Learning Devices Research Articles

Examining the Impact of Demographics on Students’ Perceptions of Mobile-Assisted Language Learning

Mobile-assisted language learning (MALL) has witnessed significant development, with a growing number of university learners relying on their mobile devices for language learning. However, limited research has been conducted on the influence of demographics, including age, gender, and university level, on students' perceptions of MALL. Addressing this research gap, the current study was conducted at the University of Sidi Mohamed Ben Abdellah, in Morocco, focusing on English department students. The study employed a quantitative approach, utilizing a questionnaire to collect data from 164 students. Through the examination of variables such as gender, age, and university level, the findings indicated that gender did not significantly impact students' acceptance of MALL while age and university level emerged as influential factors in shaping students' preferences. These findings highlight the potential effectiveness of MALL as a language learning tool. The results are particularly relevant for informing policymakers considering the implementation of MALL-based systems in higher education. Furthermore, educators are invited to consider their student cohorts' diverse age and university-level characteristics and adapt MALL activities accordingly.

Exploring learners' experiences with mobile technology: Academic uses and barriers

In an increasingly digital era, mobile technology has become an integral part of our daily lives, permeating various aspects, including education. With its portable nature and wide range of functionalities, mobile devices offer new opportunities for learners to access information, collaborate with peers, and engage in interactive learning experiences. This article investigates university learners' experiences with mobile technology, as well as their perceived barriers to such experiences in the context of English language learning. The study employs a mixed-methods approach, comprising surveys and interviews to investigate students' practices and barriers related to using mobile technology for language learning. The quantitative stage involves a sample of 142 participants, while the qualitative stage focuses on a subset of 16 participants selected for representation and diversity. The findings show extensive reliance of students on their devices for on-campus and off-campus learning activities, including chatting with AI models, social networking, app-based learning, and watching course-related videos. Furthermore, several barriers pertaining to the device, the teacher, and the learner were identified as obstacles to the effective use of mobile technology for academic purposes. Overall, this study stresses the potential of mobile devices for language learning and offers valuable insights into how students use them. Language teachers and researchers can utilize these findings to maximize the benefits of mobile technology while mitigating its drawbacks.

Differences in and relationship between digital access, use, connectivity, skill, engagement, and motivation: implications for digital inequality in online learning among first-generation and continuing-generation undergraduate students

Disruptions in education may exacerbate digital inequality among college student groups. This study examined differences in and relationships between digital access, use, and connectivity, digital skills and engagement, and academic motivation among first-generation (learners whose parents/guardians have no college education) and continuing-generation (learners whose parents/guardians have a college education) undergraduate students in the United States (N = 1224; M age = 21, 902 women, 56.8% first-generation status) in the context of COVID-19. Most first-generation and continuing-generation students reported unlimited and stable internet access at home. First-generation students reported less frequent access to fast and reliable internet and using multiple devices for online learning. First-generation and continuing-generation students reported similar levels of digital skills and engagement in online learning. Digital access and various digital skills and engagement were differentially associated with academic motivation. First-generation students reported greater academic motivation than their continuing-generation peers. Implications for reducing digital inequality for undergraduate students are discussed.

Prediction of induction motor faults using machine learning.

Unplanned downtime in industrial sectors presents significant challenges, impacting both production efficiency and profitability. To tackle this issue, companies are actively working towards optimizing their operations and reducing disruptions that hinder their ability to meet customer demands and financial goals. Predictive maintenance, utilizing advanced technologies like data analytics, machine learning, and IoT devices, offers real-time equipment data monitoring and analysis. This research study centers on the development of a versatile machine-learning model for predicting faults in induction motors within industrial environments. Implementing such a model can enable proactive maintenance, ultimately leading to decreased downtime in industrial operations. The study involved the acquisition of a dataset comprising healthy and faulty conditions of four 3-phase induction motors, along with relevant features for fault prediction. Multiple machine learning algorithms were trained using this dataset, exhibiting promising performance. The Random Forest (RF) model achieved the highest accuracy at 0.91, closely followed by the Artificial Neural Network (ANN) and k-nearest Neighbors (k-NN) models, both achieving an accuracy of 0.9. Meanwhile, the Decision Tree (DT) model showed the lowest accuracy at 0.89. Further model evaluation was carried out using a confusion matrix, which provided a detailed breakdown of the models' performance for each class, revealing the number of correctly and incorrectly classified induction motor conditions. The results from the confusion matrix indicate that the models effectively classified the various states and conditions of the induction motors. To enhance model performance in future work, potential avenues include refining the ANN and RF models, exploring transfer learning or ensemble methods, and incorporating diverse datasets to improve generalization.

Exploring Percentages of Elementary School Students Utilizing Visual Electronic Devices for Learning and Homework Assistance.

