvement for the courses and professional development needs of teachers for online teaching.FindingsThe findings revealed very mixed responses in terms of teachers' familiarity with online teaching and learning. Nonetheless, it was encouraging that the majority of teachers felt positively about the impact and usefulness of the courses in the Digital Educator Series and have expressed that would like to learn more about online teaching pedagogy. Teachers reported the greatest familiarity with Google Classroom and were very positive about the applicability the Google Classroom Course (91.2%) in their own teaching practice. Conversely, all of the participants reported they were unfamiliar with Microsoft Teams. Accordingly, the teachers did not perceive its applicability to be as high as the Google Classroom. The qualitative findings further corroborated this and expressed the need for specific professional development programmes that include pedagogical and technological support. Overall, the teachers are strongly focussed in their professional development in order to improve their online teaching,Research limitations/implicationsLike other research, this too has its limitations. The sample size in this study was restricted to those who attended the Digital Educator Series training. Hence the results of this study, whilst have been enriching, and to a certain extent are supported by the current literature, the accuracy of the description may be unique to this particular group of individuals, within this particular setting. Additionally, the study only relied on self-reports from both the questionnaire and the semi-structured interviews. This study accepts that self-reports have shortcomings. Not all experiences of the courses would have been readily accessible through the teachers' conscious reflections. This makes it difficult to construct a complete picture of the experience, challenges and identify all salient factors within a particular workshop or training.Practical implicationsAlthough the adoption of teaching and learning to online platforms is undoubtedly the way to maintain continuity of learning for students, it has also unveiled glaring inequities in Sarawak. Therefore, continuous and personalised professional development needs to be provided, focussing on pedagogical and technological support. There is a need to embrace these changes as a long-term response that will develop and improve over the next few years. That response should include better infrastructure, policies for quality improvement, accessibility standards and strategic plans for continuous access in the future. This includes advocating for platforms that can fit into the core technology environment and for teachers to adopt an innovative mindset.Originality/valueIn light of the complex and multifaceted challenge of transitioning to online learning in Sarawak Malaysia, it was evident that the need for innovative solutions to optimize educational endeavours has become accelerated. To ensure that students are well-supported and widening participation and access to education, it is imperative that the education disruption be embraced. This starts with addressing teachers' digital literacy through a professional development programme of online reaching.

Digital working during the COVID-19 pandemic: how task–technology fit improves work performance and lessens feelings of loneliness

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Simen Nordbø Abelsen ◽  
Svenn-Helge Vatne ◽  
Patrick Mikalef ◽  
Jyoti Choudrie
Keyword(s):  
Information And Communication Technologies ◽  
Structural Equation ◽  
Work Performance ◽  
Equation Modeling ◽  
Sample Population ◽  
Snowball Sampling ◽  
Online Questionnaire ◽  
Content Type ◽  
Work Related ◽  
Task Technology Fit

PurposeThis study aims to investigate the relationship between information and communication technologies (ICTs) use and work performance during the coronavirus disease 2019 (COVID-19) pandemic. Specifically, it aims to understand what the role of task–technology fit is, and what effect this has on feelings of loneliness of individuals and their subsequent work performance. As a large proportion of workers are required to work from home during the ongoing COVID-19 pandemic, understanding what aspects contribute to higher performance and reduced negative psychological outcomes is of increased practical and research interest.Design/methodology/approachTo explore these questions, a quantitative approach that employed a sample population of 357 individuals who worked from home during the COVID-19 pandemic was used. Using a convenience, purposive and snowball sampling approach the authors collected data through a custom-built online questionnaire, and analyzed the data using structural equation modeling (SEM).FindingsThe results highlight the effect that high task–technology fit has in both directly and indirectly influencing work performance of individuals. The authors find that by designing ICTs based on task–technology fit principles, individuals are less likely to experience feelings of loneliness while working from home and are more prone to perform better in their work-related tasks.Originality/valueThis study offers a new perspective on the role fit of tasks with technology have on influencing psychological states, and indirectly influencing work-related outcomes. The authors, therefore, expand the understanding about why task–technology fit is sought after by explaining part of the psychological mechanisms through which it has an effect on work performance.

Investigating medical professionals' continuance intention of the cloud-based e-learning system: an extension of expectation–confirmation model with flow theory

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yung-Ming Cheng
Keyword(s):  
Structural Equation ◽  
Flow Theory ◽  
Learning System ◽  
Theoretical Development ◽  
Equation Modeling ◽  
Medical Professionals ◽  
Continuance Intention ◽  
Content Type ◽  
E Learning ◽  
Expectation Confirmation

PurposeThe purpose of this study is to propose an integrated model based on expectation–confirmation model (ECM), flow theory and human–organization–technology fit framework to examine whether human, organizational and technology factors as antecedents to medical professionals' beliefs can affect their continuance intention of the cloud-based e-learning system.Design/methodology/approachSample data for this study were collected from medical professionals at five hospitals in Taiwan. A total of 500 questionnaires were distributed, and 368 (73.6%) useable questionnaires were analyzed using structural equation modeling in this study.FindingsSynthetically speaking, human, organizational and technology factors, as antecedents to medical professionals' continuance intention of the cloud-based e-learning system have been examined, and the results strongly support the research model with all hypothesized links being significant.Originality/valueParticularly, it is worth mentioning that the application of capturing both ECM and flow theory for completely explaining three types of factors (i.e. human, organizational and technology factors) as external variables to medical professionals' cloud-based e-learning continuance intention is well documented, that is, information systems (IS) and nonIS determinants are simultaneously evaluated, and extrinsic and intrinsic motivators are both taken into consideration in this study's theoretical development of medical professionals' cloud-based e-learning continuance intention to acquire a more comprehensive and robust analysis.

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.

Measuring E-Learning System Adoption in Universities in Tanzania

2020 ◽  
Vol 9 (2) ◽  
pp. 1-18
Author(s):  
Deogratius Mathew Lashayo
Keyword(s):  
Environmental Factors ◽  
Structural Equation ◽  
Learning Systems ◽  
Learning System ◽  
Clear Understanding ◽  
Perceived Benefits ◽  
Is Success ◽  
Actual Use ◽  
E Learning ◽  
The University

The success of e-learning systems in Tanzania relies on various factors that influence its measurement. Examples of the key factors include trust, environmental factors, and the university readiness. However, influence of these factors towards e-learning systems is not clear. Understanding their impacts and significance helps decision makers and stakeholders in making informed decisions on how to handle them. This study modifies the information systems (IS) success model whereby it adopts 12 factors that had been suggested by this author in his previous study conducted in Open University of Tanzania (OUT) in 2017. A sample of 1,005 students from eight universities in Tanzania was collected. A structural equation modelling was used in data analysis. The results shows trust (T) has positive and significant impact on e-learning actual use (EAU) while environmental factors (EF) had positive and significant impacts on e-learning actual use and perceived benefits, and at the same time, university readiness had a positive and significant impact on perceived benefits (PB).

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.

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