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ChatGPT-based Recommendations for Personalized Content Creation and Instructional Design with a Tailored Prompt Generator 2

ChatGPT-based Recommendations for Personalized Content Creat...

引用

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

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

ISBN: (纸本)9798350354799

Recent advancements in Artificial Intelligence (AI) have significantly influenced educational innovations, making learning environments more sophisticated with personalized learning, tailored feedback, and learning analytics. Among these advancements, Generative AI, namely ChatGPT, has emerged as a powerful tool in education. ChatGPT's ability to generate human-like content in real-time can assist educators with course design and educational material creation, allowing for enhanced instructional strategies without starting from scratch. Moreover, integrating ChatGPT into the recommendation process offers superior understanding of user needs and delivery of context-aware recommendations. In view of the above, this paper explores the integration of ChatGPT with a tailored prompt generator within an intelligent authoring system to offer effective recommendations for personalized content creation and instructional design. The system was evaluated and compared to its conversional version where instructors manually use ChatGPT. The findings indicate significant improvements in system usability, content quality, personalization, and time and effort savings, demonstrating the effectiveness of the proposed approach. © 2024 IEEE.

关键词： Contrastive Learning

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

Affective Computing in Intelligent Tutoring Systems: Explori...

引用

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

Personalized Learning via Gamified Virtual Environments: Exp...

引用

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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A Reduced overhead Accumulator-based BIST scheme for Two-pattern generation 9

A Reduced overhead Accumulator-based BIST scheme for Two-pat...

引用

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

作者： Fotopoulos, E. Fatouros, S. Milidonis, A. Voyiatzis, I. University of West Attica Department of Informatics and Computer Engineering Athens Greece

ISBN: (纸本)9798350342482

Two-pattern tests target the detection of common failure mechanisms in CMOS VLSI circuits, modelled as stuck-open or delay faults. In this paper, a Reduced-overhead Accumulator-Based BIST scheme for Two-pattern generation (RABIT) is presented, that generates an exhaustive n-bit two-pattern test. RABIT is implemented in hardware utilizing an accumulator whose inputs are driven by a binary counter. An important advantage of the presented scheme is that it can be implemented by augmenting existing data path components, rather than building a new pattern generation structure. Furthermore, with the proposed scheme, the requirement for additional (i.e. control and/or accompanying) circuitry is eliminated. Comparisons with previously proposed schemes reveal that the proposed here scheme presents lower hardware overhead for the implementation of the BIST structure. © 2024 IEEE.

关键词： Built-in self test

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Technology is not Enough: Educators as Catalysts for Sparking Student Interest and Engagement in Higher Education 4th

Technology is not Enough: Educators as Catalysts for Sparkin...

引用

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

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

ISBN: (纸本)9783031733437

With technology fundamentally changing the way students learn, traditional lectures often fail to capture student interest and prepare them for rapidly evolving demands of the job market. This paper highlights the need for active learning approaches that spark interest, motivation, and engagement. A significant challenge to achieving this goal is academic boredom, a negative emotional state associated with passive learning environments. Technology can offer a powerful toolset for transforming the traditional learning environment. However, effective learning relies not only on the strategic integration of technology, but also on the selection of the appropriate teaching techniques that cultivate a stimulating and interactive learning environment. To address this challenge, this study aims to explore key factors influencing university student engagement. This includes exploring academic boredom rates, the underlying factors leading students to lose interest, the impact of digital technology in university courses, and student preferences for teaching practices. The findings highlighted a gap between student preferences for engaging and meaningful learning experiences, and current teaching practices that often rely on traditional lectures and outdated content. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Contrastive 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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Automatic sign language sentence recognition in the context of guided museum tours 1

Automatic sign language sentence recognition in the context ...

引用

1st International Workshop on Accessibility and Multimodal Interaction Design Approaches in Museums for People with Impairments, AMID 2023

作者： Pikoulis, Erion-Vasilis Bifis, Aristeidis Arvanitis, Nikolaos Kosmopoulos, Dimitrios Computer Engineering and Informatics Department University of Patras Rio26504 Greece

Sign Language (SL) translation remains an extremely challenging task despite recent breakthrough progress in the constituent fields of computer Vision and Machine Learning, especially when tackled under a general unconstrained setup. This is mainly due to a combination of the difficulty of the task itself on the one hand, and the absence of large-scale labeled datasets that would enable using end-toend Deep Learning based solutions, on the other. In such cases, the ability to incorporate prior information can yield a significant improvement on the translation results, by greatly restricting the search space of the potential solutions. In this work we treat the SL translation problem in the limited confinement of an interactive, guided museum tour for deaf and hard-of-hearing visitors. Prior domain knowledge enables us to compile a list of targeted questions per museum exhibit and use these lists to create an SL training dataset for the solution of the problem at hand. In our case, SL question recognition is treated as a sentence retrieval problem, whereby the goal is to predict visitor’s question that best matches the available pool of possible inquiries. Our preliminary evaluation using both tailored deep architectures and traditional non-deep solutions has led to promising results for the recognition task at hand. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Museums

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