Barriers effecting successful implementation of E-learning in Saudi Arabian universities

advancement of digital technology is influencing the leaping development of various activities in our daily life. E-learning systems has also gained a competitive edge over the prevailing traditional methodology. The prevailing pedagogy is being replaced by the E-learning teaching systems. E-Learning, teaching learning methodology provides more flexibility and allows freedom from time, place, physical presence, hectic, and stressful teaching-learning etc, thus play a vital role in education system. However, there are many barriers in E-Learning methodology for successful teaching-learning. Present research paper attempts to study the various barriers that are affecting the successful implementation of E-Learning in Saudi Arabian Universities. This study reviews various barriers from literature and identified most important E-Learning barriers which are described and grouped in four dimensions such as student, instructor, infrastructure and technology, and institutional management. Sixteen barriers falling under these relevant dimension were validated their importance quantitatively through university students, instructors, and E-Learning staffs of some well known universities in Saudi-Arabia. A survey instrument was developed and tested on a sample of 257 respondents of Saudi Arabian Universities. It was found that infrastructure and technology dimension is the most significant as perceived by respondents. Results of the study also reveal that, all barrier factors are highly reliable, therefore should be taken care for successful implementation of E-learning systems

Structural Equation Modeling for Mobile Learning Acceptance by University Students: An Empirical Study

Advanced mobile devices and global internet services have enhanced the usage of smartphones in the education sector and their potential for fulfilling teaching and learning objectives. The current study is an attempt to assess the factors affecting mobile learning acceptance by Saudi university students. A theoretical model of mobile learning acceptance was developed based on the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT) model. Theoretically, five independent constructs were identified as most contributory towards the use of mobile learning and tested empirically. Data were collected through an online survey and analyzed using SmartPLS. The results of the study indicate that four constructs were significantly associated with mobile learning acceptance: perceived usefulness (β = 0.085, t = 2.201, and p = 0.028), perceived ease of use (β = 0.031, t = 1.688, and p = 0.013), attitude (β = 0.100, t = 3.771, and p = 0.037), and facilitating conditions (β = 0.765, t = 4.319, and p = 0.001). On the other hand, social influence was insignificant (β = −0.061, t = 0.136, and p = 0.256) for mobile learning acceptance. The contribution of social influence towards the use of mobile learning was negative and insignificant; hence, it was neglected. Thus, finally, four constructs (perceived usefulness, perceived ease of use, attitude, and facilitating conditions) were considered as important determinants of mobile learning acceptance by university students

Critical Success Factors (CSFs) for Cloud-based E-Learning

Cloud Computing has become the dominant technology to offer unlimited computing for various social and commercial applications. Cloud computing is also being adopted at the rapid pace for E-Learning. This paper has illustrated upon the phenomenon of Cloud based E-Learning adoption in the institutes of universities and institutes of higher education. Critical success factors for the effective implementing of Cloud Based E-Learning have been identified through systematic literature review using framework of Denyer and Tranfield (2009). Further they are clustered into four dimensions namely cloud service resilience, university technological maturity, university organizational readiness and Cloud Based E-Learning imperatives. The results of this research will be helpful for policymakers and practitioners of E-Learning in implementing Cloud Based E-Learning Platform

Critical Success Factors (CSFs) for Cloud-based E-Learning

Cloud Computing has become the dominant technology to offer unlimited computing for various social and commercial applications. Cloud computing is also being adopted at the rapid pace for E-Learning. This paper has illustrated upon the phenomenon of Cloud based E-Learning adoption in the institutes of universities and institutes of higher education. Critical success factors for the effective implementing of Cloud Based E-Learning have been identified through systematic literature review using framework of Denyer and Tranfield (2009). Further they are clustered into four dimensions namely cloud service resilience, university technological maturity, university organizational readiness and Cloud Based E-Learning imperatives. The results of this research will be helpful for policymakers and practitioners of E-Learning in implementing Cloud Based E-Learning Platform

Mobile Learning in Higher Education: A Systematic Literature Review

Mobile learning (M-Learning) has become a popular and effective method of education that leverages the ubiquity of mobile devices. M-Learning has digitally transformed the process of teaching and learning. It has tremendous potential to empower all sections of society through education and training. This study presents a systematic literature review of M-Learning. The articles were retrieved from Scopus and Web of Science databases. After applying inclusion and exclusion criteria, a final selection of 161 articles published between 2016 and 2022 was included in the review. To analyze the articles, the researchers employed the TCCM (Theory, Context, Characteristics, Methods) framework, which facilitated addressing the research questions. This review identified various theories, such as behaviorism, constructivism, cognitivism, situated learning, problem-based learning, context awareness learning, socio-cultural theory, collaborative learning, conversational learning, lifelong learning, informal learning, activity theory, connectivism, navigation, and location-based learning, that are used to support and guide the implementation of M-Learning. In terms of context, developing countries contributed to 70.8% of the studies, while developed countries contributed to 29.1%. Further, a majority of the studies, 93%, involved students followed by faculty members and only two studies involved staff from higher education management. A total of 19 unique characteristic factors have been identified, such as personal, intention, attitude, usage, utility, ease of use, learnability, social, technological, pedagogical, anxiety, enjoyment, accessibility, knowledge, experience, trust, price, and habit. A quantitative research design was used in 90% of the studies, followed by mixed methods research design in 7% of the studies, and qualitative research design in only 3% of the studies. Further, this article synthesizes previous research findings and highlights gaps for future research. Overall, this review contributes to the understanding and advancement of M-Learning as a valuable educational platform

