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The purpose of this study was to examine the determinants of sport consumers' mobile ticketing adoption by the technology readiness constructs and quality–satisfaction–behavioral intentions framework. A total of 295 participants were included in the analysis. Data analysis was performed using structural equation modeling and PROCESS macro. A content analysis was conducted to provide further insight into the proposed model using open-ended responses. The findings indicate that consumers' technology readiness alone was not a positive driver of mobile ticketing but suggest a role for technology readiness in promoting mobile ticketing, combined with service quality, satisfaction, and online ticket purchasing. The importance and originality of this study are that it confirms the sport context as a unique and effective vehicle in advancing existing knowledge of consumers' ticket consumption behavior via self-service technology across various disciplines. Also, the findings can be used to set out recommendations for policy or practice aimed at facilitating and sustaining mobile ticketing consumption. [ABSTRACT FROM AUTHOR]

The paper investigated the usage of mobile technology in marketing academic libraries in developing countries. The main purpose, apart from awareness, is to look at how researchers are studying mobile technology in marketing academic libraries, what are the current issues investigated and what has to be the direction of the topic globally. The paper employed 23 research papers for systematic review. The findings reveal that academic libraries are aware of mobile technology and use it at various levels for academic library promotion, visibility, and teaching and learning. Factors influencing the use of mobile technology in marketing academic libraries were identified and further noted that little has been studied regarding mobile technology in marketing academic libraries and its performance in developing countries. [ABSTRACT FROM AUTHOR]

The study focuses on mobile learning at universities, with emphasis on the changes brought by the quarantine during the COVID-19 pandemic (the first and the second wave) in which only distance education was possible. The participant sample consisted of Slovak university students (N = 48; age 20–25 in 2020 and N = 45; age 20–25 in 2021). Qualitative design and narrative method were chosen to find out the individuals' experience of concrete events embedded in a socio-cultural context. The data was analyzed using a holistic-content perspective in combination with a thematic analysis. The results showed the key moments linked to the university students' experience in the first wave of the COVID-19 pandemic: nostalgia, shock – sudden change, and adaptation. In the second wave of the COVID-19 pandemic, the key moments were: nostalgia, uncertainty, and short-term planning. The important phases for the sustainability of m-learning were related to the comparison between nostalgia, the recovery from the shock after a sudden change in lifestyle, and the adaptation to new living conditions. This was reflected in the key topics focused on the main phases, with an accent on life enjoyment, self-centring, and stress before the COVID-19 pandemic. The paper fulfills the gap in the research focused on understanding students' feelings, attitudes, values, and use of m-learning during forced distance education. Qualitative design research allowed going deeper into students" psychological aspects during national quarantine. The results allow us to prepare the universities and state policies on working with students during future crises and emphasize sustainable mobile learning. [ABSTRACT FROM AUTHOR]

The acceptability of technology is an essential factor to consider, particularly in frontier areas that encounter challenges related to availability and limited educational resources. This study aims to evaluate the acceptance of physics learning tools in a virtual laboratory (V-Lab) platform, utilizing the POGIL strategy, referred to as the Physics Funbased mobile application. Mobile learning refers to the learning process carried out through mobile devices such as smartphones. The implementation took place at a senior high school located in West Papua Province, one of Indonesia's frontier areas, with 136 students participating. The Technology Acceptance Model (TAM) and Theory of Reasoned Action (TRA) were employed in this quantitative study. Structural Equation Modeling (SEM) was implemented for data analysis. The findings indicated that Attitude (ATT) and Behavioral Intention (BI) were significantly influenced by Perceived Ease of Use (PEU) and Subjective Norm (SN), respectively, while Perceived Usefulness (PU) did not have a direct effect on ATT. As a result, to enhance the acceptance of technology, teachers and technology developers should prioritize enhancing ease of use and reinforcing social factors. This should be done with a particular emphasis on the social benefits and simple accessibility of technology in the learning process, particularly in frontier areas. [ABSTRACT FROM AUTHOR]

In the realm of marine intelligence, effective ship classification across vast oceanic expanses is pivotal. Despite strides in conventional identification techniques, existing methods exhibit limitations in terms of effectiveness, robustness, and overall performance. This paper introduces a novel Elephant Herd optimization based Spiking Neural Networks (EHO-SNN) for discerning large ships, small vessels, and the absence of ships. Initial satellite images from the Airbus dataset capture ships at sea, subjected to preprocessing via the wavelet transform-based Retinex algorithm (WRA) to eliminate noise and fog artifacts. Deep learning mobile net facilitates feature extraction, while the Elephant Herd algorithm culls irrelevant features, honing in on the most pertinent ones. Finally, the classification through a spiking neural network, distinguishing between large ships, small vessels, and the absence of ships. Detected large and small ships are accurately positioned within a selected scene, while the absence of a ship terminates the process. The Proposed EHO-SNN model attains an impressive classification accuracy of 99.10%. Notably, it surpasses OMRCNN-SHD, Efficient Net, and AN-YOLOv4 by 1.15%, 12.30%, and 7.79%, respectively, thereby advancing overall accuracy in ship classification. [ABSTRACT FROM AUTHOR]

This study analysed the content of 30 in-service primary school music teachers' lesson plans for mobile music creation during a 5-week professional development course from 2019 to 2022 in Hong Kong. During the course, the teachers were taught by the researcher on how to use the mobile application GarageBand in their instructional design for classroom music teaching. Various mobile learning pedagogies were discussed during the course to facilitate listening, performing and creating in music teaching and learning. As a learning outcome of this course, the teachers were asked to upload their lesson plans to the Knowledge Transfer website to exchange ideas for further discussion and professional sharing with other in-service teachers from their respective schools. The purpose of this study was to provide an analysis of their teaching plans based on previously published research on mobile learning and motivation. This study aimed to a) deepen the understanding of music lessons in mobile music creation, and b) analysing the lesson plans and suggesting how different teaching strategies and approaches can be used in classroom teaching. Based on the results of the study, a pedagogical model is proposed as a reference point for knowledge exchange in the research and practice of music education. [ABSTRACT FROM AUTHOR]

