Content Adaptation in Mobile Learning Environments

Whether online or in a classroom, learners have long suffered from a lack of interactivity, several mobile learning system provide recorded lectures, which only enhance passive learning. Thus and in order to improve interactivity and motivation into the learning process, we propose in this paper a conceptual framework to be efficiently integrated into the learning process. This framework describes the design requirements of a mobile learning environment that can deliver live broadcast of real-time classroom teaching to online student with mobile devices. It suggests five perspectives: generic mobile environment, mobile learning context, learning experience, social learning strategy and learning objectives. It also clarifies how to apply these last perspectives and build a mobile learning application efficiently.

A formative assessment-based mobile learning approach to improving the learning attitudes and achievements of students

In successful mobile learning (ML) integration, factors associated with live-ware, software, and infrastructure are important. The main objective of this study is to investigate and model the influencing factors for learners and teachers at once to adopt ML in higher education. The proposed model consists of five impact factors: teacher, learner, mobile devices, ML tools, ML contents, communication technologies, and higher education institutes. Then the proposed model was implemented using a modified Moodle mobile application and evaluated using 60 teachers and 60 learners attached to the University of Kelaniya, Sri Lanka in 2021. According to the experimental research design approach, the proposed impact model was assessed as pre-test and post-test surveys using seven questionnaires. According to the Pearson correlation coefficient test, the most significant factor for learners and teachers to adopt ML is the mobile device. Learning content and communication technology were elected as the second most significant adoption factors for teachers and learners consecutively. However, higher correlation values were obtained for all factors denoting that they are greatly influenced the participant to adopt ML. The significant influencing factor of each impact factor was also investigated. In conclusion, it was recommended that featured smart devices, quality learning content, user-satisfied communication technology, academic enriched ML tools and higher education institutes with sound educational facilities are crucial for the university community to adopt ML in higher education. These findings help design academic community acceptable ML environments for higher education context.

The purpose of the present study was to design a mobile learning environment that enables the use of a teleconference application used in simultaneous e-learning with mobile devices and to evaluate this mobile learning environment based on students‘ views. With the mobile learning environment developed in the study, the students are able to follow a teleconference application realized by using appropriate mobile devices. The study was carried out with 8 post-graduate students enrolled in Karadeniz Technical University (KTU), Department of Computer Education and Instructional Technologies (CEIT), Graduate School of Natural and Applied Science. The students utilized this teleconference application using mobile devices supporting internet access and Adobe Flash technology. Of the 8 students, 4 accessed the system using EDGE technology and 4 used wireless internet technology. At the end of the application, the audio and display were delayed by 4-5 seconds with EDGE technology, and were delayed by 7-8 seconds with wireless internet technology. Based on the students‘ views, it was concluded that the environment had some deficiencies in terms of quality, especially in terms of the screen resolution. Despite this, the students reported that this environment could provide more flexibility in terms of space and time when compared to other simultaneous distance education applications. Although the environment enables interaction, in particular, the problem of resolution caused by screen size is a disadvantage for the system. When this mobile learning application is compared to conventional education environments, it was found that mobile learning does have a role in helping the students overcome the problems of participating in learning activities caused by time and space constraints.

Mobile learning is gaining popularity as it modifies the conventional definition of teaching and learning by using portable devices. In order to cope with identified limitations of mobile learning, while maintaining its transformational potential of using mobile technology in higher education, we proposed a blended mobile learning environment. In this study, we described the mobile blended learning environment and examined its applicability in theatre arts classrooms by presenting and discussing how mobile devices were used in three blended theatre arts classes at a comprehensive university in Macau. Survey and interview data showed that though challenges exist, the fusion of the multichannel teaching approach (m-learning, blended learning, in class/online lectures) has greatly enhanced teaching and learning experiences.

Mobile technology has been increasingly applied to educational settings in the past decade. Although researchers have attempted to investigate both students’ and teachers’ preferences regarding mobile learning, few studies have investigated the differences between the two, an understanding of which is important for developing effective mobile learning environments. To address this issue, a mobile learning environmental preference survey (MLEPS) consisting of eight factors, “ease of use,” “continuity,” “relevance,” “adaptive content,” “multiple sources,” “timely guidance,” “student negotiation” and “inquiry learning,” was developed in this study. A total of 1239 students (609 males and 630 females) and 429 teachers (208 males and 221 females) who employed mobile technology to learn and teach in schools completed the questionnaire. From the structural equation models, it was found that the major difference between the preferences of teachers and students in learning with mobile technologies was that the teachers tended to focus more on the technical issues, while the students cared more about the richness and usefulness of the learning content. In addition, both the students and teachers considered that the “anytime” and “anywhere” support provided via the mobile technology played an important role during the learning activities, engaging them in searching for information, collecting data, interpreting data and summarizing findings. It is therefore suggested that learning environments which conform to both students’ and teachers’ preferences be developed in the future.

