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.

Learning using the Internet or training through E-Learning is growing rapidly and is increasingly favored over the traditional methods of learning and teaching. This radical shift is directly linked to the revolution in digital computer technology. The revolution propelled by innovation in computer technology has widened the scope of E-Learning and teaching, whereby the process of exchanging information has been made simple, transparent, and effective. The E-Learning system depends on different success factors from diverse points of view such as system, support from the institution, instructor, and student. Thus, the effect of critical success factors (CSFs) on the E-Learning system must be critically analyzed to make it more effective and successful. This current paper employed the analytic hierarchy process (AHP) with group decision-making (GDM) and Fuzzy AHP (FAHP) to study the diversified factors from different dimensions of the web-based E-Learning system. The present paper quantified the CSFs along with its dimensions. Five different dimensions and 25 factors associated with the web-based E-Learning system were revealed through the literature review and were analyzed further. Furthermore, the influence of each factor was derived successfully. Knowing the impact of each E-Learning factor will help stakeholders to construct education policies, manage the E-Learning system, perform asset management, and keep pace with global changes in knowledge acquisition and management.

E-Learning has proven to be the only resort as a replacement of traditional face-to-face learning methods in the current global lockdown due to COVID-19 pandemic. Academic institutions across the globe have invested heavily into E-Learning and the majority of the courses offered in traditional classroom mode have been converted into E-Learning mode. The success of E-Learning initiatives needs to be ensured to make it a sustainable mode of learning. The objective of the current study is to propose a holistic E-Learning service framework to ensure effective delivery and use of E-Learning Services that contributes to sustainable learning and academic performance. Based on an extensive literature review, a proposed theoretical model has been developed and tested empirically. The model identifies a broad range of success determinants and relates them to different success measures, including learning and academic performance. The proposed model was validated with the response from 397 respondents involved with an E-Learning system in the top five public universities in the southern region of Saudi Arabia through the Partial Least Squares regression technique using SmartPLS software. Five main factors (Learner’s Quality, Instructor’s Quality, Information’s Quality, System’s Quality and Institutional Quality) were identified as a determinant of E-Learning service performance which together explains 48.7% of the variance of perceived usefulness of ELS, 71.2% of the variance of use of the E-Learning system. Perceived usefulness of ELS and use of ELS together explain 70.6% of learning and academic performance of students. Hence the framework will help achieve the sustainable and successful adoption of E-Learning services.

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.

In the last few years, most of the public universities in the Kingdom of Saudi Arabia (KSA) have adopted electronic learning (e-learning) as an evolutionary educational platform both by choice and by demand. Despite its many advantages, it has increased the ethical and moral challenges faced in the form of the violations of academic integrity that exist in traditional education. Universities all over the world are struggling to overcome these issues. Keeping this in mind, the purpose of this paper is to investigate and priorities the factors of violating academic integrity within Saudi Arabian universities. Based on the previously published literature and using Delphi - based discussions with e-Learning experts, this paper has identified twelve major factors which were related to e-Learning environment, Awareness on Academic Integrity, and e-Learning guiding principles. Analytic Hierarchy Process (AHP) was used to prioritize these factors. It was concluded that inappropriate guidelines provided to students was the most contributing factor while Shortage of feedbacks was least contributing factor among all the identified factors.

In the past few years, educational data mining (EDM) has attracted the attention of researchers to enhance the quality of education. Predicting student academic performance is crucial to improving the value of education. Some research studies have been conducted which mainly focused on prediction of students’ performance at higher education. However, research related to performance prediction at the secondary level is scarce, whereas the secondary level tends to be a benchmark to describe students’ learning progress at further educational levels. Students’ failure or poor grades at lower secondary negatively impact them at the higher secondary level. Therefore, early prediction of performance is vital to keep students on a progressive track. This research intended to determine the critical factors that affect the performance of students at the secondary level and to build an efficient classification model through the fusion of single and ensemble-based classifiers for the prediction of academic performance. Firstly, three single classifiers including a Multilayer Perceptron (MLP), J48, and PART were observed along with three well-established ensemble algorithms encompassing Bagging (BAG), MultiBoost (MB), and Voting (VT) independently. To further enhance the performance of the abovementioned classifiers, nine other models were developed by the fusion of single and ensemble-based classifiers. The evaluation results showed that MultiBoost with MLP outperformed the others by achieving 98.7% accuracy, 98.6% precision, recall, and F-score. The study implies that the proposed model could be useful in identifying the academic performance of secondary level students at an early stage to improve the learning outcomes.