This study introduced an app, called Smart UEnglish, for helping EFL conversation practices in authentic contexts. These conversation practices were categorized into 'designed talk' and 'free talk', based on the content of an English textbook and authentic ambient environment that includes such things as transportation, weather and scenic descriptions, respectively. The mechanisms in Smart UEnglish were designed in consideration of flexible, sustainable and adaptive conversations to improve English-speaking and lexical resources. Statistical analysis results show that the learning achievement of the experimental group is significantly higher than that of the control group. Moreover, both 'designed talk' and 'free talk' have significant positive correlations with learning achievement. Further analysis with stepwise multiple regression found that 'designed talk' plays the most important role and can significantly influence learning achievement. This is because 'designed talk' can motivate them to practice what they learned in class during their daily conversations and consolidate the understanding and applying of English vocabularies and sentence patterns through 'designed talk'. According to interview records, participants also perceived that using Smart UEnglish for conversation practice in authentic contexts can stimulate their interests and ideas to think and practice more useful English conversation. Hence, Smart UEnglish can effectively help English-speaking and conversation in authentic contexts anytime and anywhere. [ABSTRACT FROM AUTHOR]

Previous reading research on incidental word learning as product and process has largely employed computer- or paper-based delivery methods. The present study uses a novel combination of offline and online measures to examine the effects of mobile media (mobile phone and tablet) compared to traditional media (paper and computer) on incidental L2 word learning from reading at three stages: the acquisition outcome, the acquisition process, and the posttest recall. One hundred fifty-six participants were assigned to one of the four media conditions with their eye movements recorded. We examined the acquisition outcome using form recognition, meaning recognition, and meaning recall posttests. We examined the acquisition process using summed first fixation duration, summed gaze duration, and summed fixation time. We used response time to examine the posttest recall. Our results show that mobile-assisted reading yielded an equivalent performance in word learning accuracy, allocated visual attention, and response time compared with paper-based reading that still presents a small advantage. Lower performance in one dimension of accuracy and two dimensions of attentional allocation suggest less efficiency in word learning from computer-assisted reading. This study presents a new research direction and cognitive evidence of the effectiveness of mobile-assisted language learning in word learning. We critically discuss the limitations of this study and provide suggestions for future research. [ABSTRACT FROM AUTHOR]

This article describes the design and implementation of a training model on Multimodal Mobile-Assisted Language Learning (M-MALL) for EFL pre-service (PSTs) teachers. Albeit EFL teachers' positive attitude towards technology integration into language teaching, they may still lack guidance and support on how to implement mobile technologies in their teaching contexts. Based on these, a training model to integrate M-MALL into PST education was suggested. An M-MALL training program was developed for the purposes of the study based on the needs, related literature, and the gap stemming from the lack of training opportunities in PST education. 16 PSTs studying in an ELT Department in Turkey participated. Following the implementation of a systematic eight-week training, participants were asked to write reflections on the training they received. The PSTs, in general, reported positive views on receiving training. Receiving such thorough training resulted in many gains for the participants such as improvement in teaching skills, expanding perspective on effective mobile technology integration, and being up to date as a teacher. The results have implications for language teachers and curriculum designers, and the suggested model provides a guideline for PST educators and language practitioners who would like to improve teaching competencies in a digital world. [ABSTRACT FROM AUTHOR]

Previous research has documented that students' reading comprehension performance in learning English as a foreign language (EFL) differs greatly between mobile-assisted and paper-based reading. The present study extends previous work by investigating whether reading cognitive load differs between mobile-assisted and paper-based EFL reading processes and exploring whether cognitive load mediates the relationship between reading medium and EFL reading comprehension performance. The instruments used are reading comprehension tests and questionnaire surveys administered to a sample of 191 first-year college students. A repeated-measures analysis of variance (ANOVA) indicates that cognitive load is significantly greater for mobile-assisted EFL reading than for paper-based EFL reading. In addition, structural equation modeling analyses indicate that cognitive load fully mediates the relationships between medium and reading comprehension performance; these mediation effects are independent of the level of English language proficiency. These results imply that cognitive load is a pivotal factor influencing students' reading comprehension across media. Reasons for differences in reading cognitive load and its role as a mediator are discussed. Recommendations for promoting students' reading experience on mobile phones are provided. [ABSTRACT FROM AUTHOR]

Education is one of the many sectors in which augmented reality has been successfully implemented. To determine how Augmented Reality (AR) supports education, this bibliometric study analyzes 1734 articles extracted from the Scopus database between 2010 and mid-2023. The study aimed to determine patterns in productivity, authorship and collaboration patterns, publications, citation structures, general research tendencies, and bibliographic coupling. Biblioshiny and VOSviewer were employed in this investigation. The outcomes of the study indicate an ongoing trend of increasing publication counts or more contributions since 2016, and still a trending topic studies on interactive learning environments and AR in education and knowledge constitute niche areas, while epidemiology, science education, and mobile augmented reality are important research topics that were underdeveloped and indicate a relationship that is both emerging and declining, based on a thematic analysis of the papers. Furthermore, the outcomes demonstrate that the USA, Spain, and the United Kingdom have the strongest global cooperation despite the USA writing more articles. To offer an ideal road map for scholars who would like to carry out research in this area, this paper also looks at the trendsetting in augmented reality in education. [ABSTRACT FROM AUTHOR]

Programming is a major subject in various Information Systems (IS) programs, with students often finding it a challenging skill to acquire. While there is extensive literature on factors helping students learn to program, most of which focuses on non-IS students. Due to the increasing demand for professionals with programming skills, there is a pressing need for further research on factors that could enhance learning programming skills at the higher education level. One promising approach to address this issue involves examining students' internal characteristics, their programming self-efficacy, and its connection to instructional methods that can enhance it. This study adopted a quantitative research design to evaluate students' programming self-efficacy. A survey was conducted to measure students' beliefs in their programming competence and engagement in various instructional activities, including the value they attributed to learning programming, the time spent practicing, and the frequency they sought guidance from teaching assistants (TA). Through a hierarchical multiple regression analysis, this work investigated how these mentioned variables could predict student-programming self-efficacy. The results indicated that the value students placed on learning programming emerged as the most significant predictor for programming self-efficacy. On the other hand, there was no substantial evidence that the practice time or consulting TA predict programming self-efficacy and the practice time or consulting TA. These findings suggest that educators and instructional designers need to emphasize the practicality and importance of learning how to program to enhance students' perceived value. [ABSTRACT FROM AUTHOR]

The rapid proliferation of mobile technology and its widespread integration in education, particularly in language instruction and acquisition, as well as its effectiveness in facilitating collaborative learning, have recently sparked a surge in research focused on collaborative mobile-assisted language learning (C-MALL). This review sought to delineate the current landscape of literature on C-MALL practices, pinpoint research trends, and propose avenues for future research while providing valuable insights for C-MALL pedagogical strategies. To achieve this objective, the review adhered to the PRISMA protocol, analyzing 72 studies sourced from five databases following stringent inclusion and exclusion criteria. Key findings encompassed: (1) an escalating yearly publication trend on C-MALL practices, with a substantial spike observed post-2019; (2) a dominant contribution from Asian nations in terms of publication volume; (3) a prevalence of studies conducted in higher education settings employing mixed-method or quantitative methodologies on small sample sizes over short durations; (4) C-MALL designs predominantly leveraging social media collaborative learning platforms via smartphones; and (5) the most prominent keywords being motivation, writing, and engagement. The implications of these findings for both researchers and educational practitioners were thoroughly deliberated upon as per the review outcomes. [ABSTRACT FROM AUTHOR]

