Online-Journals.org (International Association of Online Engineering)
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Tractor Stability for Agricultural Engineering Students: Learning Through a Project-Based Task
Get PDFMost of the fatalities in the agricultural sector in developed countries are related to machinery use, particularly tractor overturning. Despite its importance, a lack of practical teaching about this topic has been detected in the Agricultural Engineering curricula. For this reason, an active learning activity was planned within a teaching innovation project. The objective of this project was to design a structure as new teaching material to implement and use it to determine the tractor’s center of gravity coordinates. This teaching innovation project was organized in two stages: 1) The design of proposals by students following previously established requirements, and 2) A practical exercise to analyze tractor stability. Each stage involved students from two different Agricultural Engineering degree subjects. Before the second stage, the professor performed the final design of the structure based on previous proposals and later the structure was built. Five different ramp design proposals were received and graded in the first stage. A positive correlation between peer review and the professor’s grades was found. During the second stage, the ramps were used in another subject, in which the grades obtained in the related practical exercise were significantly higher in comparison with those got in the previous year. However, no improvement was found in the final exam grades. This activity involved students in the entire learning process and showed a positive influence on some of the evaluation activities
Bilingual Teaching Environment Creation and Multi-Attribute Teaching Decisions
Get PDFWith the continuous advancement of globalization, bilingual teaching has become an important component of the educational field. However, existing research methods have certain shortcomings in creating a language environment conducive to bilingual teaching and making multi-attribute teaching decisions. To solve this problem, this study conducted detailed research in three aspects. First, bilingual teaching environment creation schemes and their attribute characteristics were discussed, aiming to establish a more comprehensive and systematic language environment model. Second, evaluation indexes for the schemes were selected and weighted, aiming to establish a scientific and reasonable evaluation system. Finally, the specific implementation steps of the multi-attribute teaching decision model were elaborated, providing a comprehensive decision framework. This study not only contributes to the theoretical development of bilingual teaching but also provides a valuable reference for educational practice
Enhancing Students' Metacognition via AI-Driven Educational Support Systems
Get PDFAs the penetration of digital technology deepens and the demands for educational modernization grow, attention is increasingly being drawn towards the application of artificial intelligence (AI) in the field of education. Especially in educational practice, the optimization of students’ learning experiences and the enhancement of their metacognitive abilities through AI technology have captivated the interest of numerous educators and scholars. Metacognition, which represents a core skill in student self-regulation and self-management, has a significant impact on student learning outcomes and quality. However, current educational support systems primarily rely upon traditional methods of data collection and analysis, which have limitations in terms of real-time responsiveness, granularity, and comprehensiveness. The present research aims to investigate the integration of AI technology with a specific focus on the learning process through educational support systems and the development of a cooperative teaching interaction model. This will ultimately enhance the development of students’ metacognitive abilities more effectively
Optimizing Vocational Education Design with Big Data and Educational Technology
Get PDFAmidst the rapid advancements in big data and internet technologies, profound transformations have been witnessed in modern societal and economic structures. Vocational education, a pivotal component within the educational domain, faces challenges in course design and optimization. While the majority of existing research focuses on utilizing educational technology to optimize courses, most methodologies still rely on traditional data analysis and mining techniques, with little exploration of deep learning and big data technologies. This research proposes a novel strategy for course design and optimization. Initially, the course theme optimization is addressed through a short text clustering algorithm that utilizes a linear fusion of the biterm topic model (BTM) and global vectors for word representation (GloVe) similarity. Subsequently, course content is planned using a deep interest network (DIN) recommendation algorithm in conjunction with the gated recurrent unit (GRU) time series model. This study provides the vocational education sector with a new perspective on course design and optimization, which has important theoretical and practical implications
A Bibliometric Analysis of the Intellectual Landscape of Mobile Technology and Higher Education Research
Get PDFTechnology has become a crucial part of higher education. Higher education institutions have adapted to embrace technology-enabled classroom practices to meet the rising expectations of a varied student population while continually enhancing their learning experience. Mobile technology in higher education, in particular, has the opportunity to provide access to or improve education at a low cost with a less demanding infrastructure configuration. In the current study, the researchers aimed to better understand the intellectual landscape of mobile technology and higher education through bibliometric analysis of research articles published in the Scopus database. This research included a study of 277 papers published in Scopus-indexed peer-reviewed journals between 2006 and 2023. The citation network, co-citation analysis, and publication patterns were examined to discover influential work in this domain. Bibliometric analysis was used to identify the most notable journals, authors, nations, articles, and topics, followed by thoroughly examining the content of 277 papers in the identified clusters. The four major themes enumerated are—Rise of mobile learning, E-learning—the blended and collaborative way, Mobile Technologies in higher education, and Student Engagement in the times of mobile learning. The paper provides interesting insights into these emerging themes, the study will assist regulators, policymakers, and academic scholars in understanding the fundamentals of mobile technology and higher education and identifying pertinent topics for further research
Porting a Native Android App to iOS: Porting Process Shown by the Example of the “Schoolstart Screening App”