Exploring Percentages of Elementary School Students Utilizing Visual Electronic Devices for Learning and Homework Assistance.

The impact of mobile learning devices on the English academic performance of college students: factor analysis

The impact of mobile learning devices on the English academic performance of college students: factor analysis

The impact of mobile learning devices on the English academic performance of college students: factor analysis

The impact of mobile learning devices on the English academic performance of college students: factor analysis

Design of Static Electricity Concept Learning Device with Differentiated Strategy In facilitating Inclusive Education

Students' learning needs need to be considered when teaching in the classroom. Implementation of differentiated learning is one of the teaching applications that pays attention to students' needs. The study aims to design static electricity learning devices with a differentiated approach in facilitating inclusive education. The study is part of the development of learning devices consisting of three stages, namely: preliminary stage, development stage and implementation stage. The results show a valid value teaching module with an average value of 81.25 including the valid category. In the implementation, a trial of differentiated learning devices was carried out through teaching in class IX. At this stage, information was obtained on the value of the implementation of learning implementation above 90 including the Very High category. Likewise, student learning outcomes at this implementation stage increased with an N-Gain value of 0.578 including the moderate category. The effect size test value was obtained at 6,510 including a strong effect. This shows that the implementation of the differentiated learning device design has a strong effect on static electricity learning outcomes. The conclusions of the study were obtained as follows: (1) the design of differentiated learning devices assessed by experts and practices is valid; (2) the implementation of the differentiated learning device design is included in the high category, there are two students who have obstacles in the form of slow learners at the regular school which is the trial location; (3) the design of the differentiated learning device which is arranged effectively is shown by the N-Gain value in the medium category and the effect size value in the strong effect category

Assessment of Digital Integration in Learning

This research explores the integration of digital tools, particularly mobile learning, in educational contexts in Nepal, aiming to optimize their effectiveness. Employing a questionnaire-based methodology, data was collected from students across all over Nepal using a Google Form distributed through online media. Insights were gathered from 1104 students, revealing widespread ownership and usage of mobile devices for studying. Findings indicate a preference for laptops and smartphones, with web pages and applications being the most utilized resources. Significant associations were observed between the type of mobile device, academic major, and preference for mobile learning. The study concludes that digital tools play a critical role in modern education, emphasizing the need for comprehensive policies to promote their integration. Recommendations include government initiatives to enhance access to educational devices, conduct proper trainings to learners, expand internet connectivity, address technical challenges, and distribute digital equipment to enhance mobile learning experiences for equity of access to technology all over Nepal.

Enhancing Classroom Management Self-Efficacy through Teacher Professional Education Program: An Explorative Study

Classroom Management Self-Efficacy (CMSE) is crucial for teachers to effectively manage diverse student needs, fostering preparedness, perseverance, and the ability to maintain a productive learning environment. This study examines how Indonesia’s Pendidikan Profesi Guru (PPG), or Teacher Professional Education program, enhances CMSE among certified English teachers. By exploring the experiences of three purposively selected junior high school teachers, this research highlights the role of professional development in building teaching confidence. Data were gathered through a validated CMSE scale, which assessed perceptions across various classroom management domains, and semi-structured interviews that provided rich qualitative insights. Using the interactive model by Miles, Huberman, and Saldana (2014), the analysis revealed two key findings: teachers with high CMSE consistently exhibited perseverance, motivation, and sociability—critical traits for effective classroom management—and participants credited the PPG program, particularly its structured components such as material deepening, learning device development, and teaching practice (PPL), with significantly improving their CMSE. These findings emphasize that well-designed professional development programs not only boost self-efficacy but also equip teachers with practical skills for managing classrooms effectively. The study concludes that sustained engagement in programs like PPG is vital for enhancing classroom management skills and offers valuable insights for shaping teacher education policies and practices to ensure continuous professional growth and improved teaching outcomes.

Integrated Project-Based Learning (PjBL) Learning Tools STEM: Improving Students' Creative Thinking Skills

Integrated STEM-based PjBL learning devices are a learning context designed by teachers to motivate students to take part in learning activities so they can boost their creative thinking skills and discover new ideas. The goal of this study was to examine a learning tool that combines STEM with Project-Based Learning. It looks at whether this tool is suitable, effective, and easy to use in order to help improve creative thinking skills of fourth-grade students of Santo Paulus Martubung Elementary School - Medan. This type of research uses the Research and Development (R&D) development model. The results of the study revealed that the devices developed had significantly improved students' creative thinking skills. The increase in creative thinking skills can be seen from the average n-gain score of 0.49 (moderate increase category). The learning devices developed on the 'Care for the Environment' material are effective in significantly improving students' scientific literacy. The increase in scientific literacy can be seen from the average score of 0.64 (moderate increase category) and increased interest in science and technology, active participation in discovery activities (practice and projects), and responsible management of natural resources and the the area around us after using a project-based learning tool along with a specific method.