Mobile learning has gained significant recognition for its beneficial effects on learning across various dimensions. Nonetheless, ensuring consistent learner acceptance of mobile learning remains a critical factor to address. This meta-analysis study is the first comprehensive examination of critical antecedents impacting learners' perceived usefulness and perceived ease of use of mobile learning within the Technology Acceptance Model. This study undertook a comprehensive analysis of prior research conducted in both English and Chinese languages during the last 22 years. The aim was to build the Integrated Mobile Learning Acceptance Model utilizing a one-stage meta-analysis structural equation model. Five major antecedents of perceived usefulness and perceived ease of use were identified, and the moderating effects of education level, region, and culture were revealed. The resulting model provides a cohesive framework for understanding the factors that influence learners' intention to use mobile learning across various contexts. At the same time, the results of the study contribute to the advancement of theory in mobile learning acceptance and have practical implications for the design and evaluation of mobile learning. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine the effect of mobile learning supported science teaching on eighth grade students' Science, Technology, Engineering and Mathematics fields and Information Technologies Self-Efficacy and to determine students' views on this process. For this purpose, a quasi-experimental design with pre-test post-test control group was used in the study. The study group consisted of a total of 45 students, 25 in the experimental group where the mobile learning supported 5E learning model was applied and 20 in the control group where the 5E learning model was applied. The applications in the experimental and control groups took place in a total of four weeks. Science, Technology, Engineering and Mathematics Career Interest Survey, Information and Communication Technologies Self-Efficacy Perception Scale and semi-structured interview form were used as data collection tools in the study. As a result of the analysis of the data obtained; it was determined that mobile-assisted science teaching had a positive effect on eighth grade students' STEM interests and self-efficacy levels. In addition, students stated that mobile-assisted science teaching increased the retention of knowledge, facilitated understanding of the lesson, and was instructive and fun. Depending on the results obtained from the research, it was suggested that mobile assisted science teaching should be used in different units of the Science course in order to see the effect of mobile assisted science teaching on different variables more clearly. [ABSTRACT FROM AUTHOR]

Introduction: Mobile learning has gained significant attention in medical education in recent years. The COVID-19 crisis has further accelerated its adoption. A lack of research on student perceptions of mobile learning during pandemics limits strategies for maintaining education during these times. This study examines the perceptions of medical students in Iran regarding the mobile learning during COVID-19. It is imperative that these perceptions are understood to optimize mobile learning effectiveness in medical education during disruptions. Method: A cross-sectional study was done in 2022 among 785 medical students in Iran who spent summer semester. Convenience sampling was used to select the sample. We used Biswas et al.'s scale for measuring medical students' perceptions of mobile learning during pandemics. Face and content validity was determined by qualitative methods. Internal consistency was measured with Cronbach's Alpha (0.79). Data was collected through an online questionnaire. To analyze the data, descriptive and analytical statistics were conducted with SPSS software at a significance level of p<0.05. Results: In total, 1,200 medical students were asked to complete the survey, and 785 responded, resulting in a 65.4% response rate. Mobile learning has been embraced by majority of medical students, with Android devices being used the most frequently. They also have frequent access to the internet, and they rely on a wide range of apps and platforms for academic purposes. Students perceive mobile devices to be highly advantageous for improving subject knowledge (Mean = 4.71±0.58), accessing study materials (Mean = 4.44±0.75), and providing flexible learning opportunities (Mean = 4.40±0.79). Despite this, participants were less confident about the ability of mobile devices to assist with specific study problems (Mean = 3.12 ± 1.28), facilitate class discussions (Mean = 3.33 ± 1.38), and overcome screen size limitations (Mean = 3.32 ± 1.38). Conclusion: Medical students in Iran have widely adopted mobile learning and perceive it as beneficial for acquiring knowledge, accessing material, and being flexible during COVID-19. M-learning's effectiveness in specific learning activities must be investigated in further research, and concerns regarding problem-solving, discussion facilitation, and screen size limitations should be addressed. [ABSTRACT FROM AUTHOR]

Education is one of the many sectors in which augmented reality has been successfully implemented. To determine how Augmented Reality (AR) supports education, this bibliometric study analyzes 1734 articles extracted from the Scopus database between 2010 and mid-2023. The study aimed to determine patterns in productivity, authorship and collaboration patterns, publications, citation structures, general research tendencies, and bibliographic coupling. Biblioshiny and VOSviewer were employed in this investigation. The outcomes of the study indicate an ongoing trend of increasing publication counts or more contributions since 2016, and still a trending topic studies on interactive learning environments and AR in education and knowledge constitute niche areas, while epidemiology, science education, and mobile augmented reality are important research topics that were underdeveloped and indicate a relationship that is both emerging and declining, based on a thematic analysis of the papers. Furthermore, the outcomes demonstrate that the USA, Spain, and the United Kingdom have the strongest global cooperation despite the USA writing more articles. To offer an ideal road map for scholars who would like to carry out research in this area, this paper also looks at the trendsetting in augmented reality in education. [ABSTRACT FROM AUTHOR]

In this study, we consider the extended optimal control problem and search for a control function in the class of feasible functions for a real control object. Unlike the classical optimal control problem, the control function should depend on the state, not time. Therefore, the control synthesis problem for the initial-state domain should be solved, instead of the optimal control problem with one initial state. Alternatively, an optimal trajectory motion stabilisation system may be constructed. Both approaches—control and trajectory motion stabilisation system syntheses—cannot be applied to real-time control, as the task is too complex. The minimum threshold of quality criteria is searched for in the space of mathematical expression codes. Among other problems, the search space is difficult to define and the gradient is hard to determine. Therefore, the advanced control object model is used to obtain a feasible control function. The advanced model is firstly obtained before solving the optimal control problem and it already includes a trajectory motion stabilisation system; in particular, this stabilisation system is synthesised in advance at the control system design stage. When the optimal control problem appears, it is solved in real time in the classical statement, and a control function is searched for as a function of time. The advanced control object model also uses the reference model to generate the optimal trajectory. The search for the optimal control function is performed in real time and considers the synthesised stabilisation system of motion along a determined trajectory. Machine learning control via symbolic regression, namely, the network operator method, is used to directly solve the control synthesis problem. An example solution of the optimal control problem, with an advanced model moving in the environment with obstacles for a group of two mobile robots, is presented. The obtained solution is a control function for a reference model that generates a trajectory from a class of trajectories stabilised with the object's control system. [ABSTRACT FROM AUTHOR]

