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Knowledge Inference Combining Convolutional Feature Extraction and Path Semantics Integration
Get PDFMany knowledge representation models extract local patterns or semantic features using fact embeddings but often overlook path semantics. There is room for improvement in pathbased approaches that rely solely on single paths. A customized convolutional neural network (CNN) architecture is proposed to encode multiple paths generated by random walks into vector sequences. For each path, the feature sequence is then merged into a single vector using bidirectional long short-term memory (LSTM) by concatenating both forward and backward hidden states. Semantic relevance between different paths and candidate relations is computed using the attention mechanism. The state vectors of the relations are calculated using weighted paths. These paths help determine the probabilities of the candidate relations, which are then used to assess the validity of the triples. Link prediction experiments on two benchmark datasets, NELL995 and FB15k-237, demonstrate the advantages of our solution. Our model shows a 7.19% improvement at Hits@3 on FB15k-237 compared to Att-Model + Type, another advanced model. The model is further applied to a large complex dataset, FC17, as well as a sparse dataset, NELL-One, for few-shot reasoning
Unravelling Technology Acceptance: Lessons Learnt from Teacher's Experience During COVID-19 for Post-Pandemic Systemic Education
Get PDFThe COVID-19 pandemic presented a unique environment to understand education technology acceptance and adoption. The pandemic acted as a catalyst, encouraging higher education (HE) institutions to rapidly transition from traditional learning environments to technology-driven learning environments. While the motivation for this transition at an institutional level was driven by the need for operational continuation and survival, this rapid transition transferred an increased responsibility to the teacher. Extant research in the context of education technology acceptance and adoption during the COVID-19 pandemic gives substantial emphasis to the learner’s experience since the learner is often seen as being on the receiving end of this transformation. However, in this narrative, the teacher is often overlooked. Through a systematic literature review of technology acceptance and adoption during the COVID-19 pandemic, we examine themes surrounding the teacher’s experience to address the research questions. When the teacher or instructor is the subject of the study, how have learning technologies influenced their role? and What factors encourage or influence teachers’ acceptance of learning technologies? Key findings from this study reveal that the role of the teacher in this technology-driven learning environment shifts from instructor to facilitator, positioning them as an extension of technology. As a result, the teacher determines how the educational technology is perceived by the learner as useful or easy to use. The findings of this study recognise considerations for HE institutions in this age of digital transformation while also presenting new avenues for research in the domain of technology acceptance and adoption
Transforming Music Education Through Artificial Intelligence: A Systematic Literature Review on Enhancing Music Teaching and Learning
Get PDFThe advent of artificial intelligence (AI) has brought significant and transformative alterations to traditional music education. This study examines the progress of AI technology in music education by conducting a systematic review using the PRISMA methodology. Articles were selected for inclusion based on the criterion of specifically describing the utilization of AI in the instruction and acquisition of music. The search was performed on April 9, 2024, via the Web of Science and SCOPUS databases. The search terms “music education” and “artificial intelligence” were employed to ascertain relevant scholarly research. The group of papers underwent scrutiny by various researchers to ascertain their adherence to the established criteria. The articles that were verified by a minimum of two researchers were chosen. 31 articles were finally screened, and the results were divided into two sections: the development of AI in music education and innovative music pedagogy based on AI. A key finding is that the implementation of bibliometric analyses suggests that AI research in music education is still in its infancy. Prior research has primarily concentrated on music instruction at the university level, with a particular emphasis on the integration of AI in music education in China. In addition, this study identifies four specific facets of AI through the reshaping of music pedagogy: enhancing personalized music teaching, providing timely feedback on learning, supporting interactive experiences, and providing organized digital materials
Augmented Reality in Mobile Learning: Enhancing Interactive Learning Experiences
Get PDFA new platform for learning in a mobile environment was established by improvements in e-learning technologies. However, probably because of the low level of interactive learning content, many of the concepts in mobile-based learning environments have begun struggling to engage students. Therefore, this study paper proposes an augmented reality (AR) technique for the enhanced interactive learning experience for the students. A new platform for learning in a mobile environment was established by innovations in e-learning technologies. Unsurprisingly, owing to a tiny amount of interactive learning content, many of the concepts in mobile-based learning environments are now underperforming to engage students. To erect the mapping process for mobile task learners and empower the software of AR through mobile with the parameter, the deployment of mobile learning parameters is also appreciated. This study analyzes how AR could impact traditional learning methodologies by using mobile devices to combine digital information with actual surroundings. It achieves this by carrying out an in-depth evaluation of the most current research and an analysis of case studies. In regards to considerable accomplishments, AR in mobile learning might improve student engagement, boost experiential learning, and support better knowledge retention. The publication additionally includes implementation-related difficulties for AR, such as technological barriers and the prerequisite for revised instructional schemes. The study finalizes with proposals for future research to advance our comprehension of and enhance the value of AR applications in educational contexts and additionally suggests to educators and developers how to fully utilize the beneficial features of AR in mobile learning
The Influence of Mobile Technology on STEM Education Student Learning Outcomes
