Mobile Learning Services Research Articles

Enhancing Digital Education: A Model for Effective Mobile Learning Implementation in Malaysian Higher Education

This study investigates the implementation of mobile learning (m-learning) services in the smart environment at Kolej Poly-Tech MARA (KPTM) in Malaysia, focusing on establishing effective practices for digital education. Despite the potential of m-learning as an educational tool, its adoption in Malaysia remains limited, with the COVID-19 pandemic highlighting the need for innovative approaches to learning. The research employs a mixed methods approach, gathering quantitative data from 365 respondents, including students, lecturers, and administrators, through Likert-scale questionnaires distributed via Google Forms. Qualitative data were obtained through interviews with 10 selected participants. The study identifies existing practices in m-learning, explores its benefits, and examines challenges faced during implementation. Utilizing descriptive analysis, one-way ANOVA, Independent T-Test, and Regression Correlation, the findings reveal a positive perception of m-learning among stakeholders, alongside challenges related to infrastructure and training. The primary contribution of this research is the development of a model of good practice that provides guidelines for KPTM and other higher education institutions aiming to enhance the quality of mobile learning services. This model emphasizes the importance of accessibility, professional development, and stakeholder collaboration, positioning KPTM toward a more effective digital education landscape. Overall, the study underscores the critical role of m-learning in fostering flexible and engaging learning environments while addressing the barriers to its implementation in Malaysia.

What drives the adoption of mobile learning services among college students: An application of SEM-neural network modeling

This research aimed at examining factors influencing college students to adopt mobile learning (m-learning) services. An integrated model combined the information systems success (ISS) and Unified Theory of Acceptance and Use of Technology (UTAUT2), was developed to identify m-learning determinants. A sample of 552 was recruited to test hypotheses using structural equation modeling (SEM). The significant factors explained 70 % of the variance toward Behavioral Intention (BI) based on SEM results. While price value (PV), effort expectancy (EE), performance expectancy (PE), and privacy (PR) were not significant predictors of BI, the results of the neural network model ranked the predictive power of the factors in the following order: information quality, habit (HB), system quality (SYQ), hedonic motivation (HM), facilitating condition (FC), and social influence (SI), positively influenced m-learning adoption. The findings of this study helps the policy makers at higher educational institutions to formulate strategies to enhance students’ learning experience in upcoming crises and place a focus on sustainable mobile learning environment.

A New Technological Model on Investigating the Utilization of Mobile Learning Applications: Extending the TAM

Mobile learning has become increasingly important for higher education due to its numerous advantages and transformative potential. The aim of this study is to investigate how students perceive and utilize mobile learning (m-learning) services in universities. To achieve this objective, a conceptual model was developed, combining the TAM with additional new determinants, including perceived security, perceived trust, perceived risk, and service quality. The primary goal of this model is to assess the adoption of m-learning apps among users in university settings. To evaluate the proposed model, SEM was utilized to test the research model. The findings of the study highlight the critical roles of perceived security, perceived trust, and service quality in promoting the adoption of m-learning apps. Moreover, the results indicate that perceived risk negatively impacts both students’ trust and their attitudes towards using mobile learning services. The study reveals that the perceived trust, and service quality factors positively influence students’ attitudes towards adopting m-learning apps. These research findings hold significant implications for universities and academia, offering valuable insights to devise effective strategies for increasing the utilization of m- learning services among students. By gaining a deeper understanding of students’ perceptions and acceptance, universities can optimize their m-learning offerings to cater to students’ needs and preferences more effectively.

Virtual Reality Human–Computer Interactive English Education Experience System Based on Mobile Terminal

with the continuous development of communication technology, the rise and promotion of mobile terminals and the sound concept of digital learning are widely accepted. Mobile learning based on digital learning and mobile intelligent terminal technology has gradually attracted the attention of academic research and discussion circles. It can provide students with new learning experience of learning and training at any time. Due to the rapid development of social economy and science and technology, the application of science and technology in the education industry has also had a further development trend. Learners have also been looking for new learning methods to meet the complex and changing social development trend. This article studied the virtual reality human–computer interactive English teaching system based on mobile terminals and introduced the network topology of mobile learning environment and the elements of mobile learning service platform model. The design of virtual scene human–computer interactive English video teaching network resources was discussed. After the completion of the system construction, the relevant teaching practice was carried out. The practice results showed that 77.5% of the students agreed to the use of mobile terminals for English teaching, and 26.25% of them agreed very much. It could be seen that most students supported the English teaching mode of virtual reality human–computer interaction based on mobile terminals.

