Mobile Learning Platform Research Articles

Development of Learning Everywhere Class (LEKAS) Platform for Economic Education

The main objective of this research is to develop an Android-based mobile learning platform for economic education students so that they can study anywhere and anytime. Following the current trend, learning must be flexible in accordance with learning styles that tend to lead to online learning. Students will be more comfortable studying with their smartphones anywhere than having to carry books everywhere. This platform consists of several features, namely lecture material, evaluation results and progress of reading material in the form of PDF and video embedding. The design development in this study uses the ADDIE model, which consists of 5 stages, namely Analysis, Design, Development, Implementation, and Evaluation. This product was tested on 60 students of economic education class 2019 in introduction of macroeconomics courses. The final product of this research is an Android-based mobile learning platform with the title LEKAS (Learning Everywhere Class). The results of the evaluation of this product are that there is still a need for improvements in the ease of access to various types of android. The advantage is that students can immediately learn and find out the extent of understanding by taking tests after studying the material that has been shared. Through this platform students can study material and evaluate the material they read anywhere and anytime. The convenience provided on this platform will be able to increase the effectiveness and efficiency of learning in economic education.

Mobile-Learning Platform for the Development of Entrepreneurial Competences of the Students

The aim of the study was to determine the effectiveness of using a mobile learning platform for students’ entrepreneurial competence improvement. The platform was implemented by the Russian State Vocational Pedagogical University and the Financial University under the Government of the Russian Federation. It allowed users to publish assignments, exchange ideas, generate photo and video content, demonstrate creative developments, and receive feedback. The research process enrolled 70 experimental group students, 25 control group students, 2 instructors, and 2 administrators from the considered educational institutions, as well as 3 practitioners invited to review projects. As a result of this examination (Cronbach’s alpha ranged from 0.678 to 0.714), it was noted that 41.4% of all research participants rather agreed that the experiment goals were accomplished and noted personal progress in mastering entrepreneurial competences, whereas 53.4% agreed unequivocally that the experiment was fully successful. Analysis of entrepreneurial competences and deviations from repeated competence evaluations before and after the experiment revealed that the experimental group was marked with notable progress (F (1.32) = 42.26, p = 0.00, = 0.56). Average entrepreneurial competence assessment results for this group were slightly higher than those for control – they constituted 4.5 points against 4.0. Research findings are believed to be universal and interesting to educators and administrative staff of educational institutions or those involved in creating and conducting entrepreneurship training courses.

Application of Intelligent Terminal Mobile Learning Platform in English Teaching

Under the Internet+ operating model. The emergence of new teaching models has broken the traditional teaching methods, and a series of online teaching methods such as the Internet have provided children with newer teaching models. This not only facilitates the way of learning, but also brings more convenience to English teaching, and further promotes the method of English learning. Compared with traditional learning methods, it is more convenient to use the smart terminal mobile learning platform through the Internet. Teaching and other methods provide students with a better platform. Under the influence of smart terminals, such a learning platform can not only provide a diversified learning atmosphere, but also provide students with a better way of thinking, breaking conventions, and pioneering Innovation, and further enhance students’ interest in learning. And this kind of learning platform is more commonly used in English teaching [1].

Breaking Boundaries: Effectiveness of Gamification and Student Co‐Creation for Anatomy Remote Learning