Development of Scientific-Based Learning Devices Implemented in the Inquiry-Flipped Classroom Learning Model to Improve Science Literacy in Acid-Base Material

The trend in science education policy in the 21st century emphasizes the importance of scientific literacy in science education as a transferable outcome. This research is a type of Research and Development (R&D) development research. Development research in the field of education aims to produce products for the benefit of education. This research produces a new product in the form of e-LKPD with a scientific approach to acid-base material. The purpose of this research and development is to find out how the procedure for developing teaching materials based on a scientific approach is implemented in the inquiry-flipped classroom learning model to improve Science Literacy skills and to find out the practicality of teaching materials based on a scientific approach implemented in the inquiry-flipped classroom learning model. Based on the results of the validation carried out on material and media experts in two rounds, the results of the first material validation were 89.30%, the second material validation was 98.70%. Design validation was conducted in two rounds where the first round obtained results of 87.50% and the second round of design validation 97.50%. Based on the results obtained from chemistry teachers, the first practitioner validation obtained 87% and the second practitioner validation obtained 91%, student responses to teaching materials with a percentage of 85.50%. Based on the criteria for the interpretation of the percentage of practicality, the group evaluation (student responses) was obtained with practical criteria or feasible for revision

PRELIMINARY STUDY FOR EXPLORING THE CURRENT ISSUES AND ACTIVITIES OF MOBILE LEARNING IN PATTERN-MAKING

Mobile learning is an innovative approach that has transformed education. However, its application in fashion design, particularly garment pattern making, is still under-explored. This study investigated current issues and activities in mobile learning related to garment pattern making in the Fashion and Apparel Certificate Program at Selayang Community College. The objectives were to identify the demographic characteristics of students, examine the types of devices used, explore existing challenges in learning materials, and evaluate students' mobile learning activities. This research employed a quantitative methodology, using a structured questionnaire divided into four sections: demographics, mobile learning devices, current issues, and activities. A total of 64 respondents participated in the survey. The results revealed a significant gender imbalance among students, with 90.6% female. Smartphones and laptops were the primary devices for learning, with Android being the most commonly used operating system. Nonetheless, the findings indicated that current learning materials were incomplete, poorly understood, and lacked engaging visual content. Students relied heavily on YouTube and social media for supplementary learning, highlighting a gap in structured mobile learning resources. The study concluded a critical need for enhanced interactive e-modules tailored to pattern making. These resources should integrate multimedia elements and be optimized for various devices to enhance student engagement and skill development. Note that addressing this gap will significantly contribute to improved learning outcomes in fashion design education, particularly in the area of garment pattern making.

Development of Differentiated Learning Devices to Enhance Numeracy Skills of Students at UPT SMA Negeri 9 Bone

Development of Differentiated Learning Devices to Enhance Numeracy Skills of Students at UPT SMA Negeri 9 Bone

Detection of group-housed pigs feeding behavior using deep learning and edge devices

Abstract The detection of feed behavior at pig farms is essential in monitoring the welfare and health of pigs. Addressing the low automation level of feeding behavior detection in group-housed pig farming, this study proposes a lightweight feeding behavior detection model, GAB-YOLO, based on YOLOv8s. The model employs GhostNet with a Convolution and Self-Attention Mixed Module (ACMix) as the back-bone, enhancing feature extraction capability while reducing parameters. Wise-IoU is utilized as the bounding box loss function to improve sensitivity to piglets. To integrate features of pigs with different body types, a Feature Fusion Module called Bi-directional Multi Feature Pyramid Network (BMFPN) is proposed as the neck part of the model. Experimental results demonstrate that the improved model achieves detection accuracies of 98.40% for drinking behavior and 98.66% for eating behavior in group-housed pigs, representing improvements of 2.79% and 2.99%, respectively, over the original YOLOv8s algorithm, with a 14.5% reduction in parameters. The Deep Simple Online and Realtime Tracking (DeepSORT) algorithm is integrated into the improved model to address the issue of inaccurate video behavior judgment by YOLO, forming the lightweight model GAB-YOLO-DeepSORT. Finally, GAB-YOLO-DeepSORT is deployed on the NVIDIA Jetson Nano. The practical operation on the Jetson Nano shows that the proposed model can track multiple targets for pigs of different sizes and varieties in a group-housed environment, thus ensuring the accuracy of pig feeding behavior recognition and providing support for the subsequent establishment of pig health systems.