Evaluating Success Factors of Software Project Management in Global Software Development

At present, global software development (GSD) is gaining considerable attention in the realm of software engineering. The project management of global software projects presents substantial complexity owing to several inherent challenges of GSD. The software project management practices employed for in-house development appear inadequate to address the unique challenges posed by global software projects, making their management a formidable task. Software organizations rely on traditional software project management practices to manage global projects, often resulting in impairments or failures. This paper explores the critical success factors (CSFs) in software project management for global projects by developing a framework for effective project management within the context of GSD. The study focuses on identifying and prioritizing CSFs in software project management within a GSD setting utilizing multi-criteria decision-making (MCDM) analysis methods. Therefore, the present research provides an extensive literature review of CSFs in software project management within GSD. Additionally, the research applies the combinatorial approach to assess the various dimensions and CSFs of software project management in GSD. The proposed approach aids in measuring and comparing the effects of several dimensions and CSFs of software project management in GSD. Five dimensions and twenty factors have been determined through a literature review and further evaluated for prioritization using the combinatorial approach. The identified dimensions and factors will be valuable in devising strategies to effectively manage global software projects

Implementing Machine Learning for Smart Farming to Forecast Farmers’ Interest in Hiring Equipment

Farmers’ physical labor and debt are reduced as a result of agricultural automation, which emphasizes efficient and effective use of various machines in farming operations with the purpose of reducing physical labor and debt. It is a revolutionary idea in agriculture to create custom hiring centers, which are intended to make it easier for like-minded farmers to embrace technology/machinery for enhanced resource management practices. The study in question examines the significance of tool renting and sharing in the workplace. Rental and sharing equipment are two approaches that might be used to enable farmers to borrow equipment at a cheaper cost than they would otherwise have to pay for it. The following is a manual pilot study of 562 farmers in India to address the numerous challenges farmers face when looking for tools and equipment, as well as to determine their strong interest in the process of renting and sharing equipment. The study was conducted to address the numerous challenges farmers face when looking for tools and equipment and to determine their strong interest in the process of renting and sharing equipment. Farmers are divided into three groups according to the results of this poll: small, moderate, and large. Training and testing splits were used on the same data set in order to get a better understanding of the target variables. The data set for the survey was standardized in order to remove ambiguity. In this research, three different machine learning models were utilized: nearest neighbors, logistic regression, and decision trees. K-nearest neighbors was the most often used model, followed by logistic regression and decision trees. In order to get the best possible result, a comparison of the aforementioned algorithm models was carried out, which revealed that the decision tree is the better model among the others in this regard. Because the decision tree model is completely reliant on a large number of input factors, such as the kind of crop, the time/month of harvest, and the type of equipment necessary for the crops, it has the potential to have a social and economic impact on farmers and their livelihoods

Barriers Effecting Successful Implementation of E-Learning in Saudi Arabian Universities

Advancement of digital technology is influencing the leaping development of various activities in our daily life. E-Learning system has also gained a competitive edge over the prevailing traditional methodology. The prevailing pedagogy is being replaced by the E-Learning teaching system. E-Learning teaching-learning methodology provides more flexibility and allows freedom from time, place, physical presence, hectic, and stressful teaching-learning etc., thus plays a vital role in education system. However, there are many barriers in E-Learning methodology for successful teaching-learning. Study on such barriers will help to overcome the difficulties to the success of E-Learning. Present research paper attempts to study the various barriers that are affecting the successful implementation of E-Learning in Saudi Arabian Universities. This study reviews various barriers from literatures and identified most important E-Learning barriers which are described and grouped in four dimensions such as Student, Instructor, Infrastructure and Technology, and Institutional Management. Sixteen barriers falling under these relevant dimensions were validated their importance quantitatively through university Students, Instructors, and E-Learning staffs of some well know universities in Saudi Arabia. A survey instrument was developed and tested on a sample of 257 respondents of Saudi Arabian Universities. It was found that Infrastructure and Technology Dimension is the most significant as perceived by respondents. Results of the study also reveal that, all barrier factors are highly reliable, therefore should be taken care for successful implementation of E-Learning systems

Barriers Effecting Successful Implementation of E-Learning in Saudi Arabian Universities

advancement of digital technology is influencing the leaping development of various activities in our daily life. E-learning systems has also gained a competitive edge over the prevailing traditional methodology. The prevailing pedagogy is being replaced by the E-learning teaching systems. E-Learning, teaching learning methodology provides more flexibility and allows freedom from time, place, physical presence, hectic, and stressful teaching-learning etc, thus play a vital role in education system. However, there are many barriers in E-Learning methodology for successful teaching-learning. Present research paper attempts to study the various barriers that are affecting the successful implementation of E-Learning in Saudi Arabian Universities. This study reviews various barriers from literature and identified most important E-Learning barriers which are described and grouped in four dimensions such as student, instructor, infrastructure and technology, and institutional management. Sixteen barriers falling under these relevant dimension were validated their importance quantitatively through university students, instructors, and E-Learning staffs of some well known universities in Saudi-Arabia. A survey instrument was developed and tested on a sample of 257 respondents of Saudi Arabian Universities. It was found that infrastructure and technology dimension is the most significant as perceived by respondents. Results of the study also reveal that, all barrier factors are highly reliable, therefore should be taken care for successful implementation of E-learning systems