Introduction An international reform on anatomy education has witnessed a transition from traditional cadaveric teaching, often reliant on rote-learning, toward visualization-based learning approaches. Multimodality of the learning preferences of Generation Z and the steep threshold learning curve in anatomy has led to the conception of gamification as a means of improving anatomy engagement, with reference to the Ebbinghaus (1880) forgetting curve. The aim of this study was to quantify student engagement using Quitch®, a gamified mobile learning platform and assess the impact of the app on student academic performance in an undergraduate Musculoskeletal Anatomy unit. Method 157 students enrolled in undergraduate Health and Science degrees at Swinburne University Australia were invited to download Quitch® during the COVID-19 remote learning period. In a student-faculty partnership project, a Quitch® unit with learning modules segregated for six regional anatomy topics, featuring 12 sections, was developed for Musculoskeletal Anatomy by 3rd year past students. Engagement was quantified using a 4-stage ordinal scale (1-4), based on access time from quiz release. The correlation between engagement, retention and academic performance for two virtual ‘spotter’ examinations was analysed. Results Preliminary results indicate that ‘highly engaged’ students who completed the quizzes within 14 days, quantified with a mode ordinal score of 1, scored an average grade of 67.05±0.18% on virtual spotter examinations; 21.37% higher than those who did not engage with Quitch®. Students who did not attempt the majority of quizzes (63.92%), quantified with an ordinal score of 4, received an average of 45.68±0.22% in their examinations. Completion and accuracy data from the Quitch® leaderboard indicated that the top 20 users received an average grade of 77.50%, in comparison to 49.86% for students with low engagement. Student retention increased from 88.7% in 2019 to 96.7% in 2020; while 79% of students reported an ‘increased sense of belonging'in the unit. Conclusion Quitch® offers personalized learning capabilities, mobility with notification capacity, tracking of at-risk students and allows the delivery of high-quality case-based, radiology and virtual spotter questions. We showcase the accommodation of multimodal learning preferences of students through content co-creation by students-as-partners in a platform that uses competitive leaderboards and badges to improve student engagement. Our analytics validate the efficacy of spaced repetition to consolidate long-term retention for improved performance in practical examinations. Implications The results on the efficacy of Quitch for improved student engagement in Anatomy is presented, demonstrating how student-centred virtual learning can be cultivated in remote learning, with the benefits of students-as-partners and the social constructivism theory in content design discussed as an approach to improve engagement and performance.

Augmented Reality (AR) - based Human Digestive System Mobile Learning Platform

Augmented Reality (AR) - based Human Digestive System Mobile Learning Platform

Face recognition algorithm based on self-adaptive blocking local binary pattern

Face recognition is a common means of identity authentication. Mobile learning platform login technology has developed from user name and password to face recognition. In order to improve effectively the rate of face recognition, this paper proposes a kind of face recognition algorithm based on self-adaptive blocking local binary pattern (LBP) and dual channel convolutional neural network (CNN) with different convolution kernels. Firstly, the Gamma correction, the Mallet wavelet filtering and normalization are used to preprocess the face image. The face image is decomposed and reconstructed by 2-layer Mallet wavelet to filter out the interference signal effectively. Although the general LBP operator extracts the overall texture and contour features of the face image, the distribution of the bright spot, dark spot and other micro details cannot be fully characterized. In order to solve this problem, integral projection is introduced to project the image horizontally and vertically. The extreme points of the projection represent the texture mutation points of the face image in the horizontal and vertical directions. These extreme points are used as the boundary of the image blocking, and the LBP value of the face image is extracted by the self-adaptive blocking strategy. Combining the features of k-nearest neighbor classifier and softmax, a k-softmax classification method is proposed to classify and recognize the face image labels. After two channel network structure training, this method is tested on Yale, ORL, extended Yale B and self-built face databases by five experiments, comparing with other face recognition algorithms. The results show that the proposed method based on SAB-LBP and dual channel CNN has high recognition rate and computational efficiency.

A mobile technology‐based cooperative learning platform for undergraduate biology courses in common college classrooms

As a high‐impact educational practice, cooperative learning uses a structured group study to promote students' active learning. Currently, it lacks economical yet effective tools to facilitate the interactive nature of structured cooperative learning in regular classrooms. Here, we have established a mobile technology‐based cooperative learning (MBCL) platform that comprises the 2018 iPad, Apple Pencil, LiveBoard, Google Forms, and Google Drive. We tested the MBCL platform in multiple undergraduate biology courses. During semester‐long MBCL studies, the students engaged in cooperative learning to discuss a real‐life issue or chapter‐based contents. With the MBCL platform, the students' group study processes were shown on shared, visible electronic whiteboards that were updated in real‐time, generating visible thinking and instant, interactive communication. The instructor was able to guide the students promptly to conduct knowledge integration and knowledge synthesis using tables and diagrams. The deep learning outcome was evident in the examples and quantitative analyses of students' whiteboard study results and team presentations. Thus, integrating innovative mobile technologies into high‐impact teaching practices, exemplified by the MBCL platform, promotes deep learning in higher education.

Using Machine Learning Algorithms to Predict People's Intention to Use Mobile Learning Platforms During the COVID-19 Pandemic: Machine Learning Approach.

