Fog computing is a technology that brings computing, storage, and networking services closer to devices and systems, aiming to improve speed, efficiency, and data processing capabilities for various applications. The ...
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ISBN:
(纸本)9798350394023;9798350394030
Fog computing is a technology that brings computing, storage, and networking services closer to devices and systems, aiming to improve speed, efficiency, and data processing capabilities for various applications. The growing importance of fog and edge computing technologies means we need new and better ways to teach students about these areas. This paper offers a detailed guide on how to use xFogSim, an extended version of the Omnet++ network simulator, for teaching fog and edge computing. We give students a clear path to follow, starting with simple network designs and moving to more complex ones, helping them understand how federated learning works. We tested xFogSim with a group of students and found that it really helps them grasp fog and edge computing ideas better than traditional teaching methods. xFogSim also gives practical information about important performance metrics, helping bridge the gap between what students learn in class and what they need to know in the real world. This paper shows that using xFogSim in classrooms gives students a strong base in distributed computing systems, getting them ready for future tech challenges.
Yoga is a popular practice that promotes physical and mental well-being. The lack of regulation and standardization in yoga teaching and learning can lead to unsafe practices and health issues for practitioners, such ...
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The increasing usage of the Internet of Things (IoT) in various domains, particularly within the realm of artificial intelligence has raised concerns about data privacy. Federated learning has been established to addr...
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ISBN:
(纸本)9798350376357;9798350376340
The increasing usage of the Internet of Things (IoT) in various domains, particularly within the realm of artificial intelligence has raised concerns about data privacy. Federated learning has been established to address this issue. However, federated learning faces challenges such as constrained computing resources on IoT devices, fluctuating network bandwidth, and low scalability due to network congestion during the transition of local weights in a large scale. All of these results in a low convergence time, or even failure in the training procedure. This paper presents a reinforcement learning-based dynamic neural network splitting method called RSF to reduce overall training time with a faster partitioning decision time. The reinforcement learning agent dynamically allocates computational tasks across IoT devices, Edge servers, and the cloud, accelerating the training process in edge computing environments. The neural network partitioning adapts iteratively. The agent decides on the neural network partitioning for each IoT device at the start of each training round. Simulation results demonstrate the effectiveness of our proposed method, achieving substantial speed improvements up to 27%, and higher scalability.
Using learning analytics technology to mine online learning features can optimize the teaching process. On the basis of collecting students' online learning information, the similarity between features is firstly ...
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Language is the link of excellent civilization exchange and inheritance, all cooperation and integration among all ethnic groups, regions and countries. As two big countries on the international stage, China and Russi...
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In the traditional form of instruction, the teacher and pupil converse face to face. The discussion is started by the instructor, who generally discusses the material from the required textbooks. Many students might n...
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teaching the Unified Modelling Language (UML) is a critical task in the frame of Software engineering courses. Teachers need to understand the students' behavior along with their modeling activities to provide sug...
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ISBN:
(纸本)9798350359329;9798350359312
teaching the Unified Modelling Language (UML) is a critical task in the frame of Software engineering courses. Teachers need to understand the students' behavior along with their modeling activities to provide suggestions and feedback to avoid more frequent mistakes and improve their capabilities. This paper presents a novel approach for teaching the UML in Software engineering courses, focusing on understanding and improving student behavior and capabilities during modeling activities. It introduces a cloudbased tool that captures and analyzes UML diagrams created by students during their interactions with a UML modeling tool. The key aspect of the proposal is the integration of a Retrieval Augmented Generation Large Language Model (RAG-based LLM), which generates insightful feedback for students by leveraging knowledge acquired during the modeling process. The effectiveness of this method is demonstrated through an experiment involving a substantial dataset comprising 5,120 labeled UML models. The validation process confirms the performance of the UML RAG-based LLM in providing relevant feedback related to entities and relationships in the students' models. Additionally, a qualitative analysis highlights the user satisfaction, underscoring its potential as a valuable tool in enhancing the learning experience in software modeling education.
The development of non-technical skills, such as critical thinking and public speaking, is increasingly recognized in computing curricula as essential for computing professionals in the job market. Universities are ad...
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ISBN:
(纸本)9798350394023;9798350394030
The development of non-technical skills, such as critical thinking and public speaking, is increasingly recognized in computing curricula as essential for computing professionals in the job market. Universities are adopting active learning methods to cultivate these skills, among which are debate-based teaching methods. Previous literature showed that debating is used in many knowledge domains, and can help develop skills of information synthesis, critical thinking, and effective verbal communication. In spite of these benefits, however, debating in computing education is still rare. This work explores a partial redesign of a debates-based teaching method, called Tech Battles, implemented in a 6-ECTS non-technical course at the University of Trento targeted to first-year Master's students in Computer Science with a minor in innovation and entrepreneurship. Battles have been part of the course since 2013, and over the years the teaching team upgraded the methodology, which now foresees a preparatory activity where students read a science fiction short story assigned by the teachers. In this paper, we discuss how this latest modification changes the course and its impacts: how the workflow of each debate evolved, our criteria for selecting short stories, preliminary observations gathered from the field, and the research methods that will be used to more thoroughly validate the updated method.
Machine learning is a field that was established some years ago with the lofty goal of building computational methods to implement various aspects of teaching, Machine learning (ML) has changed materials science field...
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Software engineering is concerned with how best to create software in ways that promote sustainable development and maximise quality. We have been largely successful at transferring software engineering knowledge into...
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ISBN:
(纸本)9798400704987
Software engineering is concerned with how best to create software in ways that promote sustainable development and maximise quality. We have been largely successful at transferring software engineering knowledge into the industry, however, many challenges in software engineering training remain. A key amongst these is how best to teach practical engineering approaches along with the theoretical concepts behind them. This paper describes our experience of adopting an agile approach for reflective learning and teaching within the context of our Software Systems engineering module, aimed at addressing challenges identified with previous efforts to promote reflective practice. Our study attempts to strengthen the use of reflective learning approaches for our current cohort, as well as introducing reflective teaching practices, whereby we examine our teaching approach in order to improve its efficiency and effectiveness. Our analysis of student response to the module shows that it was very well-received by the students, and we were able to collect ample evidence from feedback to support this. Most of our approaches resulted in positive feedback and contributed to improvements in teaching quality, however, we also identified some key aspects in our method that could still benefit from refinement, such as the need for explicit links between learning outcomes and workshop activities, and intuitive design of feedback questions, along with feedback collection frequency. We plan to incorporate these additional updates into the revision of the module for the next academic year, and to continue collecting and analysing feedback data for further enhancement.
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