Get PDFThe two mobile operating systems Android and i(Pad)OS have dominated the smartphone and tablet market for years and app providers have to offer their apps for both systems in most cases in order to be competitive or to be able to reach the majority of potential customers. In native app development, separate applications have to be written and maintained for each platform. Often, apps are developed for one platform first and the second app is developed at a later stage, after some feedback could be collected. This porting from one system to the other can be either (partially) automated or manual, but in any case, it has its challenges. Both systems were designed with different approaches and differ greatly in some parts from each other – not only visually, but also in terms of the underlying structure. To illustrate the porting process, the Android app “Schoolstart Screening App”, which was developed for the Federal Ministry of Education, Science and Research of Austria by Graz University of Technology at the OU Educational Technology, was ported so that it can be used also on iPads. Automated approaches were discussed and the chosen process is explained to get a good overview of the topic
“Let’s Go,” A Mobile Learning Application for Social Studies Subjects: Prototype of Application Development
Get PDFThe value of social studies learning for junior high school students in several schools still needs to be higher. One of the factors of low student scores is the need for more variety in learning methods used by teachers, low student motivation, and the use of learning media that could be more optimal. One way to do this is to develop a learning model with engaging learning media. This research aims to develop mobile understanding by integrating artificial intelligence at the evaluation stage. The methodology used in this research is the waterfall approach method with requirements analysis, design, implementation, testing, operation, and maintenance. The mobile learning prototype was tested on media experts and junior high school student respondents. The dimensions of expert assessment are reviewed from media appearance, quality and use of media, navigation, product strength, media interface, product attractiveness, and material delivery in the media. The dimensions of questions for students consist of 4 points: content, interface, feedback and assessment, and personalization. The research results show a mobile application’s results, including a brain gym menu, problem identification, materials, discussion forums, assignment results, and quizzes. The menus presented make it easier for students to learn. The questionnaire results from experts show that the highest average is 5.00, with a standard deviation of 0.00. The questionnaire results from student respondents had the highest average of 49.714, with a standard deviation of 0.169. The results of the scores obtained in the expert and student respondent questionnaires show that mobile learning is acceptable
The Development of Geomobile App-Based Outdoor Study to Improve Critical-Social Abilities and Collaborative in the 21st Century
Get PDFGeography learning in high school is built through field and contextual experiences to verify the theories. The learning method used by the geography teacher is not quite effective in improving students’ critical-social and collaborative abilities. This study aims to 1) develop a Geomobile app-based outdoor study that is valid and practical, and 2) determine its effectiveness in improving students’ critical-social and collaborative abilities in the 21st century. This study used research and development with a modified version of the Borg and Gall model. This research utilized validity tests conducted by material experts, media professionals, and learning specialists. The authentic instruments used to measure critical-social and collaboration abilities. The data analyst used descriptive statistics to assess the quality of the product and conducted an independent sample t-test to evaluate the effectiveness of the Geomobile app for outdoor study. The research was conducted on 216 eleventh-grade Social Science students in five high schools in East Java Province during the academic year 2021–2022. Research findings show that students need tools to enhance essential skills in the 21st century through the use of Geomobile app-based outdoor study. The development results indicate that expert validation feedback on the Geomobile app is very positive, with an average rating of 93%. Additionally, the Geomobile app has been found to effectively enhance critical-social abilities by 59% and collaborative abilities by 63%. Therefore, this development effectively improves students’ abilities in the 21st century. The research has provided support for students to become future social agents, especially in terms of building a better working place and social community in the 21st century
Electronic Prototype of Autonomous Learning for the Crossing of Pedestrians with Visual Disabilities in Lima
Get PDFDifficulties related to vehicular chaos and obstacles in public spaces hinder the orientation of visually impaired individuals, limiting their autonomy and exposing them to potential accidents. Considering these factors, the objective was to develop a prototype that facilitates autonomous learning by utilizing different electronic components. The aim is to ensure the safe movement of blind pedestrians, promote self-reliance, and minimize the risk of accidents. The proposed prototype is based on the concept of implementing intelligent traffic lights that detect the presence of pedestrians, allowing for safe crossing for both pedestrians and vehicles. The proposed circuit utilizes two ESP32 modules. One module is placed in the traffic light and configured as a Bluetooth master to transmit signals. It is also equipped with an ultrasonic sensor. The other module is located in the user’s wristband and configured as a Bluetooth slave to receive signals. It is also equipped with a horn. The communication between the modules has been developed using the C programming language for microcontrollers in the Arduino IDE development environment. A master-slave communication system was implemented, resulting in the constant reporting of the distance between the pedestrian and the sidewalk within the pedestrian crossing by the ultrasonic sensor. This system controls the safe crossing by regulating the traffic lights. The HC-SR04 ultrasonic sensor can detect distances ranging from 2 cm to 450 cm. Therefore, the prototype can be used as a foundation for future advancements in various cities and contexts, ultimately benefiting blind pedestrians by improving their mobility
A Novel Technique for Brain Tumor Detection and Classification using T1-Weighted MR Image
Get PDFBrain tumors are particularly perilous because they form when cells in the brain multiply uncontrollably within the skull. Therefore, a fast and accurate method of diagnosing tumors is crucial for the patient’s health. This study proposes a method for evaluating brain cancer images. The phases of implementation for the proposed work are as follows: In the first phase, we compiled a set of specialized feature vector descriptions for advanced classification tasks by employing both deep learning (DL) and conventional feature extraction techniques. In the second phase, we employ a proposed convolutional neural network (CNN) approach and a traditional subset of features from a genetic algorithm (GA) to select our deep features. The third phase involves using the fusion method to merge the prioritized features. Finally, determine whether the brain image is normal or abnormal. The results showed that the proposed method successfully classified objects accurately and revealed their robustness across different ages and acquisition protocols. According to the results, the classification accuracy of the support vector machines (SVM) classifier has significantly improved by combining conventional features and deep learning features (DLF), achieving an accuracy of up to 86.50% using the T1 weighted brain MR image