BackgroundMobile learning has become an essential instruction platform in many schools, colleges, universities, and various other educational institutions across the globe, as a result of the COVID-19 pandemic crisis. The resulting severe, pandemic-related circumstances have disrupted physical and face-to-face contact teaching practices, thereby requiring many students to actively use mobile technologies for learning. Mobile learning technologies offer viable web-based teaching and learning platforms that are accessible to teachers and learners worldwide.ObjectiveThis study investigated the use of mobile learning platforms for instruction purposes in United Arab Emirates higher education institutions.MethodsAn extended technology acceptance model and theory of planned behavior model were proposed to analyze university students’ adoption of mobile learning platforms for accessing course materials, searching the web for information related to their disciplines, sharing knowledge, and submitting assignments during the COVID-19 pandemic. We collected a total of 1880 questionnaires from different universities in the United Arab Emirates. Partial least squares-structural equation modeling and machine learning algorithms were used to assess the research model, which was based on the data gathered from a student survey.ResultsBased on our results, each hypothesized relationship within the research model was supported by our data analysis results. It should also be noted that the J48 classifier (89.37% accuracy) typically performed better than the other classifiers when it came to the prediction of the dependent variable.ConclusionsOur study revealed that teaching and learning could considerably benefit from adopting remote learning systems as educational tools during the COVID-19 pandemic. However, the value of such systems could be lessened because of the emotions that students experience, including a fear of poor grades, stress resulting from family circumstances, and sadness resulting from a loss of friends. Accordingly, these issues can only be resolved by evaluating the emotions of students during the pandemic.

RETRACTED: Pentium microprocessor system structure and principal of political teaching and teaching material improvement

Abstract Designed a hybrid structural model of intelligent mobile learning platform based on Android system. Designed a prototype of a front-end platform for mobile learning. The intelligent system shows system test analysis to provide strong practicality and reference value and new method under mobile model to realize ideology and political leaders in university education. The report on election has been included in government method of four high school teachers. And interest of these teachers to election, by analyzing how that are trying to generate a student of politics to further concept of, author tries to understand politics of directives in better junior high school stage. Overall, author's teachers believe that capture students' interest in everyday politics and elections. However, teachers often miss opportunity to promote a subtle understanding of this interest in politics. The definition of political socialization problem is the way people have their political skills, develop direction and practices, how their experience is not shaping their own political base set. In this process is through a family relationship, or via interaction at school have been shown to occur in main. In education, in previous studies, in elementary school of lower grades, it indicates that are beginning education of political socialization and students, continued penetration of life. These ought to there is a great deal of analysis of political guidance that occurred in four classifications. In any case, these educators, a top pick of social investigations instructors in United States, have gotten formal preparing on most proficient method to instruct legislative issues. It must be emphasized that there is no. Educators perceive adulation and understudies; it should utilize an assortment of methodologies to cultivate this interest. Nonetheless, as brought up, don't accept that these measures are sufficient for guidance. Subsequently, it has botched a remarkable chance to cultivate a political comprehension of understudies.

Kaanbal: A Mobile Learning Platform Focused on Monitoring and Customization of Learning

For the new educational models, it is essential to include teaching strategies that allow students to customize their learning based on their competencies, skills, and preferences, as well as strategies that support individual monitoring of student learning. However, the implementation of these strategies in teaching is complex for professors, and it gets complicated, as the number of students in the class-room increases. In this work, the design and development of a mobile learning platform are presented, which provides the professor and student with multiple services for the learning monitoring and customization based on learning styles, context information, and mobile learning objects. Our platform is composed of three main components: (1) A mobile learning object generator system, (2) A learning object repository, and (3) A student-oriented mobile application. The in-tegration of these three components allows and facilitates the professor the im-plementation of various strategies for monitoring and customization of learning systematically. We carried out a usability assessment of the learning object gener-ator system through a field study with five research professors. According to the obtained results, the learning object generator system presents a good acceptance, satisfaction, and applicability from the professors' perspective.