Supporting efficient data access in the mobile learning environment is becoming a hot research problem in recent years, and the problem becomes tougher when the clients are light-weight mobile devices such as cell phones whose limited storage space prevents the clients from holding a large cache. A practical solution is to store the cache data at some proxies nearby, so that mobile devices can access the data from these proxies instead of data servers in order to reduce the latency time. However, when mobile devices move freely, the cache data may not enhance the overall performance because it may become too far away for the clients to access. In this paper, we propose a statistical caching mechanism which makes use of prior knowledge (statistical data) to predict the pattern of user movement and then replicates/migrates the cache objects among different proxies. We propose a statistical inference based heuristic search algorithm to accommodate dynamic mobile data access in the mobile learning environment. Experimental studies show that, with an acceptable complexity, our algorithm can obtain good performance on caching mobile data.

Learners consume video-based learning content on various mobile devices due to their mobility and accessibility. However, most video-based learning content is originally designed for desktop without consideration of constraints in mobile learning environments. We focus on readability and visibility problems caused by visual design elements such as text and images on varying screen sizes. To reveal design issues of current content, we examined mobile learning adequacy of content with 681 video frames from 108 video lectures. The content analysis revealed a distribution and guideline compliance rate of visual design elements. We also conducted semi-structured interviews with six video production engineers to investigate current practices and challenges in content design for mobile devices. Based on the interview results, we present a prototype that supports a guideline-based design of video learning content. Our findings can inform engineers and design tool makers on the challenges of editing mobile video-based learning content for accessible and adaptive design across devices.

Internet access using mobile handheld devices has surpassed that of fixed Internet, but most web pages are designed for desktop browsers. Mobile devices have resource limitations. Consequently, web pages designed for desktop browsing cannot be well displayed on mobile devices. Thus, dynamically transforming web contents designed for desktops into contents which can be displayed in a mobile device is an important task. Various approaches of content adaptation have been proposed to achieve this goal, but no single content adaptation strategy has been found to be effective. On the other hand, e-learning contents have grown manifold over years. In this paper, we provide a framework for an e-learning content adaptation system that can be used with desktops and mobile devices seamlessly. We combine multiple content adaptation strategies to make e-learning contents appropriate for mobile devices. Among the various content adaptation strategies, the segmentation algorithm plays the most important role. Our experiments demonstrate that the proposed scheme can be successfully utilized for content adaptation in mobile and handheld devices.

The wide use of e-technologies represents a great opportunity for underserved segments of the population, especially with the aim of reintegrating excluded individuals back into society through education. This is particularly true for people with different types of disabilities who may have difficulties while attending traditional on-site learning programs that are typically based on printed learning resources. The creation and provision of accessible e-learning contents may therefore become a key factor in enabling people with different access needs to enjoy quality learning experiences and services. Another e-learning challenge is represented by m-learning (which stands for mobile learning), which is emerging as a consequence of mobile terminals diffusion and provides the opportunity to browse didactical materials everywhere, outside places that are traditionally devoted to education. Both such situations share the need to access materials in limited conditions and collide with the growing use of rich media in didactical contents, which are designed to be enjoyed without any restriction. Nowadays, Web-based teaching makes great use of multimedia technologies, ranging from Flash animations to prerecorded video-lectures. Rich media in e-learning can offer significant potential in enhancing the learning environment, through helping to increase access to education, enhance the learning experience and support multiple learning styles. Moreover, they can often be used to improve the structure of Web-based courses. These highly variegated and structured contents may significantly improve the quality and the effectiveness of educational activities for learners. For example, rich media contents allow us to describe complex concepts and process flows. Audio and video elements may be utilized to add a “human touch” to distance-learning courses. Finally, real lectures may be recorded and distributed to integrate or enrich on line materials. A confirmation of the advantages of these approaches can be seen in the exponential growth of video-lecture availability on the net, due to the ease of recording and delivering activities which take place in a traditional classroom. Furthermore, the wide use of assistive technologies for learners with disabilities injects new life into e-learning systems. E-learning allows distance and flexible educational activities, thus helping disabled learners to access resources which would otherwise present significant barriers for them. For instance, students with visual impairments have difficulties in reading traditional visual materials, deaf learners have trouble in following traditional (spoken) lectures, people with motion disabilities have problems in attending on-site programs. As already mentioned, the use of wireless technologies and pervasive computing may really enhance the educational learner experience by offering mobile e-learning services that can be accessed by handheld devices. This new paradigm of educational content distribution maximizes the benefits for learners since it enables users to overcome constraints imposed by the surrounding environment. While certainly helpful for users without disabilities, we believe that the use of newmobile technologies may also become a fundamental tool for impaired learners, since it frees them from sitting in front of a PC. In this way, educational activities can be enjoyed by all the users, without hindrance, thus increasing the social inclusion of non-typical learners. While the provision of fully accessible and portable video-lectures may be extremely useful for students, it is widely recognized that structuring and managing rich media contents for mobile learning services are complex and expensive tasks. Indeed, major difficulties originate from the basic need to provide a textual equivalent for each media resource composing a rich media Learning Object (LO). Moreover, tests need to be carried out to establish whether a given LO is fully accessible to all kinds of learners. Unfortunately, both these tasks are truly time-consuming processes, depending on the type of contents the teacher is writing and on the authoring tool he/she is using. Due to these difficulties, online LOs are often distributed as partially accessible or totally inaccessible content. Bearing this in mind, this thesis aims to discuss the key issues of a system we have developed to deliver accessible, customized or nomadic learning experiences to learners with different access needs and skills. To reduce the risk of excluding users with particular access capabilities, our system exploits Learning Objects (LOs) which are dynamically adapted and transcoded based on the specific needs of non-typical users and on the barriers that they can encounter in the environment. The basic idea is to dynamically adapt contents, by selecting them from a set of media resources packaged in SCORM-compliant LOs and stored in a self-adapting format. The system schedules and orchestrates a set of transcoding processes based on specific learner needs, so as to produce a customized LO that can be fully enjoyed by any (impaired or mobile) student.