Edge computing has much lower elasticity than cloud computing because cloudlets have much smaller physical and electrical footprints than a data center. This hurts the scalability of applications that involve low-latency edge offload. We show how this problem can be addressed by leveraging the growing sophistication and compute capability of recent wearable devices. We investigate four Wearable Cognitive Assistance applications on three wearable devices, and show that the technique of offload shaping can significantly reduce network utilization and cloudlet load without compromising accuracy or performance. Our investigation considers the offload shaping strategies of mapping processes to different computing tiers, gating, and decluttering. We find that all three strategies offer a significant bandwidth savings compared to transmitting full camera images to a cloudlet. Two out of the three devices we test are capable of running all offload shaping strategies within a reasonable latency bound. [ABSTRACT FROM AUTHOR]

Path planning is one of the main focal points and challenges in mobile robotics research. Traditional ant colony optimization (ACO) algorithms encounter issues such as low efficiency, slow convergence, and a tendency to become stuck in local optima and search stagnation when applied to complex dynamic environments. Addressing these challenges, this study introduces an adaptive deep ant colony optimization (ADACO) algorithm, which significantly improves efficiency and convergence speed through enhanced pheromone diffusion mechanisms and updating strategies, applied to global path planning. To adapt to dynamically changing environments and achieve more precise local path planning, an asymmetric strategy network TD3 algorithm (ATD3) is further proposed, which utilizes global path planning information within the strategy network only, creating a new hierarchical path planning algorithm—ADACO-ATD3. Simulation experiments demonstrate that the proposed algorithm significantly outperforms in terms of path length and number of iterations, effectively enhancing the mobile robot's path planning performance in complex dynamic environments. [ABSTRACT FROM AUTHOR]

This study explored the gamified experiences of Grade 8 students in MAPEH classroom using game elements of the mobile game, Mobile Legend, Bang! Bang! (MLBB) This study used qualitative research design, and cluster sampling was utilized. 40 students were invited to participate in a semi-structured interview to describe their experiences in the gamified classroom. The interview results were gathered, analyzed, and coded into main themes such as: gamified elements, positive experiences in gamified classroom, negative experiences in gamified classroom and suggestions for improvement. This study proved that the use of gamification in the classroom provided fun and interesting experiences as compared to traditional classroom. The participants mainly have positive experiences in the gamified classroom. They described gamification as motivating, fun, engaging, and interesting. Additionally, the study showed that gamification was effective in increasing motivation and engagement level of the students in the classroom. The study recommended teachers to adopt the game elements of MLBB in other subject areas and grade levels. [ABSTRACT FROM AUTHOR]

The study aimed to perform a literature review to identify the trends, impacts, and challenges associated with the integration of microlearning and social media. A total of seven academic databases were used as sources for searching: Scopus, Web of Science, ACM, EBSCOhost, PubMed, ProQuest, and IEEE. A combination of keywords related to microlearning and social media was employed during the search process. No specific date limit was imposed, but only materials published in English were considered for inclusion. A total of 2312 articles were identified in the first phase of the search. Sixteen articles were selected during phase two after applying the inclusion and exclusion criteria. The reviewed studies encompassed various fields, including computing, programming, language, nursing, surgery, and radiology. Additionally, multiple social media platforms were identified, such as podcasts, chatbots, Facebook, Instagram, LinkedIn, MP3, TikTok, Twitter, YouTube, and Sina Weibo. The results indicate that the integration of microlearning and social media has the potential to enhance learning outcomes positively. These outcomes include increased learner satisfaction, expanded reach, improved learner engagement, and enhanced learning effectiveness. Additionally, the review highlights that the most significant benefits of combining microlearning with social media are increased reach and enhanced learner engagement. [ABSTRACT FROM AUTHOR]

Copyright of Turkish Online Journal of Design, Art & Communication is the property of Turkish Online Journal of Design, Art & Communication and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ciencia y Educación (2707-3378) is the property of Duanys Miguel Pena Lopez and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study evaluates an intervention program that uses mobile learning, designed for Israeli Arab hearing‐impaired elementary school students, focused on language and mathematics. Participants included 23 hearing‐impaired students, 39 teachers, and 46 parents. The evaluation combined quantitative and qualitative methods, using questionnaires, knowledge mapping, observations, individual semi‐structured interviews, and focus group discussions. Findings revealed: (1) integrating mobile learning promoted learning enjoyment of learning, and satisfaction with program implementation; (2) content knowledge development contributed to mathematical knowledge and all language components except grammar; (3) inequality among students persisted since only hearing‐impaired students benefited from the program, leading to another kind of inequality; (4) teachers coped with various challenges: lack of technological skills, need for differential teaching for different populations in the classroom, and general lack of attention in the classroom when using apps with audible instructions and (5) parents have vital role in implementing new learning approaches for special needs students. [ABSTRACT FROM AUTHOR]

In this study, we propose a model called LFSPN, which serves as an extension of stochastic Petri nets dedicated to the multi-agent systems paradigm. The main objective is to specify, verify, validate, and evaluate the flow of materials within an automated production chain. We illustrate the practicality of our model by engaging in a systematic process of modeling and simulation of a production chain involving material flow. To evaluate the performance, we employ a mobile learning agent, which has distinct characteristics, namely mobility and learning. So, the distinctive characteristics of the learning agent are manifested in two key behaviors: mobility and learning. Notably, the learning agent is equipped with a flexible learning algorithm that integrates stochastic elements based on transitions. We suggest using a MATLAB simulation to determine the firing time of each transition within a sequence, guided by three different probability laws (exponential, normal, and log-normal). This sequence is designed to optimize the production process objective while facilitating learning cycles through agent rewards, specified by a production and consumption of tokens in our evolving model. We validate the effectiveness of our model by performing a comparative analysis with similar existing works. The advantages of our LFSPN model are twofold. Firstly, it offers a representation with two levels of abstraction: a graph representing the classic components of an SPN, and an additional layer encompassing the learning and migration aspects inherent to a mobile learning agent. Secondly, our model stands out for its flexibility and simulation simplicity. [ABSTRACT FROM AUTHOR]