Investigating students' behavioral intention to use mobile learning in higher education in UAE during Coronavirus-19 pandemic

The study explores the impacts of fear emotions on technology adoption by teachers and students during the COVID-19 pandemic. Mobile learning (ML) has been considered an educational, social platform in private and public higher education institutes. Since several fears are connected with COVID-19, this study's key hypotheses are related to how COVID-19 influences Mobile Learning (ML) adoption. Educators, teachers, and students may face some common types of fear in the course of the coronavirus pandemic, such as fear of losing social relationships, fear of educational loss and failure, and fear because of the lockdown of the family in the prevailing circumstances. Different theoretical models, named Expectation-Confirmation Model (ECM) and Technology Acceptance Model (TAM), are combined to develop an integrated model for this study. The proposed model was analyzed with the development of a questionnaire survey. The survey served as a data collection instrument to collect data from students of the University of Sharjah in Sharjah city in the United Arab Emirates (UAE). Three hundred twenty undergraduate students participated in the study. The collected data was evaluated using the partial least squares-structural equation modeling (PLS-SEM). The significant predictors revealed by experimental results included perceived fear, perceived ease of use, expectation confirmation, satisfaction, and perceived usefulness, explaining the intention to use the mobile learning platform. According to our study, teaching and learning can be benefitted to a great extent by the adoption of mobile learning (ML) during this pandemic for educational purposes; however, this process may be negatively affected by the fear of future educational results, fear of losing social relations and fear of stressful family situations. Therefore, appropriate student evaluation may be conducted to overcome the emotional distress caused by the pandemic effectively.

Secure Mobile Learning

The widespread adoption and employment of hand-held devices is a well-known and academically acknowledged fact as digital pervasiveness and hardware availability has triggered off this massive and convenient trend of accessing and consuming online resources and services from anywhere at any time. In this paper we argue that five areas in the mobile learning platform and the computer networks that support the processes and environments, require particular attention and proper training of the people involved to ensure the soundness of all the security methods and best practices are maintained, along with continual maintenance and updating of systems and procedures in each of these five categories. The paper closes with numerous recommendations regarding security in a mobile learning environment.

Autonomous Mobile Learning Model of Cloud Education Based on Intelligent Algorithm of Wireless Network Communication

The rapid development of a new generation of information technology and its widespread application in colleges and universities have promoted profound changes in campus informatization. On the one hand, wireless campus networks as the main infrastructure of digital campuses are gradually popularized in domestic colleges and universities, expanding the campus information network coverage. This article is aimed at studying the addition of intelligent algorithms to wireless network communications to optimize and build autonomous mobile learning for cloud education. In order for children to communicate with teachers face to face, no matter where they are, this article proposes how to reduce the energy loss in wireless communication and find the best intelligent algorithm to realize the cloud education mobile learning platform. Experimental results show that the transmission delay of the wireless communication system of this method is significantly shorter than that of the other two methods, close to 5%, which speeds up the data transmission speed of the wireless communication system. It can be implemented under time‐sensitive conditions and has high practical application value. The wireless network communication system of this method has a low packet loss rate and less wireless network data transmission errors, which is nearly 10% lower than the other two methods, thereby improving the data transmission power of the wireless communication network.

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>

Educational Experience in the Mobile Learning Environment: Consumer Behavior Perspective

<p class="0abstract">The development of digital technologies necessitates the formation of digital literacy and entrepreneurship skills in the modern "digital generation". The study has as the objective to identify the aspects of consumer demand for educational services in the process of testing the conceptual model of mobile learning adapted to the modern business environment in the context of digital transformations of the socio-economic life. The concept of an educational course based on the Sakai mobile learning platform with a focus on the formation of digital literacy in the business segment has been proposed in the study. The educational and applied course "Entrepreneurship in the Digital Mode" was tested within the educational programs of the State University of Management (Lyubertsy, Russia) and Herzen State Pedagogical University of Russia (St. Petersburg, Russia). The experiment made it possible to identify key aspects of consumer demand for distance education based on the characteristics of the participants' perception of the advantages and effectiveness of mobile learning. Most participants confirmed their professional achievements and the fact of the implementation of personal educational goals. Mobile learning was described as an easy, comfortable, interesting, innovative and modern method of learning compared to traditional classroom lessons. In the process of mobile learning, students demonstrated an increase in personal responsibility and self-organization while practical classes and the synergy of the educational content with real business cases greatly contributed to their involvement and productivity. Until now, research has not dealt with real measurable in terms of real income from specific activities, the results of the application of mobile learning. The contribution of this study to the area under study is to establish pedagogical demands that can be satisfied with mobile learning.</p>

The Application and Research of College English Blended Teaching Mode Based on MosoTeach