Virtual Community Digital Learning Nusantara

As of April 27, 2020, approximately 1.7 billion students were affected by the pandemic. Policies taken by Indonesia were disbursing all educational activities, making the government and related institutions present alternative educational processes for students by conducting online learning. This research aims to determine how far VCDLN is a learning medium in social distancing for teachers who study at Institut Pendidikan Indonesia (IPI). VCDLN is a Virtual Community Digital Learning Network to confirm the design for distance, Blended, and Mobile learning services that are easy, cheap, broad, and anchor to all corners of the archipelago through multi-platform mobile telecommunications, such as Android, IOS, Streaming, LCJ, YouTube, and TVUPI. Satellite. The research method is the qualitative research method. The data collecting technique used google form. The research subjects were teachers from post-graduate students of Educational Technology Program Class 16 and 17 at Institut Pendidikan Indonesia. Out of 54 students, they have taken advantage of VCDLN as a platform to teach during online learning. The data showed that 70% of the respondents thought that VCDLN is effective for online course activities. The results showed that the VCDLN platform is quite effective in learning; however, some participants believe that using the VCDLN platform is considered less effective due to several factors. Although VCDLN is considered less effective in some cases, this platform is considered more efficient and practical for students.

Design of Mobile Learning Service Platform Based on Data Mining

The current mobile learning service platforms are mostly self-centered, and they provide exactly the same learning content, and their personalized service capabilities are insufficient to meet the different learning needs of different students at the same time. To this end, combined with data mining technology, the research on a mobile learning service platform that can provide personalized services is conducted in this paper. The platform design includes four parts, namely frame design (development frame design and network architecture), main hardware design (microprocessor, switch, memory), main software design (user registration and login program, personalized mining analysis program, online learning procedures, online communication procedures) and system testing. The test results show that the concurrent performance and compatibility performance of the system meets the requirements after testing, allowing multiple users to use different mobile clients to access the platform at the same time.

The Effectiveness of Using Mobile Learning Techniques to Improve Learning Outcomes in Higher Education

Recently Mobile technology is considered an effective way to improve students' skills such as positive thinking, collaborative, communication, as well as it is considered the main part of major innovation in many e-learning research areas. As a result of the 21<sup>st.</sup> century requirements, skills were developed to address the rising needs in higher education which causes a shifting paradigm from the traditional methods of teaching to M-learning. In this research, we discuss the effect of using Mobile learning techniques to improve learning outcomes in Higher Education. We have implemented a web-based survey through two questionnaires. The questionnaires were distributed among 200 students in the second and third levels in the computer science department at both Community College and College of Arts and Science. This research explores a study on e-learning using mobile technology to identify students’ perceptions in the acceptance of mobile techniques and recognize the quality of mobile services for academic and social purposes to improve teaching strategy and learning performance in higher educational organizations. The outcomes of this research would support the evolution of M-learning at the university-level and cause shifting the traditional learning methods by merging M-learning methodologies as a learning management system that provides mobile learning services to students and teachers any time and from any location. The research study shows some important results towards the integration of mobile technology into teaching include: student positive perception, facilitates student concentrate, flexible access to m-services for learning materials, and increases students' skills in using mobile technology for e-learning.

Developing a Cloud-Based Mobile Learning Adoption Model to Promote Sustainable Education

Education plays a very significant role in the context of sustainability. As the world population is growing, providing education through the traditional classroom setting is not sufficient and not feasible to extend learning in professional life. Therefore, modern technology-mediated learning paradigms such as mobile learning are becoming increasingly popular. Mobile learning is said to integrate multiple contexts, learning types, mobilities and communications. As information and communications technology (ICT) plays a vital role in the delivery of mobile learning services, it is very essential to adopt sustainable IT resources to keep it viable. Cloud computing offers a range of affordable, scalable and on-demand solutions. This paper attempts to model important critical success factors (CSFs) in the area of cloud-based mobile learning using the interpretive structural modeling (ISM) technique. ISM helps in identifying the hierarchical inter-relationships between the variables of study with the help of experts in the field. Finally, Matrice d’Impacts Croisés-Multiplication Appliquée á un Classement (MICMAC) analysis is employed to classify the variables into dependent and independent variables. Management support has been identified as most rudimentary among sixteen CSFs identified through a literature review to establish a distinguished relative advantage. Further, the paper discusses the theoretical underpinning of all the constructs. This study will help organizations to implement mobile learning in sustainable ways.

Mobile Cloud Computing as Competence Intensifier

Since the arrival of mobile devices, such as Personal Digital Assistants (PDA’s), smartphones, tablets etc., and their amalgamation with cloud computing is bringing up and transforming ubiquitous computing into actual existence. This concept of ubiquitous computing straightens out the way to unusual and experimental applications, in which the mobile devices are integrated and provide assistance to the users. This paper discusses about the concept of mobile cloud computing, identify advantages and disadvantages of collaborating mobile applications with cloud and identify benefits of leveraging mobile learning services on cloud. Mobile cloud computing induces innumerable benefits and overcomes the technical limitations of mobile learning.

