Mobile Cloud Learning Research Articles

Wahyudin Implementasi Model Creative Problem Solving (CPS) Pada Smart Mobile Cloud Learning System Multimedia Berbasis Animasi Untuk Meningkatkan Kemampuan Berfikir Kreatif Siswa

Creative thinking skills are skills that need to be developed for all students, and creativethinking is often associated with problem solving activities. Students who have the ability to thinkcreatively use all their thinking skills to find solutions to the problems they face. However, thecurrent learning process has not fully developed students' creative thinking skills. This is inaccordance with a preliminary study by researchers that teachers show that in the learning process to manage network infrastructure, teachers have not developed creative thinking skills due to the high demand for teaching materials. So this study aims to design a smart mobile cloud learning multimedia system based on animation with a Creative Problem Solving model to improve students' creative thinking skills. The research method is quantitative, using a Pre-Experimental Design research design, namely One-Group Pretest-Posttest. The multimedia development method refers to the Whole Life Cycle (SHM) method. The results of this survey: 1) Multimedia is available, the average percentage of media professionals is 86.68, and the category is “very good”. 2) Multimedia design can improve students' creative thinking skills. This refers to the four indicators of creative thinking, namely the average creative thinking ability of students as a whole or 55.12 in the "fully creative" category. In addition, the gain index is 0.48 and the effectiveness is "medium". 3) Student responses to multimedia scored 92 percent in the "very good" category.

The Correctness of Service in Runtime Adaptation for Context-Aware Mobile Cloud Learning

Service-Based Applications (SBAs) have become increasingly pervasive. These applications rely on the third-parties services available on the cloud, and services must be aware of and adapt to their changing contexts in highly dynamic environments. SBAs with context-aware capabilities have provided the users with personalized services based on their user's (intrinsic) and device's (extrinsic) contextual information, as well as the Quality of Services (QoS). The correctness of service substitution in runtime adaptation is substantial for the continuity of user activity on the system. In Mobile Cloud Learning (MCL) environment most works only focus on intrinsic context factors such as learner's profile, learner's location, etc. We then introduce a comprehensive Dynamic Service Adaptation of Context-Aware Mobile Cloud Learning (DACAMoL), which is designed to reason for bothcontextual factors and QoS inservice discovery, ranking, and selection. The framework represents the contextual information, service descriptions, and QoS using a semantic-based approach to improve the correctness of service substitution. In this paper, wepresent a quasi-experiment study to demonstrate the DACAMoL framework with a mobile app called Mudahnya BM. Mudahnya BM is a learning app to learn basic knowledge of Malay language that build using RESTful backend services. The study involved 30 participants and 33 randomized scenarios tested using One-Sample Wilcoxon Signed Rank test. The results show significantly better service substitutions with 32 out of 33educational servicesare correctly adapted (i.e. 95% of the population).

Determining the Factors that Affect the Use of Virtual Classrooms: A Modification of the UTAUT Model