This paper explores the relationships between m-learning, learning outcomes, and developing critical thinking in university students. A systematic review of empirical articles in English published in journals indexed in the Web of Science from 2015–May 2024 was carried out. A sample of 50 articles was obtained. The results show that, in most of the analyzed articles, integrating m-learning tools can potentially to improve students' learning outcomes and critical thinking skills. Considering the above, we recommended that educators and university managers integrate and promote the adoption of new technologies in teaching methods. Several recommendations are provided for the effective integration of m-learning into learning activities, stressing the importance of teachers becoming familiar with technology-enhanced learning environments early in their training. [ABSTRACT FROM AUTHOR]

This study addresses a significant problem: it is difficult to choose a suitable mobile learning platform effectively since many learning platforms are readily available for users. For this purpose, the study proposes an efficient way to rank and choose the most suitable mobile learning platform by integrating risk analysis and multi-criteria decision-making methods. The selection of a suitable mobile learning platform is challenging due to the vast collection of available platforms. Traditional decision-making approaches often struggle to manage the inherent uncertainty and subjectivity in platform evaluation. To address this, we propose an enhanced methodology that combines grey relational analysis (GRA) and fuzzy analytic hierarchy process (FAHP), leveraging their complementary strengths to provide a robust and adaptive solution. The study employs ISO/IEC 9126 software quality standards to locate the most suitable mobile learning platform. FMEA is based on three risk factors: occurrence, severity, and detection. The fuzzy analytical hierarchy process (FAHP) is used to determine the relative weight of each risk factor to identify the grey risk priority number that can be calculated for each criterion. Mobile learning platforms are then ranked based on their grey risk priority number. The method was applied to five widely used mobile learning platforms with three decision-makers. In addition, the multi-criteria decision-making software was developed to aid users, educators, and administrators in their decision-making processes. The integrated FMEA-GRA-FAHP technique, using ISO/IEC 9126 standards, provides an effective way of locating the most suitable mobile learning platform and ranking them according to their reliability. This research is believed to be the only study applying an integrated FMEA-GRA-FAHP approach to evaluate the risks and quality of mobile learning platforms. The unique approach overcomes certain limitations of the standalone methods such as FMEA and FAHP, making it a valuable tool for identifying the suitability of mobile learning platforms. In addition, the study underscores the importance of inclusivity and equity in ensuring high-quality education and creating an environment conducive to lifelong learning for all. [ABSTRACT FROM AUTHOR]

We systematically review mobile health applications in supporting learners living with epilepsy disorders. There are two objectives of this study i.e., assessing the existing epilepsy-related apps and providing information about some features provided by the apps. In total, 18 of 47 mobile apps that meet the final criteria were reviewed using the Mobile Application Rating Scale (MARS). We found that more than half of the apps had below-average quality and most offered only a few distinct functionalities. Six of them were deemed high quality since they met all standard criteria. In terms of selfmanagement features, we identified several important features such as the provision of a seizure calendar (14/18, 78%), report generation (5/18, 28%), adding individual seizure occurrence and causes (9/18, 50%), and emergency alert (6/18, 34%). The majority of the apps included medication tracker (12/18, 67%), expert consultation (6/18, 34%), and educational features (10/18, 56%). Moreover, 40% of included apps have considered self-efficacy features by providing analytical support for seizure frequency, duration, occurrence distribution, and analysis. This research can make inperson support more feasible for epilepsy learners so that it helps families, caregivers, and educators to easily manage the risk and perform continuous aid. This research can also be the basis for developing more patient-centered software for epilepsy management. [ABSTRACT FROM AUTHOR]

Despite the widespread necessity of students to learn English, Peruvian students face challenges that include a lack of motivation, overwhelmed academic expectations, and low socioeconomic status. Therefore, in this paper, a mobile application that employs virtual reality and gamification is proposed to improve English language learning among Peruvian high school students. This research consists of three stages: (1) review, (2) proposal, and (3) validation. In (1), an exhaustive review of teaching techniques, gamification strategies, and virtual reality models applied to English language learning is carried out. In (2), specific guidelines are selected for the implementation of teaching techniques, gamification, and type of virtual reality for the construction of the mobile application, using Google Cardboard virtual reality glasses. Finally, in (3) the validation of the mobile application is reported, in which 58 high school students participated. Data were collected on student performance before and after using the application. The results showed that students increased their performance in the English language by 22%. This percentage was measured by the average of the grades taken at the beginning and at the end of the experiment. [ABSTRACT FROM AUTHOR]

Mobile devices face significant security challenges due to the increasing proliferation of Android malware. This study introduces an innovative approach to Android malware detection, combining Support Vector Regression (SVR) and dynamic feature analysis to address escalating mobile security challenges. Our research aimed to develop a more accurate and reliable malware detection system capable of identifying both known and novel malware variants. We implemented a comprehensive methodology encompassing dynamic feature extraction from Android applications, feature preprocessing and normalization, and the application of SVR with a Radial Basis Function (RBF) kernel for malware classification. Our results demonstrate the SVR-based model's superior performance, achieving 95.74% accuracy, 94.76% precision, 98.06% recall, and a 96.38% F1-score, outperforming benchmark algorithms including SVM, Random Forest, and CNN. The model exhibited excellent discriminative ability with an Area Under the Curve (AUC) of 0.98 in ROC analysis. The proposed model's capacity to capture complex, non-linear relationships in the feature space significantly enhanced its effectiveness in distinguishing between benign and malicious applications. This research provides a robust foundation for advancing Android malware detection systems, offering valuable insights for researchers and security practitioners in addressing evolving malware challenges. [ABSTRACT FROM AUTHOR]

The inconsistent findings about learning outcomes in VR (virtual reality) learning necessitate further robustness of empirical data. This article addressed this gap by comparing the learning outcomes across VR, phone, and mobile learning on two dimensions: recall accuracy and recall speed, as well as learners' attitudes. Additionally, this paper attempted to investigate the differences between 5 and 10 min time duration. By inviting a total of 28 participants to the lab experiments on English vocabulary acquisition, this study yielded no statistically significant difference in vocabulary recall accuracy between VR, computer, and mobile learning. Nonetheless, the significant difference in vocabulary recall speed was generated. Besides, the time spent on vocabulary acquisition was significantly shorter in VR than in computer and mobile learning. Additionally, pairwise comparisons revealed that learners' perceptions and attitudes toward SUS resulted in significantly lower scores in VR than in computer- and mobile-based learning. Further, merely two of the nine items on the VR sickness scale demonstrated a significant raise in visual fatigue as well as significant decline in headache between 5 and 10 min learning duration. Future research should anticipate a larger sample size to ensure the validity of research findings and further construct a 3D modeling for the same language learning settings for non-college, primary, as well as secondary school students. [ABSTRACT FROM AUTHOR]

