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检索条件"任意字段=5th International Conference on Learning and Teaching in Computing and Engineering, LaTiCE 2017"

共 328 条记录，以下是31-40 订阅

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Online learning in teaching Initial Math Education 5th

Online Learning in Teaching Initial Math Education

引用

5th international conference on Recent Innovations in computing, ICRIC 2022

作者： Pokorný, Milan Trnava University Trnava Slovakia

ISBN: (纸本)9789811998751

the paper summarizes experience with online learning in teaching Initial Math Education at Trnava University, Faculty of Education. In the winter term of the academic year 2021/2022, as a result of COVID-19, face-to-face lessons were limited and teachers had to rely on synchronous and asynchronous forms of online learning, regardless of their previous experience with proper utilization of modern technologies in education. thus, the subject Initial Math Education was taught by a combination of pre-recorded video lessons, the e-learning course, and face-to-face lessons with a small number of students in a classroom and majority of students connected via Teams. An analysis of the students’ results in a final test revealed that this form of teaching was efficient and helped to reduce a possible negative impact of COVID-19 on a students’ knowledge level. Moreover, the analysis of students’ answers in a questionnaire revealed further benefits of this method of teaching, including an increase of the sense of final evaluation objectivity, as well as an increase of students’ satisfaction with their own results. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Students

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Semi-FLChain: Toward Secure and Efficient Semi-Supervised Federated learning for IoT Using Blockchain 5

Semi-FLChain: Toward Secure and Efficient Semi-Supervised Fe...

引用

5th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2023

作者： Qi, Yuanhang Liu, Guisong School of Computer Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu611731 China School of Computer Science University of Electronic Science and Technology of China Zhongshan Institute Guangdong Zhongshan528402 China School of Computing and Artificial Intelligence Southwestern University of Finance and Economics Sichuan Chengdu611130 China

ISBN: (纸本)9798350333442

this paper proposes a novel semi-supervised federated learning (SSFL) algorithm for Internet of things (IoT) systems using blockchain technology, called Semi-FLChain. the algorithm is designed to improve the efficiency and security of SSFL by combining hybrid data augmentation and Bayesian estimation to enhance the consistency regularization and pseudo-labeling methods in SSFL. the proposed algorithm aims to overcome the limitations of existing SSFL methods, such as the low accuracy of pseudo-labeling and the high computational cost of consistency regularization. the use of blockchain technology in Semi-FLChain further ensures the security and privacy of IoT devices and their data during the training process. the experimental results demonstrate that Semi-FLChain outperforms state-of-the-art SSFL algorithms in terms of both accuracy and efficiency, making it a promising solution for secure and efficient federated learning in IoT systems. © 2023 IEEE.

关键词： Blockchain

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Optimalization Jaro Winkler Algorithm Using Fuzzy Logic to Evaluate Essay Questions in E-learning System Based Microserver 5

Optimalization Jaro Winkler Algorithm Using Fuzzy Logic to E...

引用

5th international conference on Vocational Education and Electrical engineering, ICVEE 2022

作者： Editya, Arda Surya Kurniati, Neny Lisdiyanto, Angga Irsyad, Moch. Nafiul Mahendra, Wahananta Izha Informatics Engineering Universitas Nahdlatul Ulama Sidoarjo Sidoarjo Indonesia

ISBN: (数字)9781665475815

ISBN: (纸本)9781665475815

Microserver is a server device that has limited computing power. However, this technology is widely developed due to the use of very minimal power so that it can be turned on using battery power. One of the uses of this microserver is as an E-learning server. E-learning is a system that helps in the distance learning process where with the E-learning system teachers and students can interact in learning. One of them is teaching, giving assignments, to exams. One of the features in E-learning is the Computer Based Test System feature. Computer Based Test system offers the convenience of administering an exam. the exam itself sometimes takes a long time in terms of correcting answers. However, there are several weaknesses in the Computer Based Test system system which does not have a feature to correct answers in the form of essays. therefore, in this study, a method for correcting an essay answer will be offered using the Jaro Winkler method combined with a fuzzy logic algorithm. this method offers a high level of accuracy and less computing processed compared to other methods. © 2022 IEEE.

关键词： E-learning

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A Novel teaching Strategy Based on EduCoder Platform for C Programming Language 5th

A Novel Teaching Strategy Based on EduCoder Platform for C P...