Optimalisasi Pembelajaran Praktik Keterampilan Mengajar (PKM) Dalam Pelaksanakaan Program Asistensi Mengajar (AM)

The success of the Teaching Assistance program is supported by the optimal implementation of Teaching Skills Practice (PKM) learning. The good or bad implementation of PKM learning has close implications for the achievement of Learning (CPL) and the success of the Teaching Assistance (AM) program. The purpose of this study was to determine the implementation of Teaching Skills Practice (PKM) learning and the implementation of the Teaching Assistance program in the Social Sciences Education Department, FITK UIN Maulana Malik Ibrahim Malang. The research method uses a qualitative approach with a descriptive analysis research type. The results of the study explain that: The implementation of the Teaching Assistance student program in the Social Sciences Education Department is not optimal and there are still many things that need to be evaluated again, because students are not ready to be deployed to the field. Efforts that can be made to optimize PKM learning in the Social Sciences Education Department are providing learning evaluation courses before implementing teaching assistance, socializing the process of compiling independent curriculum learning devices, providing training on learning media innovation, workshops on developing learning models and strategies, and in the implementation of teaching skills practice courses, it is necessary to emphasize an explanation of the importance of teacher professional ethics.

Exploring the effect of digital and multisensory educational materials on retention in primary school using Tangible User Interfaces

ABSTRACT The spreading of digital tools for learning has been impressive in later years. Some attempts have been made to augment traditional tools with digital solutions, still offering the chance to propose multisensory stimulation and interactivity. In this context, the aim of this study is to strengthen the importance of a multisensorial approach as a key factor in the development of learning devices in educational settings. We focused on investigating if there was a significant difference in knowledge retention when adding to the learning experience the stimulation of increasingly more sensorial channels using tangible interfaces. Results indicate that children recall more information if the interface is enhanced through multisensory materials including auditory, visual, and olfactory stimuli. This effect is even stronger when the time between exposition and recall is longer. This study supports the potential of merging digital and physical elements in educational materials to foster learning, in particular, it adds new data supporting the use of the sense of smell to improve memory retention.

Augmented Reality in Smart Learning Devices: Advancing Cognitive Development and Entertainment

The integration of Augmented Reality (AR) in smart learning devices is transforming the way children engage with educational content. These devices merge physical and digital environments to create interactive, immersive learning experiences, enhancing cognitive development and providing entertainment. This paper explores the current applications of AR in educational devices for children, its impacts on cognitive growth, the role of interactivity, and its potential in future learning environments. The paper also provides a critical review of existing literature, identifying opportunities and challenges in this emerging field. Augmented Reality (AR) has revolutionized how children interact with educational content, offering an immersive, engaging learning experience. This paper explores the integration of AR into smart learning devices and its impact on cognitive development and entertainment for children. We delve into how AR enhances memory retention, problem solving skills, and spatial reasoning while making learning enjoyable. By critically analysing current literature and case studies, we highlight the potential and challenges of using AR to bridge the gap between education and entertainment.

Mobile learning in the classroom – Should students bring mobile devices for learning, or should these be provided by schools?

AbstractIn recent years, the importance of mobile devices has increased for education in general and more specifically for science and mathematics education. In the classroom, approaches for teaching with mobile devices include using student-owned devices (“bring your own device”; BYOD approach) or using school-owned devices from central pools (POOL approach). While many studies point out features of mobile learning and BYOD that are conducive to learning, a research gap can be identified in the analysis of effects of mobile device access concepts on teaching–learning processes. Thus, this study aimed to empirically compare BYOD and POOL approaches in terms of learning performance and cognitive performance (subject knowledge development, cognitive load, concentration performance). Furthermore, the analyses included specific characteristics and preconditions (gender, socioeconomic status, fear of missing out, problematic smartphone use). A quasi-experimental study (two groups) was conducted in year 8 and 9 physics classes (N = 339 students) in which smartphones are used for different purposes. The present data show no group differences between the BYOD and the POOL approach in the group of learners with respect to subject knowledge development, cognitive load, and concentration performance. However, individual findings in subsamples indicate that the POOL approach may be beneficial for certain learners (e.g., learners with low fear of missing out or learners tending toward problematic smartphone use). For school practice, these results indicate that organizational, economic, and ecological aspects appear to be the main factors in deciding about the mobile device access concept.

Design of Energy-Efficient CMOS Circuits for AI Applications

The design of energy-efficient CMOS circuits has become a critical area of research, driven by the escalating demand for artificial intelligence (AI) applications that require immense computational power. This study investigates advanced techniques for optimizing CMOS (Complementary Metal-Oxide-Semiconductor) circuit architectures to enhance energy efficiency without compromising performance. Key areas of focus include reducing dynamic and static power consumption through innovative transistor-level designs, clock-gating strategies, and the integration of advanced materials. Additionally, the research explores the potential of hybrid architectures combining CMOS with emerging technologies like memristors and neuromorphic circuits. By addressing power constraints in AI hardware, the study aims to contribute to the development of scalable, sustainable computing systems for machine learning, neural networks, and edge AI devices. The findings have broad implications for the future of AI hardware, offering solutions that balance computational demands with energy sustainability.