With the rapid development of the Internet, mobile learning environment is rapidly and profoundly affecting the learning behavior of college students in the new era. This paper investigates the current situation and problems of college students' learning behaviors under the mobile learning environment by using a combination of questionnaire survey and interview with undergraduates in a certain university in a certain region as the research object. The survey results show that from the learning behavior of mobile learning environment, it can be seen that college students have a great demand for online learning, but most of them have not found a reasonable way of learning, resulting in low learning efficiency. In view of the existing problems, the author proposes corresponding online learning strategies, so that college students can exert greater learning potential in the mobile learning environment.

In order to narrow the learning divide, mobile learning should be provided to handicapped learners, especially to learners with visual impairment. However, in spite of development of the resolution and screen size of mobile devices, there are still many inconvenient factors. Among recent studies, there is a Proposal of Ahmed Rana and Four Startup Screen operates in mobile devices with touch screen. Although Proposal of Ahmed Rana gives magnified virtual key-board and startup screen, and Four Startup Screen reduce complexity of menu structure, it is not good enough for learners with visual impairment in mobile learning environment. In this paper, we have proposed universal design of a cursor for mobile learners with visual impairment. First of all, our cursor has been designed to separate objects under a magnifying glass on the rim of the cursor. Secondly, the cursor has four kinds of startup screens in order to reduce repetitive moving. Thirdly, by dragging the cursor to the border of the screen, entire screen perform the magnifier. Universal design of a cursor can help mobile learners with visual impairment to more easily read documents consisting of text and to look video. For performance evaluation, our cursor is easy to select a character and easy to reduce of repetitive moving and depth of the hierarchical menu structure than the Four Startup Screen and the proposed method of Ahmed Rana. Consequently, universal design of cursor improves the performance of the input tool for learners with visual impairment in e-learning environment using small size mobile devices screen.

What people look at during a visual task reflects an interplay between ocular motor functions and cognitive processes. In this paper, we study the links between eye gaze and cognitive states to investigate whether eye gaze reveal information about an individual’s knowledgeability. We focus on a mobile learning scenario where a user and a virtual agent play a quiz game using a hand-held mobile device. To the best of our knowledge, this is the first attempt to predict user’s knowledgeability from eye gaze using a noninvasive eye tracking method on mobile devices: we perform gaze estimation using front-facing camera of mobile devices in contrast to using specialised eye tracking devices. First, we define a set of eye movement features that are discriminative for inferring user’s knowledgeability. Next, we train a model to predict users’ knowledgeability in the course of responding to a question. We obtain a classification performance of 59.1% achieving human performance, using eye movement features only, which has implications for (1) adapting behaviours of the virtual agent to user’s needs (e.g., virtual agent can give hints); (2) personalising quiz questions to the user’s perceived knowledgeability.

While mobile devices offer many benefits for learning, they can also have negative effects on focus and distraction. To support motivation and sustain interest, a gamification approach to mobile learning can be utilized, which has become increasingly popular in recent years. Previous meta-analyses have highlighted the effects of gamification on learning outcomes. Additional research is necessary to understand its impact, which will help to fully identify its affordances for mobile learning. This study investigates the effects of gamification elements in mobile learning on learner engagement, motivation, outcomes, interaction, academic achievement, and attitudes, and identifies key factors for their effective implementation. A meta-synthesis of 15 theses and 19 articles published between 2010 and 2023 was conducted. Theses were researched via the Turkish Council of Higher Education Thesis Center and ProQuest database, while articles were sourced from the Web of Science and Google Scholar. The findings indicate a notable increase in studies on gamification during 2018–2019. The importance of gamification technologies, especially gamified learning management systems, was highlighted in the studies reviewed. Overall, gamification adoption showed a positive and statistically significant effect on most examined variables in mobile learning. According to the research findings, some suggestions were made for educators, gamification designers, and academicians.

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