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检索条件"机构=Informatics and Computer Engineering"

共 20353 条记录，以下是31-40 订阅

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Evaluating ChatGPT-driven Automated Test Generation for Personalized Programming Education 2

Evaluating ChatGPT-driven Automated Test Generation for Pers...

引用

2nd International Conference on Foundation and Large Language Models, FLLM 2024

作者： Troussas, Christos Papakostas, Christos Krouska, Akrivi Mylonas, Phivos Sgouropoulou, Cleo University of West Attica Department of Informatics and Computer Engineering Egaleo Greece

ISBN: (纸本)9798350354799

Large Language Models (LLMs), such as ChatGPT, hold immense potential to irrevocably influence the dimension of educational technology by providing empowerment for personalized learning experiences. This paper covers the integration of ChatGPT into existing eLearning platforms toward supporting Java programming education. Using artificial intelligence-based capabilities of ChatGPT in natural language processing, our software enables instructors to generate individual module assessments tailored to a student's profile with unprecedented ease. Evaluation of the effectiveness and efficiency of the system was performed by a comprehensive review of the system, obtaining feedback from instructors and students, and analyzing test performance metrics. The evaluation showed that most teachers found the system very user friendly, with significant savings in time for test creation. Satisfaction related to personalized tests designed by ChatGPT was also adequate, and the average scores achieved on test cases set by ChatGPT were relatively high compared to those manually curated. Results underline the potential of ChatGPT-driven automated test generation for enhancing personalized programming education on eLearning platforms, making available tailored assessment, by consideration of individual needs of students, and increased learning outcomes and efficiency. © 2024 IEEE.

关键词： Java programming language

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The Implementation of Natural Language Processing on Chatbot as Academic Information System: A Case Study of IC2IE 2024 7

The Implementation of Natural Language Processing on Chatbot...

引用

7th International Conference of computer and informatics engineering, IC2IE 2024

作者： Purba, Christian Nataniel Yosua Parulian, Pratama Varian Andika Iswara, Ratna Widya Suhandana, Ariawan Andi Sari, Risna Politeknik Negeri Jakarta Department of Computer and Informatics Engineering Depok Indonesia

ISBN: (纸本)9798331505530

The implementation of Natural Language Processing (NLP) in chatbots has significantly enhanced the efficiency and user experience of academic information systems. This paper presents a case study of the International Conference on Computing, Communication, and Information engineering (IC2IE) 2024, exploring how NLP-driven chatbot can serve as a robust academic information system. By employing advanced NLP techniques, the chatbot effectively understands and processes user inquiries, providing accurate and timely information about the conference schedules, speakers, submission guidelines, etc. Accuracy testing demonstrated an overall performance of 84.533%, with perfect accuracy in the 0.75-1.0 similarity range and 96.15% accuracy in the 0.5-0.74 range. The findings suggest that integrating NLP in academic information systems can streamline operations and enhance communication within academic events. © 2024 IEEE.

关键词： Information use

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Personalized Path Planning Estimation of Georeferenced Urban Scene Considering Criminality Map: The Case of Attica 4th

Personalized Path Planning Estimation of Georeferenced Urban...

引用

4th International Conference on Novel and Intelligent Digital Systems, NiDS 2024

作者： Yiakoumettis, Christos Karanikolas, Nikitas Department of Informatics and Computer Engineering University of West Attica Aigaleo Greece

ISBN: (纸本)9783031733437

This paper introduces an advanced georeferenced path planning methodology that enhances urban navigation by incorporating crime statistics to ensure safety and adherence to user preferences. Leveraging a combination of Geographic Information Systems (GIS) and 3D urban modeling, our approach proposes a unique platform that personalizes route planning within the urban landscape of Attica, Greece. Our approach is taking into consideration user’s preferences considering qualitative and quantitative features and a Criminality Map. Initially the user profile is estimated based on a pairwise comparison approach of inductive-based learning methodology using Analytical Hierarchy Process (AHP). The proposed platform provides a personalized path planning estimation for urban areas by aligning geographic data with both user-specific preferences and safety considerations. The efficacy of our approach is demonstrated through a detailed case study of Attica (Greece), where over 700 georeferenced models are analyzed for path planning alongside with criminal reports of Police for the year 2022. This research highlights the potential of combining safety metrics with personalization in path planning, offering significant implications for the development of smart navigation systems in urban environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Crime

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Utilizing Fuzzy Weights for Enhanced User Experience in Virtual Museums 19

Utilizing Fuzzy Weights for Enhanced User Experience in Virt...