Aim/Purpose: The aim of this study was to examine the factors that may influence the use of virtual classrooms. Background: The coronavirus (COVID-19) pandemic has affected and interrupted several aspects of our lives, including education. Most educational institutes and universities have changed their teaching mode from being face-to-face or fixable learning to ‘emergency remote education’. As a result, virtual classrooms were utilised in most of these universities to keep the continuity of teaching and delivering education to their students Methodology: Through an online survey, data was collected from 235 of the teaching staff at the University of Ha’il, Saudi Arabia. Structural equation modelling (SEM) using AMOS was applied to analyse the data and testing the hypothesis of the proposed model. Contribution: The study findings have a theoretical, methodological, and practical contribution in the area of virtual classrooms. In terms of its theoretical contribution, this research has enriched the literature on virtual classrooms. Most of previous studies used the basic UTAUT model or other models for different technology, such as LMS, Mobile Cloud Learning and social websites. Few studies have focused on virtual classrooms, and, based on the best knowledge of the researcher, this study is the first study that has extended and modified the UTAUT model by adding an external factor (mobility) with virtual classrooms technology. Thus, it contributes theoretically to IS acceptance literature in general, and to UTAUT models specifically. In terms of methodological contribution, this study assessed all latent constructs in the model in a different context (Saudi Arabia), and tested them through an advanced analysis technique, which some call a second-generation multivariate, by applying a two-step rule in AMOS (CFA and SEM). The CFA has shown solid results that can measure all constructs in the model after deleting a few items that show a low factor loading to the construct. According to Awang (2015), examining the construct, convergent and discriminant validities is essential during the CFA before moving on a step and analysing data using SEM. Thus, this study has validated all constructs and its items using CFA which can be further used in a different culture, specifically in an Arab culture, such as Saudi Arabia. Findings: The results showed that effort expectancy and performance expectancy are significant predictors of behaviour intention toward the use of virtual classrooms. However, in contrast of our expectation, social influence, facilitating condition and mobility were insignificant factors and had no influence on teaching staff’s behaviour intention toward the use of virtual classrooms. Recommendations for Practitioners: This research has made a practical contribution. The findings of this study showed which factors can determine the use of virtual classrooms. Decision makers and university organizations and administration can improve their virtual classrooms services based on the factors that determine their use. Taking care of that will lead to an increased use of virtual classrooms and lead to a successful use of virtual classrooms, which will result in huge benefits in applying virtual classrooms in the teaching process. Recommendation for Researchers: Researchers may develop different models and examine other factors to assess their influence on the usage of different technologies. Understanding the factors that may influence the usage of a technology leads to an increase in its usage and adoption. Impact on Society: This study may increase the usage of virtual classrooms among teaching staff by understanding and examining the factors that might determine the use of virtual classrooms. Future Research: Future studies could examine the moderation variables to establish their impact. This study relied on only a purely quantitative design study. Future research might employ a mixed method using both quantitative and qualitative designs to apply an interview after the quantitative study for a better insight and deeper knowledge as well as confirming the quantitative results.

Academic Performance and Cognitive Load in Mobile Learning

<p class="0abstract">The study considers the influence of cognitive load on the achievement of educational goals in the concept of mobile learning. It has been proved that the effectiveness of educational programs in a mobile learning environment is achieved by harmonizing cognitive load and structuring the educational content. The experiment was performed in order to identify pedagogical tools to ensure the effective use of the mental resources of students and to reduce their cognitive load when studying educational materials. The experiment was performed within the course of National education as part of the educational programs of Sechenov First Moscow State University (Russia) and Abai Kazakh National Pedagogical University (Kazakhstan). Traditional classroom learning was supplemented with electronic educational resources and a mobile learning program developed based on the Storage ISpring Cloud mobile learning platform with a focus on the study of national values of good manners and education. The experimental groups were offered three different approaches to studying the discipline in a mobile learning environment. The observation of the learning process helped us to identify the key aspects of effective educational practice in a mobile learning environment, namely: high-quality educational content; thematic and temporal structuring of the educational process; distribution of cognitive load in the educational course; introduction of tools to encourage student attention; active participation of students in the educational process; synergy of knowledge accumulation and delivery in the learning environment; thematic social interaction of the members of the educational group. The results of the experiment confirmed the constructive influence of pedagogical tools aimed at the reduction of cognitive load of students on the effectiveness of educational programs in a mobile learning strategy.</p>

Mobile Cloud Learning based on User Acceptance using DeLone and McLean Model for Higher Education

Mobile learning has been used in the learning process in several tertiary institutions in Indonesia. However, several universities have not been able to implement mobile learning due to the limitations of computer and network infrastructure. Cloud computing is a solution for agencies that experience limitations in computer infrastructure in the form of internet-based services for their customers. This paper discusses the implementation of mobile cloud learning which is a combination of mobile learning technology and cloud computing using the renewal DeLone and McLean Model which is a successful model to measure how important the implementation of a mobile cloud learning system is. The results showed that from the F test results obtained Fcount of 13,222, then Fcount> Ftable (13,222> 3.01), then Ho was rejected and H1 was accepted. So it can be concluded Information Quality, System Quality, and Service Quality together affect the Intensity of Use.