Get PDFIn many educational institutions, the adoption of mobile learning continues to be a growing topic. As has been considered recently, wireless technologies are currently employed by mobile technology to spread and exchange data via thinking, communicating, exchanging, and understanding. As a consequence, merging mobile technologies into teaching and learning can enhance the ambiance in higher education. Thus, the purpose of this investigation is to implement mobile learning to examine students’ applications in the framework of educational technology. The use of mobile technologies in STEM education is always efficient and engaging for the students. According to its potential to redefine traditional classroom learning paradigms, the inclusion of cellular phones into STEM (science, technology, engineering, and mathematics) education has drawn significant interest. Three artificial intelligence education (AIEd) paradigm structures are utilized to narrow our exploration of how AI is influencing the STEM sectors. An established cross-disciplinary topic of research dealing with leveraging artificial intelligence (AI) approaches to improve training is defined as AIEd. There seems to be an increasing desire to harness AIEd’s promise to tackle academic barriers in STEM fields. The implications of mobile phones on the educational outcomes of students in STEM education settings are explored in this study. By performing a deep review of existing scholarship and empirical investigation, we look for the impact of mobile devices, functions, and platforms on pupil engagement, understanding, and performance in multifaceted STEM fields. A learning approach entitled STEM Project-Based Learning merges project-based curriculum design with the STEM approach to education. As a whole, pupils’ science and technology literacy were improved by the STEM mobile learning package on the ecosystem. Certain learning packages deserve to be studied isolated, while others might be given outright during offline or personal conversations
Generative Artificial Intelligence on Mobile Devices in the University Preparation of Future Teachers of Mathematics
Get PDFThe integration of artificial intelligence (AI) is revolutionizing the field of education. The possibilities of AI in education range from providing intelligent tutoring to facilitating computational thinking, a key skill in an AI-based society. As education systems around the world adapt to technological advances, the need for teachers to develop AI skills becomes crucial. This paper explores the use of AI on mobile devices to improve the preparation of future mathematics teachers. We acknowledge the need for teachers to be skilled in the use of AI tools to foster collaborative, effective, and ethical learning environments. We also provide a case study of our implementation of the generative AI ChatGPT in the preparation of future mathematics teachers at the Faculty of Mathematics, Physics and Computer Science at Comenius University in Bratislava. After this implementation, we analyzed students’ opinions on the application of AI in selected areas. We present the results of this analysis and the implications for the practical use of AI in the university education of future mathematics teachers. Finally, based on our study results, we highlight the possibilities of the successful use of AI in different aspects of teaching and its temporary limitations, which are likely to be reduced by further technological developments
Metaverse Applications in Education 4.0: A Decade of Systematic Literature Review
Get PDFThe advent of Education 4.0, which aligns with the fourth industrial revolution, has been significantly influenced by advancements in digital technologies. Central to this evolution is the metaverse, a virtual shared space that merges augmented reality, virtual reality, and physical reality. This paper delves into the metaverse's applications within Education 4.0, highlighting its potential to revolutionize learning experiences, enhance collaboration, and improve access to quality education. By reviewing current literature and case studies, we identify the primary benefits, such as increased engagement, personalized learning, and broader accessibility. Additionally, we address the challenges associated with metaverse integration, including technical limitations, privacy concerns, and the need for new pedagogical approaches. Through a mixed-methods research approach, combining qualitative and quantitative data along with expert interviews, this paper provides a comprehensive overview of the metaverse's role in future education. The findings suggest that while significant hurdles remain, the metaverse offers a promising avenue for transforming educational practices to meet the demands of the digital age, ultimately fostering more dynamic, inclusive, and effective learning environments. Future research should focus on evaluating long-term impacts and developing standards for metaverse applications in education
Improving the Imbalanced Data Accuracy Using CNN and ReLU
Get PDFIn today’s academic world, learning from datasets is a trendy topic. In the event of imbalanced data, none of the many data mining tools available for this purpose work well, partly because this type of data generates a range of minority classes, which might obstruct the learning process. In addition to its enormous volume, big data has the traits of speed and variety. In this paper, the authors have proposed a CNN model with a rectified linear activation function (ReLU) activation function to get good accuracy on an imbalanced dataset. The dataset used in this paper was electrocardiogram (ECG) heartbeat categorization
Material Selection and Design Methods for Flexible RFID Tag Antenna
Get PDFIn recent years, advancements in flexible printed electronics have significantly propelled the development of wearable devices, especially in areas of integration, comfort, and streamlined manufacturing. By incorporating electronic components and conductive coatings onto flexible substrates, circuits gain enhanced flexibility and some degree of stretchability. Among these circuits, radio frequency identification (RFID) tag antennas have emerged as a focal point in wearable device communication due to their adaptability in power selection and their compatibility with printed circuit technologies. When designing flexible and stretchable RFID tag antennas using printed electronics, two critical factors need to be addressed. The first is the antenna’s structural design, which must account for varying environments and usage contexts. The second is the development of the antenna prototype, involving the selection of conductive coatings and flexible substrates, as well as the printing processes and performance evaluation standards. This paper will explore common conductive coatings and substrate materials used in flexible printed electronics, along with the design methods of printed tag antennas for wearable applications. Lastly, a novel approach is proposed in which the flexible and stretchable RFID tag antenna itself functions as a strain sensor for posture or pressure detection. Unlike conventional strain sensors, this design eliminates the need for additional communication modules, offering a simplified structure that can be easily printed onto clothing, thereby streamlining the production process
Review of Healthcare Workers’ Strategies for Coping with the Stress of COVID-19 and Their Relevance to the Future of Society and Education
Get PDFThe literature on frontline healthcare professionals’ coping strategies in the face of COVID-19 stress is growing rapidly, highlighting their high risk of stress and strain associated with the pandemic. This study examines the methods they use to cope with this stress, analyzing 21 articles out of 2560, published between 2019 and 2023 on PubMed, Google Scholar, and ScienceDirect. The results show that social support and proactive emotion management are essential for maintaining psychological health. The stress management strategies employed by healthcare staff in response to the COVID-19 pandemic are of paramount importance to society and education. By recognizing the importance of social support and emotional management for their psychological health, we are strengthening social resilience. The psychological support programs offered to healthcare workers prepare them to face challenges constructively, thereby contributing to a more resilient and engaged society