Publications

Katifori, Akrivi; Petousi, Dimitra; Sakelariadis, Pantelis; Ioannidis, Yannis

"It’s Not Fair!”-Exploring Game Master Unfairness in Tabletop Role Playing Games Proceedings Article

In: Proceedings of the 19th International Conference on the Foundations of Digital Games, pp. 1-9, 2024.

(Ed.)

A Conversational AI Assistant for Teaching and Learning Periodical

vol. 2024, no. 136, 2024, visited: 01.01.2024.

Papadimitriou, Katerina; Sapountzaki, Galini; Vasilaki, Kyriaki; Efthimiou, Eleni; Fotinea, Stavroula-Evita; Potamianos, Gerasimos

A large corpus for the recognition of Greek Sign Language gestures Journal Article

In: Computer Vision and Image Understanding, pp. 104212, 2024, ISSN: 1077-3142.

Abstract | Links | BibTeX

@article{PAPADIMITRIOU2024104212,

title = {A large corpus for the recognition of Greek Sign Language gestures},

author = {Katerina Papadimitriou and Galini Sapountzaki and Kyriaki Vasilaki and Eleni Efthimiou and Stavroula-Evita Fotinea and Gerasimos Potamianos},

url = {https://www.sciencedirect.com/science/article/pii/S1077314224002935},

doi = {https://doi.org/10.1016/j.cviu.2024.104212},

issn = {1077-3142},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Computer Vision and Image Understanding},

pages = {104212},

abstract = {Sign language recognition (SLR) from videos constitutes a captivating problem in gesture recognition, requiring the interpretation of hand movements, facial expressions, and body postures. The complexity of sign formation, signing variability among signers, and the technical hurdles of visual detection and tracking render SLR a challenging task. At the same time, the scarcity of large-scale SLR datasets, which are critical for developing robust data-intensive deep-learning SLR models, exacerbates these issues. In this article, we introduce a multi-signer video corpus of Greek Sign Language (GSL), which is the largest GSL database to date, serving as a valuable resource for SLR research. This corpus comprises an extensive RGB+D video collection that conveys rich lexical content in a multi-modal fashion, encompassing three subsets: (i) isolated signs; (ii) continuous signing; and (iii) continuous alphabet fingerspelling of words. Moreover, we introduce a comprehensive experimental setup that paves the way for more accurate and robust SLR solutions. In particular, except for the multi-signer (MS) and signer-independent (SI) settings, we employ a signer-adapted (SA) experimental paradigm, facilitating a comprehensive evaluation of system performance across various scenarios. Further, we provide three baseline SLR systems for isolated signs, continuous signing, and continuous fingerspelling. These systems leverage cutting-edge methods in deep learning and sequence modeling to capture the intricate temporal dynamics inherent in sign gestures. The models are evaluated on the three corpus subsets, setting their state-of-the-art recognition benchmark. The SL-ReDu GSL corpus, including its recommended experimental frameworks, is publicly available at https://sl-redu.e-ce.uth.gr/corpus.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

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Kiourt, Chairi; Evangelidis, Vasileios; Grigoropoulos, Dimitris

Agent-Based Simulation of Crowd Movements in Uneven Terrains: archaeological case studies Proceedings Article

In: Arcaeo-Infromatics: Use and Challenges of AI in Archaeology, Ankara, Turkey, 2024.

BibTeX

Evangelidis, Vasileios; Theodoropoulou, Helena G; Katsouros, Vassilis; Kiourt, Chairi

AI-Enabled Art Education: Unleashing Creative Potential and Exploring Co-Creation Frontiers Proceedings Article

In: Proceedings of the 16th International Conference on Computer Supported Education, pp. 294–301, 2024.

Abstract | Links | BibTeX

Vacalopoulou, Anna; Gardelli, Viktor; Karafyllidis, Theodoros; Liwicki, Foteini; Mokayed, Hamam; Papaevripidou, Marios; Paraskevopoulos, Georgios; Stamouli, Spyridoula; Katsamanis, Athanasios; Katsouros, Vassilis

AI4EDU: An innovative conversational AI assistant for teaching and learning Proceedings Article

In: INTED2024 Proceedings, pp. 7119-7127, IATED, 2024, ISBN: 978-84-09-59215-9.

Abstract | Links | BibTeX

@inproceedings{nokey,

title = {AI4EDU: An innovative conversational AI assistant for teaching and learning},

author = {Anna Vacalopoulou and Viktor Gardelli and Theodoros Karafyllidis and Foteini Liwicki and Hamam Mokayed and Marios Papaevripidou and Georgios Paraskevopoulos and Spyridoula Stamouli and Athanasios Katsamanis and Vassilis Katsouros},

url = {https://library.iated.org/view/VACALOPOULOU2024AI4},

doi = {10.21125/inted.2024.1877},

isbn = {978-84-09-59215-9},

year  = {2024},

date = {2024-03-12},

urldate = {2024-03-12},

booktitle = {INTED2024 Proceedings},

pages = {7119-7127},

publisher = {IATED},

abstract = {Artificial intelligence (AI) is transforming education by introducing innovative tools and approaches to enhance teaching and learning. Chatbots like Dawebot and TA-bot serve as intelligent student assistants, providing interactive quizzes, immediate feedback, and personalized support. AI-based systems like Rexy and Kwame offer personalized learning experiences, adapting to individual student needs and enhancing self-regulated learning. Chatbots and AI-based systems can address educational challenges in resource-constrained settings, providing scalable and cost-effective learning solutions. More specifically, Generative AI technologies, like the Large Language Model-based ChatGPT, with their advanced language capabilities, promise enriched and interactive real-time learning through natural conversation. These advancements demonstrate the potential of AI to revolutionize education, making it more personalized, accessible, and effective for all learners. Some typical ways in which this potential is demonstrated is the ability to quickly answer questions, provide explanations according to preset criteria, and suggest additional teaching and learning resources.