The impact of information culture on the adoption of mobile cloud learning in higher education environments

Adoption of new innovated technologies has become an important requirement for a successful development and implementation of computer systems. Mobile cloud learning is a relatively recent paradigm shift that provides significant promise for meeting future education development and delivery requirements based on mobile cloud computing. The focal point of this study is to develop a conceptual model which highlights the effects of information cultural factors on the adoption of mobile cloud learning in higher education environments. The proposed model is developed based on four identified information cultural variables, namely information integrity, formality, control and pro-activeness. A pilot survey is conducted to test the questionnaire using a small sample of information systems experts and university lecturers. The results show acceptable reliability and validity of the instrument. Finally, conclusions, possible practical contributions of this study and some of the directions for upcoming research are discussed.

The Dynamic Web Services Adaptation Framework in Context-Aware Mobile Cloud Learning Using Semantic-Based Method

Most of Service-Based Applications (SBAs) have to be changed after their first deployment not solely due to the changing system requirements as well as of continuous change of the environment itself. With the growth of web service paradigm, there is a need for an efficient mechanism in dynamic adaptation process to offer users a better service experience. In particular, context-aware can be adapted in dynamic adaptation by considering user's contexts and device's contexts. Context awareness will be a key area for Mobile Cloud Learning (MCL) environment as it helps in the reasoning process to provide correct education resources for learners' prospect. Contextual information are represented using semantic-based approach for high expressiveness and formal representation for reasoning technique. However, dynamic adaptations frameworks in previous research are still lacking in terms of contextual information of the learner and device, and quality of services (QoS) were not considered. Besides, there is limited support of semantic expressiveness in terms of contextual information and services by using solely semantic-based technique. This paper proposes Dynamic Adaptation in Context Aware Mobile Cloud Learning (DACAMoL) framework to support adaptation process in MCL using semantic-based approach. The framework is applied in MCL mobile application that offers basic learning language.

Determining the factors that affect the uses of Mobile Cloud Learning (MCL) platform Blackboard- a modification of the UTAUT model

The aim of this study was to unveil the factors that affect the use of Mobile Cloud Learning (MCL) platform Blackboard. Considering the nature of MCL, the Unified Theory of Acceptance and Use of Technology (UTAUT) model was applied and modified with two additional variables, i.e. mobility and self-management learning to understand the use behaviour of the users. A survey was conducted through a structured questionnaire to collect quantitative data for analysis. Structural equation modelling (SEM) was used to analyse the data and test the hypotheses of this study. In outcome, performance expectancy, effort expectancy and self-management learning are found as significant factors. Blackboard platform provider and users’ can be benefited through the outcome of this study by looking at the significant factors and understanding the use behaviour of the users.

Auto-Scaling Approach for Cloud based Mobile Learning Applications

In the last decade, mobile learning applications have attracted a significant amount of attention. Huge investments have been made to develop educational applications that can be implemented on mobile devices. However, mobile learning applications have some limitations, such as storage space and battery life. Cloud computing provides a new idea to solve some limitations of mobile learning applications. However, there are other limitations, like scalability, that must be solved before mobile cloud learning can become completely operational. There are two main problems with scalability. The first occurs when the application server’s performance declines due to an increase in the number of requests, which affects usability. The second is that a decrease in the number of requests makes most application servers idle and therefore wastes money. These two problems can be avoided or minimized by provisioning auto-scaling techniques that permit the acquisition and release of resources dynamically to accommodate demand. In this paper, we propose an intelligent neuro-fuzzy reinforcement learning approach to solve the scalability problem in mobile cloud learning applications, and evaluate the proposed approach against some of the existing approaches via MATLAB. The large state space and long training time required to find the optimal policy are the main problems of reinforcement learning. We use fuzzy Q-learning to solve the large state space problem by grouping similar variables in the same state; there is then no need to use large look-up tables. The use of parallel learning agents reduces the training time needed to determine optimal policies. The experimental results prove that the proposed approach is able to increase learning speed and reduce the training time needed to determine optimal policies.

Challenges and Opportunities of Mobile Cloud Learning for Higher Education: A Case Study of the Integration of Cloud Learning Platform and Zuvio

With the popularization of smart devices, the threshold for implementing cloud mobile learning is decreasing. With higher education presently facing the need for reform and innovation, this study addresses this need based upon the framework of activity theory. It implements a teaching mode combining a cloud learning platform and a real-time evaluation system, Zuvio, and explores the acceptance of this by students, the preparation and acceptance of teachers, and the support of the school. Also examined is whether the above three have different levels of cognition and actual execution problems and difficulties. The results of the study will be applied to courses in the School of Business and Management, where it will signify a major breakthrough in curriculum innovation. This study is based on the perspectives of students and teachers. The purpose is to understand the challenges and opportunities in teaching practice resulting from the integration of the cloud learning platform and Zuvio. It is expected that the research results obtained will be promoted, referenced, and applied to the teaching field of higher education as a pioneering procedure.

