Globally, <span>teaching methods and tools in higher education institutions (HEIs) have changed nowadays. Many attempts have been made in Jordanian higher education institutions (JHEIs) in order to improve and continuity of the educational process, especially during coronavirus pandemic. The outbreak of this virus has become a major disruption where all Jordanian universities cancelled classes and moved toward online learning, and mobile learning (ML) has appeared as one of the possible solutions. ML is in its early stages at JHEIs, and it is academically unexplored enough. So, this study explores the ML experience at JHEIs during coronavirus disease 2019 (COVID-19) crisis. The data were collected using a web survey where 272 students in JHEIs participated. The results revealed that the smartphone is the most widely used mobile device for ML ML is easy to use, ML increases the interaction between the instructor and the students and among the students themselves, ML has a positive impact on students’ performance, and also students are willing to use ML in the future. The outcomes of the study support policy makers at JHEIs to make educational decisions relating ML phenomenon.</span>
With the continued growth of mobile devices usage, wireless communications improvement, and cloud computing evolution, many educational institutions around the world, especially universities and colleges, began to provide their students with mobile learning systems based on cloud computing. The widespread, ubiquitous, and flexible natures of mobile devices make mobile learning an attractive alternative in education, particularly when integrating it with cloud computing which is the up-to-date technology that delivers computing hardware and software as services. However, the participatory between mobile learning and cloud computing as a cloud based mobile learning (CBML) becomes one of the important methods in the learning process. Many researches have attempted to combine the unique features of CBML in a form of frameworks. These frameworks have been designed to identify, categorize, or evaluate the major components of the CBML system. This paper is an attempt to identify the important role of cloud computing technology in mobile learning, investigate the main advantages and limitations of CBML systems, and explore the previously designed CBML frameworks.
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