Purpose: Professional Identity Formation is the dynamic evolution to "think, act and feel" to become part of a professional community. This document presents the development and the study that aimed to assess the usability of a m-Learning Identity App (MLIA) focused on the formation of professional identity among undergraduate medical students. Design/methodology/approach: MLIA development included four phases: Conceptual, prototype, pilot and implementation, before further deployment. The conceptual model was designed by eight faculty members from three Latin American universities. The prototype was developed and tested with stakeholders. The pilot was performed during 5 weeks before the implementation. Cross-sectional data collected during implementation from 138 medical students who completed a survey to assess the usability of MLIA are presented. During deployment, 977 posts were made on Professional Identity Formation, and examples of these posts are presented. Findings: The prototype and pilot phases demanded improvements. The survey explored (1) Familiarity, (2) Perceived ease of use, (3) Perceived usefulness for Professional Identity Formation, (4) Satisfaction, (5) Intention to reuse (6) Digital aesthetics and (7) Safety. Results from the usability assessment suggest that students perceived MLIA as a secure space with positive aesthetics and ease of use. Research limitations/implications: Important limitations of the present study include, firstly, that it does not provide information on the effectiveness of the MLIA in shaping professional identity in medical students, it focuses exclusively on its development (conceptual model, prototype, pilot and implementation) and usability. Secondly, the study design did not consider a control group and, therefore, does not provide information on how the App compares with other strategies addressing self-reflection and sharing of meaningful experiences related to professional identity. Originality/value: MLIA introduces a different approach to education, simulating a secure, easy-to-use, social media with a friendly interface in a safe environment to share academic and motivational moments, transitioning from being to becoming a professional. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to improve the Unified Theory of Acceptance and Use of Technology (UTAUT) model by examining technological anxiety and other influential factors on international students' adoption of mobile learning (m-learning) during COVID-19 emergency remote teaching (ERT). Design/methodology/approach: This study utilized the modified UTAUT framework to test hypotheses through a cross-sectional survey method. Participants were university students studying Chinese as a foreign language who were selected using a convenience sampling approach. An online questionnaire was then administered. The data collected from the surveys were analyzed using the partial least squares method with SmartPLS 4 software. Findings: The study examined 16 hypotheses and found support for six of them. The results confirmed that performance expectancy (PE) is a significant predictor of behavioral intention (BI), and anxiety influences both PE and effort expectancy. The negative effect of social influence on anxiety was found to be significant, while facilitating conditions had a negative impact on learners' self-efficacy. The model fit indices indicated a good overall fit for the model. Research limitations/implications: This study presents a valuable contribution to the literature on m-learning in emergency education by incorporating technological anxiety into the enhanced UTAUT model. Examining the relationships between the key factors of the model provides a better understanding of learners' intentions and can inspire researchers to establish new theoretical foundations to evaluate the roles of these factors in diverse educational settings. Practical implications: The study found that performance expectations are linked to learners' intentions, and anxiety indirectly affects BIs to use mobile learning platforms. Thus, these platforms should be designed to meet learners' expectations with minimum effort and eliminate anxiety triggers to facilitate ease of use. Language curriculum developers and policymakers should incorporate mobile learning applications to support diverse language skills, address students' needs and encourage their use through professional development opportunities for instructors. Social implications: Social factors have been found to significantly influence anxiety levels among learners. Therefore, it is crucial for teachers and family members to play an essential role in mitigating anxiety's adverse effects. Discussing related issues can enhance the quality of mobile learning and stimulate social initiative by providers, ultimately improving the learning experience for all learners, regardless of their location or circumstances. This can also contribute to the growth and development of society. Originality/value: This study contributes to the originality of m-learning development by proposing an enhanced UTAUT model that considers anxiety and emphasizes the critical role of foreign learners' BIs. It provides fundamental guidelines for designing and evaluating m-learning in ERT contexts. [ABSTRACT FROM AUTHOR]

Education for sustainability refers to educational policies that focus on shaping a sustainable future. Mobile learning software refers to the use of mobile applications through smart devices for promoting online learning. However, the effectiveness of such software in learning for sustainability depends on users' intention to adopt it. While there is growing interest in using mobile technology for sustainability education, empirical evidence on how personalized mobile software can influence users' attitudes and behaviors toward sustainable practices is limited. Thus, this study investigates the factors that affect users' acceptance of mobile learning technology in sustainability education, by integrating environmental awareness and personalization strategies into a modified model based on the unified theory of acceptance and use of technology (UTAUT). A total of 120 users participated in the survey. An empirical analysis of data was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the relationship between the variables of the model. The results showed that both environmental awareness and personalization strategies had a significant effect on users' behavioral intentions. In addition, hedonic motivation and habit exerted an effect on behavioral intention, contrary to effort expectancy and social influence. These findings confirm that a personalized mobile learning application related to environmental issues reveals as a powerful tool for supporting environmental education since such software appears to have high acceptance by the user. The significance of the study lies in its potential to inform the design and development of personalized mobile applications for sustainability education. The study contributes to the creation of more effective mobile applications that promote sustainable behavior and contribute to a more sustainable future by identifying the elements that influence user acceptance. [ABSTRACT FROM AUTHOR]

User experience or usability is under research, particularly in mobile learning in the era of industrial revolution (IR) 5.0. This article discusses incorporating sophisticated mobile technologies such as augmented reality (AR), virtual reality (VR), and artificial intelligence (AI) into the user experience in educational settings. Therefore, this paper investigates the relatively new revolutionary potential of mobile learning user experience in the context of the IR 5.0, where the digital and technology spheres meet for better user experiences, particularly for students in learning. The research explores novel meta-mobile technology approaches by examining concrete cases from 2012, analyzing their impact, and improving the user experience. Likewise, this article elucidates the need for mobile learning user experience research based on bibliometric analysis. [ABSTRACT FROM AUTHOR]

E-learning is the process of sharing knowledge out of the traditional classrooms through different online tools using internet. The availability and use of these tools are not easy for every student. Many institutions gather e-learning feedback to know the problems of students to improve their systems. In e-learning systems, typically a high volume of electronic feedback is received every day. In order to respond to feedback quickly and to address the issues raised by the stakeholders timely, it is desirable to provide an intelligent and automatic classification of the feedback. This study proposes a feedback classification model, named "ACME: Automated Classification Model for E-learning Feedback" to fulfill this need. The proposed model is capable of both sentiment analysis and category classification of the feedback. In this regard, feedback from 20,000 records has been collected from many online sources, such as social media platforms, surveys, and questionnaires. To build a baseline corpus, these feedbacks were analyzed and characterized in two dimensions, that is category and sentiment. The model achieved an accuracy of 98% and 99% by using a Random Forest and Decision Tree classifier, respectively. [ABSTRACT FROM AUTHOR]