引用

5th international conference on Computer Science and Educational Informatization, CSEI 2023

作者： Li, Wei Hei, Xinhong Wang, Lei Wang, Yichuan School of Computer Science and Engineering Xi’an University of Technology Xi’an China Shaanxi Key Laboratory for Network Computing and Security Technology Xi’an China School of Mathematics and Computer Science Shaanxi University of Technology Hanzhong China

ISBN: (纸本)9789819994915

Experimental teaching is an important part of the C programming language course, which aims to cultivate students’ Computational thinking ability, problem solving ability and programming ability. However, the existing experimental teaching mode of the C programming language course has been criticized mainly for their: 1) it is difficult for teachers to check all students’ programs within a limited time;2) Limited computer room capacity, fixed time, and other factors make it difficult to meet the personalized requirements of students. In this paper, we put forward the construction scheme of experimental teaching of the C programming language course based on the EduCoder platform, which alleviates all the above two problems. the scheme follows the fundamental law of engineering practice ability training and constructs a LDEI practice teaching closed loop of "learning (L), doing (D), evaluation (E) and improvement (I)". through specific cases, this paper elaborates the implementation process of this scheme in the experimental teaching of the C programming language course. Finally, a survey are conducted on 64 students from computer science and technology majors. the survey results show that the designed scheme effectively enhances the students’ Computational thinking ability and programming ability. © 2024, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Students

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Improved support vector machine and deep neural network-based rural education platform for data analysis and network education enhancement 5

Improved support vector machine and deep neural network-base...

引用

5th international conference on Telecommunications, Optics, and Computer Science, TOCS 2024

作者： Yang, Jiaxue International Education College Guizhou Normal University Guizhou Guiyang55000 China

ISBN: (纸本)9781510691667

this paper presents the design and implementation of a rural education platform utilizing Improved Support Vector Machine (ISVM) and Deep Neural Network (DNN) methodologies within a cloud computing framework. the platform addresses critical challenges in rural education, including limited access to resources, inadequate infrastructure, and a shortage of qualified educators. By integrating ISVM and DNN, the platform effectively analyzes and predicts the needs of students and teachers, facilitating personalized learning resources and teaching support. Performance evaluations demonstrate that the ISVM-DNN model outperforms traditional SVM and DNN-based SVM models in accuracy, precision, recall, and F1-score, showcasing its superior capability in managing complex, non-linear data. Furthermore, dynamic resource scheduling ensures the platform's scalability and robust performance under high concurrent user loads. User feedback confirms the platform's user-friendly interface and its positive impact on student engagement and teaching efficiency. this study contributes to educational technology by offering a scalable solution that promotes educational equity and quality in rural regions. © 2025 SPIE.

关键词： Deep neural networks

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the Impact of Virtual learning Environments on the Practical Skills of Open Distance learning Students in Electrical engineering 5

The Impact of Virtual Learning Environments on the Practical...

引用

5th international conference on Artificial Intelligence, Big Data, computing and Data Communication Systems (ICABCD)

作者： Hlalele, Sidwell Umenne, Patrice Univ South Africa Elect Engn Johannesburg South Africa

ISBN: (数字)9781665484220

ISBN: (纸本)9781665484220

Open distance learning (ODL) education has been developing rapidly in South Africa. the main reason behind the growth is the demand for online studies created due to the corona pandemic. the ODL system involves study that is not limited by geographical boundaries and extends to many knowledge areas electronically. In practice the study tends to extend to knowledge areas beyond those offered by the standard contact or traditional universities. At the University of South Africa (UNISA), the adoption of the ODL framework to theoretical subjects has been successful by making use of the Sakai virtual learning environment (VLE). the practical subjects or practical knowledge areas on the other hand have previously been taught face-to-face. therefore, the practical modules have not been effectively taught online particularly in the electrical engineering curriculum. this issue can contribute to graduates who are unskilled in the practical component of a knowledge area, which can lead to unemployment. Virtual learning environments (VLE's) play a vital role when it comes to teaching and learning online. In this paper, the impact of VLE's on the practical skills of students and practical knowledge is investigated. this is done by analyzing the change in pass rates of students in a practical subject such as Electrical engineering when taught face-to-face as compared to when taught through a VLE such as Sakai online. Two groups termed as emerging centered learner (ECL) and a developed centered learner (DCL) are investigated. the method evaluates students who study electrical engineering practical module part-time. In this paper the Sakai platform was used as a VLE to teach and then evaluate students in the electrical engineering practical module. the practical guide with the full set of experiments was uploaded on Sakai under additional resources. the students were given the necessary guidelines and tasks via Sakai online, examined and then the pass rates achieved were analyzed

关键词： Electrical engineering Open Distance learning (ODL) Practical's Pass rates Sakai Virtual learning Environment (VLE)

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Evaluation of learning effect based on data analysis and BOPPPS teaching model 5

Evaluation of learning effect based on data analysis and BOP...

引用

5th international conference on E-Business, Information Management and Computer Science, EBIMCS 2022

作者： Li, Zhaomin Zhou, Shangheng College of Electronic Information Engineering Wuhan Business University Hubei Wuhan China

ISBN: (纸本)9781450397834

this paper takes the content of "Collaborative Filtering"in "Data Mining"as an example, discusses the method of course teaching design based on the BOPPPS model, puts forward a student-centered teaching design concept, encourages students to learn independently, and fully taps students' abilities. Interactive teaching practice that realizes the needs of learners' personalized learning and realizes the natural transition from the known to the unknown. the results show that the six-link teaching mode of BOPPPS can effectively stimulate students' interest in learning and strengthen their awareness of autonomous learning. Improve the practical ability, thereby greatly improving the teaching effect. CCS CONCEPTS •Applied computing ∼Education ∼Computer-assisted instruction © 2022 ACM.