引用

19th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2024

作者： Papakostas, Christos Troussas, Christos Krouska, Akrivi Mylonas, Phivos Sgouropoulou, Cleo University of West Attica Department of Informatics and Computer Engineering Egaleo Greece

ISBN: (纸本)9798331504502

In the digital age, the existence and experience of art, history, and culture change worldwide, and the rise of virtual museums ensures that the boundaries are eliminated and interactions with the population diversities are improved for education and culture preservation. This paper analyzes fuzzy weights for personalizing user experiences in virtual museums. Fuzzy weights propose recommendations and subtle content adaptation from user preferences and behaviors to enhance further engagement in the content exposed. Based on a case study of VirtuMuse, we have developed a model to calculate fuzzy weights from user interactions, which are integrated into content management and recommendation systems. User engagement was high, personalization effective and the users were satisfied based on forty university students' evaluation. In conclusion, these findings underscore its effectiveness in matching contents according to individual users' preferences, thereby enhancing their overall experience. Such research highlights the potential for virtual museums to act as preservers of digital cultural heritage and providers of personalized immersive educational experiences. © 2024 IEEE.

关键词： Virtual environments

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Exploring Teachers’ Attitudes and Self-efficacy Towards AI Learning in Science Instruction 4th

Exploring Teachers’ Attitudes and Self-efficacy Towards AI ...

引用

4th International Conference on Novel and Intelligent Digital Systems, NiDS 2024

作者： Stryftoy, Stavroula Krouska, Akrivi Troussas, Christos Mylonas, Phivos Sgouropoulou, Cleo Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (纸本)9783031733437

As teachers strive to adapt to the technologically evolving landscape of education, understanding the impact of Artificial Intelligence (AI) on pedagogical practices becomes increasingly crucial. This study explores the contribution of Artificial Intelligent Learning (AI Learning) model to teachers’ attitudes and self-efficacy in teaching science. As such, an educational intervention based on AI Learning was conducted with a sample of 13 primary school teachers. The teachers were asked to answer a Dimensions of Attitude toward Science (DAS) questionnaire designed for this study, before and after the intervention. Before the intervention, a significant percentage of teachers expressed disagreement about the importance of physics in primary education (53.8%) and had a negative attitude towards its introduction (46.2%). However, after the intervention, there was a substantial shift towards positive attitudes: 38.5% acknowledged the importance of physics and 38.5% expressed a positive intention towards its introduction. The intervention also positively impacted teachers’ anxiety levels, enjoyment of teaching physics, and perceptions of their knowledge adequacy to support students. Additionally, there was a noticeable positive change in teachers’ perceptions of their preparedness to provide help to students. The improvement of DAS score (mean 68.15 before intervention/mean 89.15 after intervention) indicates that the intervention led to a more positive attitude among teachers regarding the use of AI learning in teaching science. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Contrastive Learning

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Analysing the Effectiveness of a Social Digital Repository for Learning and Teaching: A Fuzzy Comprehensive Evaluation 19

Analysing the Effectiveness of a Social Digital Repository f...

引用

19th International Conference on Evaluation of Novel Approaches to Software engineering, ENASE 2024

作者： Krouska, Akrivi Troussas, Christos Mylonas, Phivos Sgouropoulou, Cleo Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (纸本)9789897586965

Since the beginning of the 21st century, Open Education has emerged as an important field in education. Open Educational Resources (OERs) are closely related to it, which are hosted in Digital Repositories. OERs, despite their global recognition and their growing number, are not yet established widely. Teachers face many challenges when they want to use them, including the lack of pedagogical knowledge about their value, the way to use them, produce them and integrate them into teaching process. The purpose of this research is to strengthen the movement of OERs and to realise their full potential. To this end, a social digital repository was developed, for promoting OERs in primary education. This platform aims to create an open and interactive community of teachers, where through interaction, communication and collaboration, the teachers will be educated on OERs. The effectiveness of this digital repository is assessed using the fuzzy comprehensive evaluation model, in order to handle the subjective and imprecise information and better interpret the results of the survey. The results are very encouraging regarding the adoption of this technology. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： E-learning

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Redefining the Concept of Literacy: a DigCompEdu extension for Critical Engagement with AI tools 9

Redefining the Concept of Literacy: a DigCompEdu extension f...

引用

9th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2024

作者： Georgopoulou, Maria Sofia Krouska, Akrivi Troussas, Christos Sgouropoulou, Cleo University of West Attica Department of Informatics and Computer Engineering Aigaleo Greece

ISBN: (纸本)9798350342482

Artificial Intelligence (AI) is rapidly transforming our world, and education is no exception. The growing popularity and use of AI systems calls for a new understanding of what it means to be literate in the modern world. Thus, it is crucial for individuals to develop AI-driven critical thinking skills to effectively interact with these technologies. However, existing research focuses mainly on the "how"of AI integration, with limited exploration of the "why"and "how"of fostering critical engagement with AI tools. In this article, we propose an extension to DigCompEdu that aligns with the UNESCO pillars of education. This extension highlights five key elements that challenge critical thinking capabilities in relation to AI: "know-what,""know-who,""know-where,""know-how,"and "know-why". By combining critical thinking skills with AI functionalities, educators can empower students to become responsible and informed digital citizens in the era of generative AI. © 2024 IEEE.