This study developed a VR-based mobile learning system to simulate the natural environment of a geopark for university students to learn geological knowledge. This learning method used a Google cardboard equipped with smartphones, where students can watch stereoscopic scenes and experience virtual environments as if visiting the geopark. In order to evaluate the learning effectiveness of the proposed system, we collected the learning outcomes, learning motivation, and cognitive load of students before and after the learning activity. The results indicated that students had significantly better learning achievement in their comprehension ability and learning motivation after using the proposed system. Therefore, it can be inferred that the VR-based mobile learning system not only helps students restructure knowledge and improves their comprehension skills but also enhances their learning motivation tendencies. In addition, the results showed that the students did not have high intrinsic and extraneous cognitive loads but had a high germane cognitive load. This finding implies that the proposed system can promote students' learning without overloading their working memories. [ABSTRACT FROM AUTHOR]

Introduction: This study explores the motivators to use learning management systems (LMS) adopted and used in eLearning by Hong Kong universities among Mainland Chinese postgraduate students amid COVID-19 pandemic. Methods: An adapted and extended UTUAT2 model was first proposed and tested using the structural equation modeling approach. Through self-report online questionnaire, data were collected in 2022 from 352 Mainland Chinese postgraduate students of nine universities in Hong Kong. The reliability and validity of the data were tested using the confirmatory factor analysis, followed by path analysis to test the hypotheses in the proposed model. Results: The study revealed nine motivators which explained 50% of the variance in LMS use intention. Trust (0.204), instructor characteristics (0.202), performance expectancy (0.181), and facilitating conditions (0.181) were identified as strong motivators of behavioral intention. Other factors such as effort expectancy (0.148), learning value (0.118) and social influence (0.115) also had significant positive effects on LMS use intention. Habit (0.014) and hedonic motivation (-0.016) had no significant direct effect on it. Discussion: These findings provide inspirations for educational stakeholders to promote the acceptance of LMS platforms among distance and online learners who adopt the cyberspace as the only means of learning. They also offer insights about instructor recruitment and evaluation methods. [ABSTRACT FROM AUTHOR]

To solve the problem of mobile robots needing to adjust their pose for accurate operation after reaching the target point in the indoor environment, a localization method based on scene modeling and recognition has been designed. Firstly, the offline scene model is created by both handcrafted feature and semantic feature. Then, the scene recognition and location calculation are performed online based on the offline scene model. To improve the accuracy of recognition and location calculation, this paper proposes a method that integrates both semantic features matching and handcrafted features matching. Based on the results of scene recognition, the accurate location is obtained through metric calculation with 3D information. The experimental results show that the accuracy of scene recognition is over 90%, and the average localization error is less than 1 meter. Experimental results demonstrate that the localization has a better performance after using the proposed improved method. [ABSTRACT FROM AUTHOR]

The fast and nondestructive identification of mobile phone cases is a crucial task for law enforcement personnel in the field of forensic science. Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) has been employed in conjunction with feature extraction and deep learning algorithms to develop a method for distinguishing mobile phone cases. As preprocessing steps, multivariate scatter correction and standard normal variate were performed. Feature variables were extracted using the competitive adaptive reweighted sampling and shuffled frog leaping algorithm. Several supervised pattern recognition methods, namely ResNet50, VGG16, and multilayer perceptron (MLP), were utilized for constructing classifiers. The results indicated that the model's performance based on multivariate scattering correction (MSC) with competitive adaptive re-weighted sampling (CARS) surpassed that of other approaches. Notably, the ResNet50 model exhibited superior discriminative ability compared to the VGG16 and MLP models, achieving 100% accuracy in the differentiation of all samples. This designed method represents a potentially rapid and nondestructive approach for identifying mobile phone cases in forensic science. [ABSTRACT FROM AUTHOR]

Objective To analyze the relationship between parental academic upward social comparison perception (PAUSCP) and mobile phone dependence tendency (MPDT) among children, and explore the chain mediation of learning boredom(LB) and academic self-handicapping(ASH).Methods In October 2023,1 024 higher primary school pupils were tested with parental academic upward social comparison perception scale, academic self-handicapping scale, learning boredom scale, and mobile phone dependence tendency scale, and process 4.3 were used to analyze mediation. Results Not detected tendency accounted for 54.78%, potential Children's MPDT accounted for 27.25%, and MPDT accounted for 17.97%. Boys(χ² = 10.975,P = 0.004), grade(χ² = 47.055,P < 0.001), relationship with parents(χ² = 28.453,P < 0.001) and residence(χ² = 14.128,P = 0.007)was correlation factors. Total indirect effect of PAUSCP → MPDT was 0.115(95%CI: 0.090,0.142), effect size PM = 58.67%. Indirect effect of PAUSCP→LB→MPDT was 0.064(95%CI: 0.042,0.090).Indirect effect PAUSCP→ASH→MPDT was 0.024(95%CI: 0.013,0.038).Indirect effect of PAUSCP→LB→ASH→MPDT was 0.027(95%CI: 0.018,0.040).Conclusion Parental academic upward social comparison perception can indirectly affect mobile phone dependence tendency among children through learning boredom and academic self-handicapping. [ABSTRACT FROM AUTHOR]

The purpose of this study was to examine the perceived empowerment of children through the use of a digital musical instrument (DMI) mobile app from the perspective of early childhood educators. Twenty-eight early childhood educators were invited to attend a workshop and guided in the use of a motion-based DMI mobile app, evaluating its potential to empower children to make music within a classroom setting. While participants' positive responses revealed that the accessibility afforded by the mobile technology could help the children overcome the instrumental learning thresholds and enjoy the music-making process, along with the competency developments afforded by the learning tool, limitations, in the form of ethical and societal considerations, hinted that the fluent adoption of the DMI mobile app in the teaching and learning process may be affected. The findings of this study shed light on the design of music and mobile technology for potentially furthering children's musical explorations. [ABSTRACT FROM AUTHOR]