Використання мобільних технологій у процесі навчання фахівців спеціальності 193 “Геодезія та землеустрій”

The research is devoted to the problems of interactive learning as a special form of cognitive activity organization, which has very specific and predictable goals. It is noted that the characteristic feature of the last decade was active using of mobile communications means and various electronic devices. The modern mobile phone has capabilities that are not inferior to entry level PCs, and in some cases – and medium power. In particular this applies to smart phones and personal communicators (pocket personal computers with means of communication). In this regard, the use of mobile learning technologies in the educational process of training specialists in geodesy and land management needs to be generalized and systematized. The purpose of the article was to analyze the main possibilities of implementation mobile technologies in higher education, as well as the experience of their using in the training process of specialists in the field of geodesy and land management. The essence of mobile learning is presented as an interactive technology on the basis of which the higher education institutions create new learning environment where students can access educational materials at anytime and anywhere, making the learning process more attractive, democratic, comfortable and stimulates the student to self-education and lifelong learning. The technology of creation of interactive learning game with the help of free Kahoot online service is analyzed. It is noted that the possibility of mobile learning services expand the range of active learning methods and increase interactivity in studying and consolidating the educational material of land management disciplines. Implementation of online services and organization the current testing on their basis have positive affect on the study of disciplines in the professional cycle. Particular attention is paid to positive motivation in education and interest of students in the discipline, willingness to use modern information and communication technology and mobile tools for learning. Key words: Interactive learning, mobile tools, mobile learning, Google Forms mobile apps, Survey Monkey, Kahoot, Socrative, Plickers.

CoboChild: a blended mobile game-based learning service for children in museum contexts

PurposeThe purpose of this paper is to develop a blended mobile game-based learning service called CoboChild Mobile Exploration Service (hereinafter CoboChild) to support children’s learning in an environment blending virtual game worlds and a museum’s physical space. The contextual model of learning (CML) was applied to consider the related influential factors affecting museum learning and to promote children’s continuous learning and revisit motivations.Design/methodology/approachCoboChild provides a thematic game-based learning environment to facilitate children’s interactions with exhibits and other visitors. A practical system has been implemented in the National Museum of Natural Science (NMNS), Taiwan. A questionnaire was used to examine whether CoboChild can effectively fulfill the CML and to evaluate the impacts on museum learning.FindingsCoboChild effectively fulfilled the CML to facilitate children’s interactive experiences and re-visit motivations in the blended mobile game-based learning environment. Most children described the system as providing fruitful playfulness while improving their interpretations of exhibitions and learning experiences.Practical implicationsCoboChild considers the related contextual influences on the effective support of children’s learning in a museum, and builds a child-centered museum learning environment with highly integrated blended learning resources for children. CoboChild has been successfully operating in the NMNS since 2011.Originality/valueThis study developed a blended mobile game-based learning service to effectively support children’s learning in museum contexts. The related issues are shown to improve the design of blended museum learning services. This innovative approach can be applied to the design of other child-centered services for engaging children’s interactive experiences in museums.

Improving the Quality of Mobile Learning Services

The quality of services (QoS) has a key role to improve the performances of the collaborative mobile learning. However, many factors can limit it such as the cache management policies, the collaboration architecture, a heavy communication, etc. Therefore, we are interested in developing an impeccable learning system supporting cache management, collaboration architecture decisiveness, based mobile agent and web services standardization. The aim is to improve the quality of mobile learning services in term of information availability (hit rates and byte hit rates), learners’ average latency and the cognitive profiles of students. Consequently, we implemented four removal policies named Least Frequently Used (LFU), First In First Out (FIFO), Least Recently Used (LFU) and Size. In addition, we proposed and evaluated three collaboration architectures based mobile agent named Sequential, Random and diffusion mechanism. Experimental results show that our system improves the cognitive profiles of students and reduces the learners’ average latency. Furthermore, the experience and the performance results gained from this system prove that the removal policies performances depend on the learning method of each student and its collaboration patterns. For this raison, it is advantageous to allow the student to choose and/or change the removal policy during each learning session. However, diffusion mechanism provides the best performances in term of learners’ average latency.

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.