关键词： Artificial intelligence

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Development of a Machine Learning Model for Production Facility Predictive Diagnostics

Development of a Machine Learning Model for Production Facil...

引用

2024 International Conference on Industrial engineering, Applications and Manufacturing, ICIEAM 2024

作者： Vorsin, Daniil Toichkin, Nikolay Murmansk Arctic University Department Of Informatics And Computer Engineering Apatity Russia

ISBN: (纸本)9798350395013

The usage of artificial intelligence in problems related to industry makes it possible to develop optimization, predictive digital models for their operation in real time. The developed model can conduct predictive diagnostics of equipment's, or can be employed as a system that offers recommendations to the user for subsequent optimization of the technological process Considering the growing complexity of technical equipment and their control systems, it becomes highly imperative to develop an intelligent diagnostic structure for safety management in multi-level industrial systems. The article's relevance stems from the implementation of machine learning algorithms in the industry, enabling the analysis of a considerable amount of sensor-derived data. As a result, this facilitates predictive equipment diagnostics, anomaly prediction, intelligent safety management, uninterrupted operations, and reduced maintenance downtime. © 2024 IEEE.

关键词： Recurrent neural networks

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Personalized Learning via Gamified Virtual Environments: Exploring Insights and Impact 19

Personalized Learning via Gamified Virtual Environments: Exp...

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19th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2024

作者： Strousopoulos, Panagiotis Troussas, Christos University of West Attica Department of Informatics and Computer Engineering Egaleo Greece

ISBN: (纸本)9798331504502

This paper explores the transformative potential of combining Artificial Intelligence (AI) with gamified learning environments (GLEs) to enhance personalized learning experiences. Gamified learning environments have emerged as relevant practical tools that provide dynamic learning pathways, helping learners engage better through motivation, interactivity, and entertainment. Integrating GLEs with AI amplifies the element of personalization by analyzing student progress, strengths, and weaknesses to tailor accordingly. AIdriven adaptive learning systems create a flexible and supportive learning environment in which feedback, recommending resources, and adapting levels of difficulty are tuned to the pace of the learner. This stretches even to virtual environments (VEs) that enable learning through immersive and interactive experiences about abstract concepts in learning. Gamification is changing learning with more sustained motivation. The paper, therefore, discusses the possibilities of using those technologies in reshaping education and points to AI and gamification as cutting-edge tools that would help shape adaptive, engaging, personalized learning environments. Finally, it calls on all stakeholders, the educators, the developers, and the theorists, to empower those tools toward more inclusivity and innovation in education so that, in the future, learning experiences turn out functional and enjoyable. The goals should be underscored with the true potential of AI and gamification in democratizing education and improving learning methodologies until innovation is continuous. © 2024 IEEE.

关键词： Federated learning

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Affective Computing in Intelligent Tutoring Systems: Exploring Insights and Innovations 9

Affective Computing in Intelligent Tutoring Systems: Explori...

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9th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2024

作者： Tasoulas, Theofanis Troussas, Christos Mylonas, Phivos Sgouropoulou, Cleo University of West Attica Department of Informatics and Computer Engineering Egaleo Greece

ISBN: (纸本)9798350342482

Integrating intelligent tutoring systems (ITS) into education has significantly enriched personalized learning experiences for students and educators alike. However, these systems often neglect the critical role of emotions in the learning process. By integrating affective computing, which empowers computers to recognize and respond to emotions, ITS can foster more engaging and impactful learning environments. This paper explores the utilization of affective computing techniques, such as facial expression analysis and voice modulation, to enhance ITS functionality. Case studies and existing systems have been scrutinized to comprehend design decisions, outcomes, and guidelines for effective integration, thereby enhancing learning outcomes and user engagement. Furthermore, this study underscores the necessity of considering emotional aspects in the development and deployment of educational technology to optimize its influence on student learning and well-being. A major conclusion of this research is that integration of affective computing into ITS empowers educators to customize learning experiences to students' emotional states, thereby enhancing educational effectiveness. To achieve this, it is crucial for such systems to make informed design decisions and adhere to established guidelines. These design decisions may involve selecting appropriate emotion recognition algorithms and integrating them seamlessly into the ITS interface, while guidelines can offer practical insights into effectively implementing affective computing techniques in ITS, such as ensuring data privacy and security measures are in place and providing adequate training for educators on interpreting emotional data. © 2024 IEEE.

关键词： Contrastive Learning

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