关键词： Collaborative filtering

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Ontology Development for Deep learning and Documentation of Heritage Structures 5th

Ontology Development for Deep Learning and Documentation of ...

引用

5th international conference on Protection of Historical Constructions, PROHITECH 2025

作者： Rihal, Satwant Assal, Hisham School of Architecture and Environmental Design Cal Poly State University San Luis ObispoCA United States Noyce School of Applied Computing Cal Poly State University San Luis ObispoCA United States

ISBN: (纸本)9783031873119

Artificial intelligence and machine learning applications (AI/ML) provide unique opportunities for documentation, assessment and protection of world cultural heritage, at risk from natural disasters such as earthquakes, climate change, uncontrolled urbanization, etc. Some examples include the deep knowledge bases of churches/mosques damaged in the earthquakes in Italy in 2016, Mexico 2017, Morocco 2023 and Tukey/Syria 2023. Ontology development provides a unifying view of this data and is crucial for effectively applying deep learning techniques to document and manage heritage structures information. A well-designed ontology serves as a structured knowledge graph that facilitates data integration, search, and analysis. Key aspects of ontology development for heritage structure documentation include Ontology Design to ensure the ontology is generic enough to be applicable across diverse heritage assets, Integration of fragmented data from various sources enabling efficient data acquisition and storage, Deep learning Applications employing the ontology to support deep learning algorithms for semantic segmentation of point cloud data, automated generation of heritage building information models (HBIM) among others, and Knowledge Completion, through models to predict missing information and enhance the quality of the knowledge graphs. Combining ontology development with deep learning techniques, improves heritage structure documentation significantly in terms of accessibility, interpretation, collaboration, and preservation. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Knowledge graph

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Machine learning Approach for Mitigating Security threats in IoT Environment 5

Machine Learning Approach for Mitigating Security Threats in...

引用

5th international conference on Inventive Research in computing Applications, ICIRCA 2023

作者： Saini, Harnit Bala, Saroj Ida, S.Jhansi Kumar, K. Suresh Swetha, Shankerpally Divyabarathi, P. Ajay Kumar Garg Engineering College Department of Cse Ghaziabad India Ajay Kumar Garg Engineering College Department of Mca Ghaziabad India R.M.K Engineering College Department of Computer Science and Business Systems Kavaraipettai India Kongu Engineering College Department of Cse Erode India Cvr College of Engineering Department of Information Technology Telangana India Bannari Amman Institute of Technology Department of Artificial Intelligence and Data Science Erode India

ISBN: (纸本)9798350321425

In today's world, a huge amount of data and information is transferred through wireless networks. the Internet of things (IoT) is a complex network that consists of diverse sensors, devices, and things, which often have limited resources and are susceptible to various security threats, including Distributed Denial of Service (DDoS) attacks. these networks are vulnerable to a variety of cyber threats and privacy issues. Intrusions are harmful activities that can damage a network. IoT networks are particularly vulnerable to security threats. the Bi-Layer Intrusion Detection Model (BIDM) identifies intrusions based on the optimal features selected in the Optimal Feature Vector Selection (OFVS) phase. this scheme not only prevents attacks, but also serves as a defense against legitimate threats. the proposed technique was evaluated using the KDD CUP 99 dataset, a well-known Intrusion Detection System (IDS) benchmark. the performance of the proposed scheme was further analyzed using the NSL-KDD and CICIDS-2017 datasets. the performance of OFVS was also investigated using the relatively new IoT Network Intrusion dataset. the implementation was carried out in Jupyter Notebook using the Python programming language. Matplotlib, Scikit-learn, pandas, and NumPy were some of the packages used in the implementation. the proposed framework achieved high accuracy rates, with NB at 97.4%, SVM at 96.1%, and DT at 98.1%. By utilizing this approach, the security of IoT networks can be significantly enhanced, and the risks associated with DDoS attacks can be mitigated. © 2023 IEEE.

关键词： Denial-of-service attack

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Deep Knowledge Tracing Integrating Multiple learning Behaviors 5

Deep Knowledge Tracing Integrating Multiple Learning Behavio...

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5th international conference on Algorithms, computing and Artificial Intelligence, ACAI 2022

作者： Zhu, Longhai Ji, Yang Beijing University of Posts and Telecommunications Guangzhou China

ISBN: (纸本)9781450398343

By analyzing students' external learning behaviors, knowledge tracing quantifies students' latent knowledge state on this learning task, so as to further develop targeted learning and teaching plans and promote personalized learning. Students' learning behaviors in online learning platforms are diverse, such as exercise, exam and tutorial browsing. However, most of the existing knowledge tracing models only consider exercise and do not fully utilize other behaviors that also reflect students' learning process. In order to solve this problem, this paper proposes a deep knowledge tracing with multiple learning behaviors model (DKT-MLB), which combines multiple learning behaviors with knowledge concepts. the effectiveness of the proposed model is verified by experiments in a dataset built in real online learning platforms. © 2022 ACM.

关键词： Students

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