The Relationship among Self-Efficacy, Social Influence,Performance Expectancy, Effort Expectancy, and Behavioral Intention in Mobile Learning Service

The purpose of this study is to examine the structural relationship among self-efficacy, social influence, effort expectancy, performance expectancy, and behavioral intention of mobile learning, which is based on the extended technology acceptance model. We performed a study to determine the impacts that social influence, performance expectancy, and effort expectancy have on behavioral intention of mobile learning through self-efficacy. Appropriate measures were developed and tested on 226 university students of Gyeongnam province in South Korea with a cross-sectional questionnaire survey. The path relationship of the research model was analyzed by structural equation modeling (SEM) using AMOS 18.0. The results revealed that firstly, self-efficacy has positive effects on performance expectancy, social influence, and effort expectancy. Second, social influence has positive effects on performance expectancy, behavioral intention, and effort expectancy. Third, effort expectancy has positive effects on performance expectancy and behavioral intention. Fourth, performance expectancy has a positive effect on behavioral intention. Managers of mobile learning should focus on self-efficacy to enhance behavioral intention.

Towards a quality model of technical aspects for mobile learning services: An empirical investigation

Quality issues are commonly reported following the development of mobile learning applications. To evaluate and increase the chance of the successful development of new mobile learning products, the adoption of a complete and well-defined set of technical quality aspects for mobile learning development and their adoption in the education environment are proposed. This work describes a model that captures most abstract and generic technical aspects of mobile learning service quality, including availability, fast response times, flexibility, scalability, usability, maintainability, functionality, functionality, reliability, connectivity, performance, user interface and security. A set of technical quality aspects was developed following a literature study focussing on standards and guidelines for learning and mobile application software quality. The presented case studies point to a set of contextual technical quality factors that influence the choice of mobile learning application. The findings also indicate that there are causal relationships between learner satisfaction and the overall proposed model technical quality aspects. The model has a positive impact on overall learning process outcomes by evaluating the technical aspects while maintaining the quality of mobile learning delivered. The model components purportedly affect learning outcomes by assessing and improving the acceptability to stakeholders of the technical aspects of mobile learning.

An empirical study on cloud computing requirements for better mobile learning services

Information technology and its applications change not only the way students learn but also how they are taught. M-learning provides many advantages to our education system. Cloud computing is the new technology that has started to be widely adopted for use with several applications by many education providers. A number of issues that have delayed the complete adoption of M-learning applications through cloud computing services still need to be solved. This paper defines an appropriate set of requirements, i.e. availability, quick response, flexibility and ease of use, long-term storage, elasticity and scalability, integrity, privacy and confidentiality and the control of information flow. The dimensions of these requirements are tailored to criteria developed from the literature study, standards for software quality and their guidelines. The paper then highlights the level of importance of each defined requirement for higher educational institutions, training centres, research laboratories, infant and junior schools.

Investigating Students' Perceptions on Mobile Learning Services

M-learning is a form of learning, which has similarities and differences with the electronic learning (e-learning). It is mainly based on the use of the mobile wireless technologies that allow for learners to easily access learning materials anytime he desires and anywhere, whether on campus or off campus. Therefore, this creates a new flexible learning environment in the context of different learning settings. Students' perception of such technology is one of the most important factors for successful adoption of m-learning in the higher education environment. This study is conducted to investigate the perceptions of students in University Malaysia Terengganu (UMT) to move towards applying m-learning in their studies by using their mobile devices and to explore their expectations on mobile learning services. A total number of 91 undergraduate students majoring in computer science participated in the study. The findings show that the students have positive perception towards mobile learning and would like to use their mobile devices for both learning and administrative services.

Research on Mobile Learning Based on a Feedback Model

This paper presents an approach for modeling the mobile learning applications using a feedback-based recommendation model. Formal definitions are proposed for the mobile learning activity. The design unites three of the mobile learning's aspects, namely learner, service and context, and provides means for learner service evaluation within the recommendation model. The results show that the recommendation model can easily be constructed, while enabling accurate recommendations by solving the sparsity problem of service and learner′s information.

Construction of Mobile Learning Network System Based on Cloud Computing

Distributed computing and Resource sharing in large-scale heterogeneous system are the key to realize mobile learning system. This paper sets up a mobile learning service system through the construction of teaching cloud platform and cloud resources, cloud resource sharing, application and service of cloud resource, system and mechanism construction. The mobile learning network system is established by building models of it, which realizes mobile learning, collaborative learning and the situated learning anytime anywhere with freedom, individuality and diversification.

Collaborative M-Learning Adoption Model: A Case Study for Jordan

This work investigates university students’ acceptance and readiness for adopting collaborative and context-aware mobile learning services. An acceptance evaluation study was conducted to identify challenges affecting successful implementation and adoption of collaborative m-learning system. The acceptance study has focused on learning contextual factors and learners requirements available at developing countries, where Jordan was considered as the case of this research. Results have confirmed that learning style, mobile device capability and perceived ease of use are having the most positive contribution towards learners’ behavior to use collaborative m-learning services. In light of the achieved results, this work provides a new user acceptance model focused toward the adoption of collaborative m-learning services. Finally, this research draws fundamental recommendations allowing for learning context adaptation and successful collaborative m-learning services implementation.