Background: Digital health technologies are increasingly used by healthcare professionals working in pediatric hospital and rehabilitation settings. Multiple factors may affect the implementation and use of digital health technologies in these settings. However, such factors have not been identified in a multidisciplinary, pediatric context. The objective of this study was to describe actual use and to identify the factors that promote or hinder the intention to use digital health technologies (mobile learning applications, virtual/augmented reality, serious games, robotic devices, telehealth applications, computerized assessment tools, and wearables) among pediatric healthcare professionals. Methods: An online survey evaluating opinions, current use, and future intentions to use digital health technologies was completed by 108 professionals at one of Canada's largest pediatric institutes. Mann-Whitney U tests were used to compare the attitudes of healthcare professionals who intend to increase their use of digital health technologies and those who do not. Linear regression analyses were used to determine predictors of usage success. Results: Healthcare professionals reported mostly using mobile and tablet learning applications (n = 43, 38.1%), telehealth applications (n = 49, 43.4%), and computerized assessment tools (n = 33, 29.2%). Attitudes promoting the intention to increase the use of digital health technologies varied according to technology type. Healthcare professionals who wished to increase their use of digital health technologies reported a more positive attitude regarding benefits in clinical practice and patient care, but were also more critical of potential negative impacts on patient-professional relationships. Ease of use (β = 0.374; p = 0.020) was a significant predictor of more favorable usage success. The range of obstacles encountered was also a significant predictor (β = 0.342; p = 0.032) of less favorable evaluation of usage success. Specific factors that hinder successful usage are lack of training (β = 0.303; p = 0.033) and inadequate infrastructure (β = 0.342; p = 0.032). Conclusions: When working with children, incorporating digital health technologies can be effective for motivation and adherence. However, it is crucial to ensure these tools are implemented properly. The findings of this study underscore the importance of addressing training and infrastructure needs when elaborating technology-specific strategies for multidisciplinary adoption of digital health technologies in pediatric settings. [ABSTRACT FROM AUTHOR]

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The rapid advancement of technology and the push toward digitalizing the educational system have led higher education institutions to explore mobile solutions as alternatives to traditional study methods. These mobile applications aim to enhance the university experience by offering instant access to educational resources and simplifying the management of academic processes. This paper seeks to explore the range of existing mobile learning applications, focusing on their functionalities and user experience. Additionally, the study examines how these educational apps impact students' academic lives, specifically looking at factors such as academic performance, productivity, engagement, and social interaction. The research adopts a methodological approach centered on collecting statistical data regarding the adoption of mobile solutions in the academic sector. Results indicate a growing use of mobile applications at the university level, primarily due to their portability and the quick access they provide to educational materials. The study also reveals a positive impact on both students and faculty, enhancing communication and interaction from both an educational and social perspective. [ABSTRACT FROM AUTHOR]

Copyright of Turcology Research is the property of Ataturk University Coordinatorship of Scientific Journals and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: In India, the leading cause of mortality for those aged 15-39 in 2016 was reported to be suicide. Despite these alarming statistics, efforts to prevent suicide are nevertheless thwarted by a number of obstacles to getting help. Timely identification is essential to ensuring that people at risk of suicide receive the right care and assistance. The World Health Organization's mental health action plan advocates employing self-help treatments through electronic and mobile technologies in addition to other steps to promote accessibility to and availability of evidence-based mental health services with encouraging results. With encouraging results, technology has been utilized to give self-help and guided psychological therapies, and it may be employed as a low-intensity and low-cost tactic to reach a bigger population in need of care. Aims and Objectives: The objectives of this study were to study the comparison of mobile application versus conventional teaching techniques for implementation of suicide risk assessment among medical students. Materials and Methods: Study comprises MBBS students. Sample size was calculated to be 138, with 67 in Group A (conventional teaching) and 67 in Group B (mobile teaching). Week 1 and 2 - students were randomly allocated into Group A and B. Both the groups were taught about suicide risk assessment. Results: We found that 87.61% found the mobile application easier to comprehend than the conventional teaching methods. Conclusion: Mobile application learning for implementation of suicide risk assessment in MBBS students is non-inferior to conventional teaching methods. [ABSTRACT FROM AUTHOR]

Road conditions, often degraded by insufficient maintenance or adverse weather, significantly contribute to accidents, exacerbated by the limited human reaction time to sudden hazards like potholes. Early detection of distant potholes is crucial for timely corrective actions, such as reducing speed or avoiding obstacles, to mitigate vehicle damage and accidents. This paper introduces a novel approach that utilizes perspective transformation to enhance pothole detection at different distances, focusing particularly on distant potholes. Perspective transformation improves the visibility and clarity of potholes by virtually bringing them closer and enlarging their features, which is particularly beneficial given the fixed-size input requirement of object detection networks, typically significantly smaller than the raw image resolutions captured by cameras. Our method automatically identifies the region of interest (ROI)—the road area—and calculates the corner points to generate a perspective transformation matrix. This matrix is applied to all images and corresponding bounding box labels, enhancing the representation of potholes in the dataset. This approach significantly boosts detection performance when used with YOLOv5-small, achieving a 43% improvement in the average precision (AP) metric at intersection-over-union thresholds of 0.5 to 0.95 for single class evaluation, and notable improvements of 34%, 63%, and 194% for near, medium, and far potholes, respectively, after categorizing them based on their distance. To the best of our knowledge, this work is the first to employ perspective transformation specifically for enhancing the detection of distant potholes. [ABSTRACT FROM AUTHOR]

The post-COVID-19 period presents an opportunity to build on the teaching and learning strategies that higher education institutions adopted during the pandemic. While there is substantial literature on general higher education needs, there is a noticeable gap concerning teaching and learning needs in special needs and inclusive education within an Open and Distance e-Learning (ODeL) environment. This paper addresses the research question: "How are teaching and learning innovations in inclusive education offered in a higher education ODeL environment?" Rooted in constructivist philosophy, the study used a qualitative research approach to capture the real-life experiences of ten tutors from the Zimbabwe Open University, Faculty of Education, selected through criterion sampling based on their expertise, experience, and involvement in supporting students with diverse needs in ODeL. Open-ended interviews allowed participants to fully express their insights, with data coded using open coding and presented through descriptive narratives. The study identified several innovative teaching and learning strategies, including Google Classroom, Microsoft Teams, WhatsApp Audio and Video, Mobile Learning (M-Learning), Video Learning Environment, and Moodle-based learning platforms (LMS) such as MyVista, which have significantly enhanced the accessibility of educational materials. While these innovations represent progress in inclusivity, challenges such as equitable access to resources, especially for students in rural and under-resourced areas, remain. The study recommends that universities facilitate access to affordable e-learning tools and enhance digital platform accessibility by incorporating features like text-to-audio, video captions, and interactive content. [ABSTRACT FROM AUTHOR]