Now it is the digital information age. With the maturity of mobile Internet technology and the increase of online education demand, mobile learning applications based on mobile Internet terminals have been vigorously developed and widely used. Blended English teaching based on mobile network technology has become an inevitable trend in College English teaching. The new teaching mode is student-centered and emphasizes the interaction between teachers and students. The implementation of personalized teaching mode is conducive to improving students' learning autonomy and innovation, it can improve the classroom teaching effect to a certain extent. At present, the post-90s college students are the pioneers of the Internet era, but also the trendsetters in the wave of mobile Internet. How to effectively apply the mobile learning platform such as MosoTeach to College English teaching is the core theme of this paper.

How a company’s gamification strategy influences corporate learning: A study based on gamified MSLP (Mobile social learning platform)

Advances in personal devices and communication technologies have changed the learning landscape. Gamification is the use of technology to promote and induce the user's internal motivation by exploiting the game's characteristics. Recently, mobile learning applications introduce various gamification strategies to provoke users' voluntary participation. However, empirical evidence on how to attract users and influence sustained usage is limited. This study establishes a theoretical basis for designing learning applications and discusses its impact on business. A series of gamification strategies such as Competition, Challenge, Compensation, Relationship, and Usability, were applied to a company's Mobile Social Learning Platform (MSLP). A survey result of 293 users from South Korea was used for the advanced mediation model analysis. The result showed that Challenge, Relationship, and Usability had affected Flow and Continuous usage intention. This paper argues that the user's usage intention will have a positive effect on voluntary learning. It also provides a significant implication for organizational effectiveness through the development and application of mobile learning platform.

Reflective Practices To Explore Postgraduate Students Learning Experience In Mobile Learning Platform

Mobile Learning (M-learning) has great potential to be an effective learning tool in creating meaningful learning experiences. The purpose of this study is to explore postgraduate students M-learning experiences in Massive Open Online Courses (MOOCs) platform. Reflective practice is used to measure the students M-learning experience based on mobile-based task-centered activity. This study is qualitative in nature employed thematic analysis method. Therefore, 34 postgraduate students from a public university in Malaysia were selected for this purposive sampling. The postgraduate students were initially introduced to M-learning course content in FutureLearn platform followed by reflective practices. Pre-reflective practice happened before students are enlisted into the M-learning process, During-reflective process in FutureLearn platform and Post-reflective upon completion of task-centered activity. The findings revealed that majority of these students were unsure of M-learning platform during the pre-reflective stage. This is due to lack of prior knowledge and experience in M-learning platform using mobile devices as real time hindered the students from exploring. However, most of them progress to gained positive M-learning experiences as their able to monitoring and self-evaluate their own learning development throughout this learning process and completed the task-centered activity successfully. Therefore, the reflective approach practice has given students insight on their meaningful learning experience and their own learning capabilities.

Cognitive load management in mobile learning systems: principles and theories

With the widespread adoption of mobile technologies, mobile-assisted learning is gaining lots of momentum. This new learning paradigm promotes education across different contexts, which is a key factor that contributes to enhancing learning irrespective of the conditions and location of the learner. Therefore, it creates an authentic learning setting whereby students can make meaningful connections to the real world while learning takes place. Previous research works in the field of mobile learning showed that improper design of learning elements is still present in mobile systems and consequently results in poor dynamic content adaptation. Some attempts to adapt learning contents with appropriate instructional design principles are conducted, but with moderate exploitation of smart technological assets in mobile learning systems and limited pedagogical reflections and cognitive factors. In this paper, a learning efficiency model chart is derived using important learning factors that can be considered to enhance mobile learning experiences. Some popular learning theories are analysed and compared with the proposed learning efficiency model chart. This investigation is considered to significantly reduce complexities that exist in mobile learning platforms and promote an enhanced mobile learning experience.

Design of a WeChat Mobile Learning Platform for Multi-modal Language Learning and its Application

To follow the increasingly popularity of MALL (Mobile Assisted Language Learning) in the mobile multi-media era, the study probes into the design of a multi-modal language mobile learning platform supported by WeChat. The study also practically applies the platform to an English course for mobile learning and analyses the learning results with the quasi experimental research method. The experiment shows that the platform can effectively improve learners’ language ability, especially listening, writing and speaking skills.