The Concept Framework of Structural Equation model of Mobile Cloud Learning Acceptance for Higher Education Students in the 21st Century

This research’s part is in the structural equation model of mobile cloud learning acceptance for higher education students in the 21st century as its objective is to synthesize and design the framework of this model. The methods of this research are divided into 2 parts which are synthesis, combining it to process the mode and designing framework concept. The findings of this research are as the following: 1. Basic digital literacy, Information Quality and Social Cloud are included in the model as the exogenous latent variables. 2. Satisfaction and TAM model (perceived usefulness and perceived ease of use) are included as the mediating latent variables. 3. Actual Use is the outcome of the model’s latent variable.

Study on College Students Education under the Cloud Mobile Learning Behavior and Service

With the development of the global mobile Internet advocate digital form, students in the mobile terminal to achieve professional Internet browsing and data transmission has become a reality. This paper through the theoretical framework and characteristics of mobile learning are summarized, and further raises the construction background of education cloud service system. Starting from the objective perspective, we analyze the significance of the existence of Education Center under the cloud services and mobile learning. We think there is lack of education cloud, mobile learning behavior of college students need to stimulate, therefore the analysis of how to enhance and improve the behavior and service of mobile learning for college students in education under the cloud.

Investigating mobile cloud learning through blog mining

With the help of cloud computing, Mobile Cloud Learning MCL can overcome many of the obstacles related to mobile learning. It holds considerable promise when it is developed and delivered in the business and education sectors. However, the discussion of MCL is disparate, fragmented, and distributed among different outlets. Systematic, extensively published research on MCL is unavailable. This paper adopts a novel method called blog mining to synthesise the MCL-related discussions in the literature, to provide an in-depth review of MCL, and to identify future trends and challenges to MCL. The findings indicate that, although MCL can offer many benefits to educational institutions and learners, concerns about MCL exist, including security concerns, privacy concerns, vendor lock-in/dependency concerns, price concerns, and concerns about legal/regulatory/information policy consequences. Wireless networks are facing challenges as well.

Mobile cloud learning for higher education: A case study of Moodle in the cloud

<p style="margin: 0in 0in 12pt; text-align: justify; line-height: 150%; text-indent: 0in; -ms-text-justify: inter-ideograph;"><span style="color: black; line-height: 150%; font-family: 'Georgia','serif'; font-size: 10pt; mso-fareast-font-family: Cambria; mso-ansi-language: FR-CA; mso-themecolor: text1;" lang="FR-CA">Mobile cloud learning, a combination of mobile learning and cloud computing, is a relatively new concept that holds considerable promise for future development and delivery in the education sectors. Cloud computing helps mobile learning overcome obstacles related to mobile computing. The main focus of this paper is to explore how cloud computing changes traditional mobile learning. A case study of the usage of Moodle in the cloud via mobile learning in Khalifa University was conducted. </span></p>

Public Health Practice Course Using Google Plus

In recent years, mobile device-assisted clinical education has become popular among nursing school students. The introduction of mobile devices saves manpower and reduces errors while enhancing nursing students' professional knowledge and skills. To respond to the demands of various learning strategies and to maintain existing systems of education, the concept of Cloud Learning is gradually being introduced to instructional environments. Cloud computing facilitates learning that is personalized, diverse, and virtual. This study involved assessing the advantages of mobile devices and Cloud Learning in a public health practice course, in which Google+ was used as the learning platform, integrating various application tools. Users could save and access data by using any wireless Internet device. The platform was student centered and based on resource sharing and collaborative learning. With the assistance of highly flexible and convenient technology, certain obstacles in traditional practice training can be resolved. Our findings showed that the students who adopted Google+ were learned more effectively compared with those who were limited to traditional learning systems. Most students and the nurse educator expressed a positive attitude toward and were satisfied with the innovative learning method.