The Conversational AI assistant for teaching and learning (AI4EDU) project aims to improve school education by exploring and implementing new approaches, technologies, and applications of AI in Education. It seeks to create new, innovative, adaptable, personalized, engaging, and effective ways of teaching and learning, in view of the growing challenges brought on by the digital transformation of education. This paper describes the design and development of a student-facing AI platform to enhance, personalize, and facilitate learning, empower teachers, and support teaching and assessment objectives, increase knowledge and understanding of AI among students and teachers to understand how AI applications work, their potential, and their limitations. A key feature of this endeavor is the incorporation of Large Language Models (LLMs) like ChatGPT. Incorporating LLMs into educational environments poses challenges like restricted personalization, the risk of misinformation, and excessive dependence on technology. In order to combine LLMs with textbooks and other educational resources currently used in schools, AI4EDU tackles these issues by employing Retrieval Augmented Generation (RAG) and a conversational AI model for interacting with students and teachers through natural language understanding. Key aspects include ethical considerations, content reliability, and a balance between AI assistance and human interaction. The project seeks to transform education by delivering personalized, adaptive, and captivating learning experiences for both students and teachers.

To combine all these into a flexible, personalized, engaging, and effective educational platform, AI4EDU develops two different tools that accommodate the needs of both students and teachers. These tools are Study Buddy, a conversational AI assistant to help students with a wide range of learning activities, and Teacher Mate, a dashboard and chatbot that also incorporates AI-powered technologies and assists teachers in organizing the teaching process, preparing materials and tests, evaluating students, tracking their progress, and more. Both tools incorporate educational resources from four EU countries (Cyprus, Greece, Ireland, Sweden) and are offered in three European languages (Greek, Irish, Swedish).},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

Close

Artificial intelligence (AI) is transforming education by introducing innovative tools and approaches to enhance teaching and learning. Chatbots like Dawebot and TA-bot serve as intelligent student assistants, providing interactive quizzes, immediate feedback, and personalized support. AI-based systems like Rexy and Kwame offer personalized learning experiences, adapting to individual student needs and enhancing self-regulated learning. Chatbots and AI-based systems can address educational challenges in resource-constrained settings, providing scalable and cost-effective learning solutions. More specifically, Generative AI technologies, like the Large Language Model-based ChatGPT, with their advanced language capabilities, promise enriched and interactive real-time learning through natural conversation. These advancements demonstrate the potential of AI to revolutionize education, making it more personalized, accessible, and effective for all learners. Some typical ways in which this potential is demonstrated is the ability to quickly answer questions, provide explanations according to preset criteria, and suggest additional teaching and learning resources.
The Conversational AI assistant for teaching and learning (AI4EDU) project aims to improve school education by exploring and implementing new approaches, technologies, and applications of AI in Education. It seeks to create new, innovative, adaptable, personalized, engaging, and effective ways of teaching and learning, in view of the growing challenges brought on by the digital transformation of education. This paper describes the design and development of a student-facing AI platform to enhance, personalize, and facilitate learning, empower teachers, and support teaching and assessment objectives, increase knowledge and understanding of AI among students and teachers to understand how AI applications work, their potential, and their limitations. A key feature of this endeavor is the incorporation of Large Language Models (LLMs) like ChatGPT. Incorporating LLMs into educational environments poses challenges like restricted personalization, the risk of misinformation, and excessive dependence on technology. In order to combine LLMs with textbooks and other educational resources currently used in schools, AI4EDU tackles these issues by employing Retrieval Augmented Generation (RAG) and a conversational AI model for interacting with students and teachers through natural language understanding. Key aspects include ethical considerations, content reliability, and a balance between AI assistance and human interaction. The project seeks to transform education by delivering personalized, adaptive, and captivating learning experiences for both students and teachers.
To combine all these into a flexible, personalized, engaging, and effective educational platform, AI4EDU develops two different tools that accommodate the needs of both students and teachers. These tools are Study Buddy, a conversational AI assistant to help students with a wide range of learning activities, and Teacher Mate, a dashboard and chatbot that also incorporates AI-powered technologies and assists teachers in organizing the teaching process, preparing materials and tests, evaluating students, tracking their progress, and more. Both tools incorporate educational resources from four EU countries (Cyprus, Greece, Ireland, Sweden) and are offered in three European languages (Greek, Irish, Swedish).

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Kotsopoulos, Konstantinos I.; Chourdaki, Pelagia; Tsolis, Dimitrios; Antoniadis, Rallis; Pavlidis, George; Assimakopoulos, Nikitas

An authoring platform for developing smart apps which elevate cultural heritage experiences: A system dynamics approach in gamification Journal Article

In: Journal of Ambient Intelligence and Humanized Computing, vol. 15, iss. 2, 2024.