Christos Troussas – författare

This book discusses three important, hot research issues: social networking-based learning, machine learning-based user modeling and sentiment analysis. Although these three technologies have been widely used by researchers around the globe by academic disciplines and by R&D departments in the IT industry, they have not yet been used extensively for the purposes of education. The authors present a novel approach that uses adaptive hypermedia in e-learning models to personalize educational content and learning resources based on the needs and preferences of individual learners. According to reports, in 2018 the vast majority of internet users worldwide are active on social networks, and the global average social network penetration rate as of 2018 is close to half the population. Employing social networking technologies in the field of education allows the latest technological advances to be used to create interactive educational environments where students can learn, collaborate with peers and communicate with tutors while benefiting from a social and pedagogical structure similar to a real class.

The book first discusses in detail the current trend of social networking-based learning. It then provides a novel framework that moves further away from digital learning technologies while incorporating a wide range of recent advances to provide solutions to future challenges. This approach incorporates machine learning to the student-modeling component, which also uses conceptual frameworks and pedagogical theories in order to further promote individualization and adaptivity in e-learning environments. Moreover, it examines error diagnosis, misconceptions, tailored testing and collaboration between students are examined and proposes new approaches for these modules. Sentiment analysis is also incorporated into the general framework, supporting personalized learning by considering the user’s emotional state, and creating a user-friendly learningenvironment tailored to students’ needs. Support for students, in the form of motivation, completes the framework. This book helps researchers in the field of knowledge-based software engineering to build more sophisticated personalized educational software, while retaining a high level of adaptivity and user-friendliness within human–computer interactions. Furthermore, it is a valuable resource for educators and software developers designing and implementing intelligent tutoring systems and adaptive educational hypermedia systems.

This volume constitutes the proceedings of the 16th International Conference on Intelligent Tutoring Systems, ITS 2020, held in Athens, Greece, in June 2020.

The 23 full papers and 31 short papers presented in this volume were carefully reviewed and selected from 85 submissions. They reflect a variety of new techniques, including multimodal affective computing, explainable AI, mixed-compensation multidimensional item response, ensemble deep learning, cohesion network analysis, spiral of silence, conversational agent, semantic web, computer-supported collaborative learning, and social network analysis.

This book summarizes the research findings presented at the 2nd International Conference on Novel & Intelligent Digital Systems (NiDS 2022). NiDS 2022 was implemented virtually due to COVID-19 restrictions, on September 29-30, 2022, under the auspices of the Institute of Intelligent Systems. NiDS lays special emphasis on the novelties of intelligent systems and on the interdisciplinary research which enables, supports, and enhances artificial intelligence (AI) in software development. It promotes high-quality research, creating a forum for the exploration of challenges and new advances in AI, and addresses experts, researchers, and scholars in the fields of artificial and computational intelligence in systems and in computer sciences in general, enabling them to learn more about pertinent, strongly related, and mutually complementary fields. The conference promotes an exchange of ideas, reinforcing and expanding the network of researchers, academics, and market representatives.

This book constitutes the refereed proceedings of the 19th International Conference on Augmented Intelligence and Intelligent Tutoring Systems, ITS 2023, held in Corfu, Greece, during June 2-5, 2023.

The 41 full papers and 19 short papers presented in this book were carefully reviewed and selected from 84 submissions. The papers are divided into the following topical sections: augmented intelligence in tutoring systems; augmented intelligence in healthcare informatics; augmented intelligence in games, serious games and virtual reality; neural networks and data mining; augmented intelligence and metaverse; security, privacy and ethics in augmented intelligence; and applied natural language processing.

This monograph explores the synergy of Artificial Intelligence (AI), Augmented Reality (AR) and cognitive processes to enhance spatial abilities — an integral aspect of cognitive development. The ability to comprehend and manipulate spatial information is not only fundamental to our understanding of the physical world but also plays a pivotal role in numerous academic and professional fields. Recognizing the profound impact of spatial ability on scientific disciplines and educational achievement, this monograph takes on the challenge of enhancing spatial skills among users.

The authors present the design and development of a mobile training system that incorporates AR features to enhance learners’ spatial ability. Involving mental generation, transformation, and rotation of visual images for understanding spatial relationships, spatial ability is closely linked to success in various scientific disciplines and educational pursuits. While spatial visualization skills testsare available, this monograph takes a unique approach by focusing on developing targeted interventions to improve spatial ability. It aims to unlock new avenues for cognitive growth and dive into the untapped potential within the realm of spatial intelligence. 

Beyond its emphasis on spatial ability enhancement, this monograph goes above and beyond traditional approaches by integrating AI techniques into the training system. As such, it aims to provide personalized and adaptive learning experiences for learners. The training system, through intelligent techniques, dynamically analyzes individual learners’ strengths, weaknesses, and progress, tailoring content and challenges to their specific needs. This effort establishes a new frontier in educational technology, offering a groundbreaking solution that not only augments spatial ability development but also showcases the transformative potential of AI in reshaping the learning experience.

The book is a valuable resource for researchers, educators, developers and technology enthusiasts, as it exemplifies the profound impact of AI and AR in shaping the future of online learning experiences.

This book explores the transformative roles of human-computer interaction (HCI) and augmented intelligence (AI) in shaping intelligent systems. HCI focuses on designing interactive systems that enhance human-technology relationships, while AI empowers users with adaptive, data-driven tools that complement decision-making. Together, these fields drive innovation, creating systems that are efficient, intuitive, and inclusive, addressing diverse user needs across various domains.

Central to this work is the paradigm of interactive machine learning (IML), which builds on HCI and AI principles to create adaptive systems capable of evolving in real-time. The book highlights the application of IML in educational software, demonstrating how dynamic, personalized, and responsive learning environments can enhance student engagement and success. It provides detailed case studies and practical examples that showcase how IML aligns educational content, feedback, and interactions with learner behaviors and preferences. Additionally, it includes numerous Python code implementations and actionable design strategies, making these concepts accessible to practitioners and researchers alike.

Key topics include leveraging cognitive and communication styles to shape adaptive systems, integrating learning models to enhance personalization, and addressing ethical considerations such as data privacy and algorithmic fairness. Readers will also discover discussions on creating personalized tutoring systems, collaborative platforms, and immersive environments that redefine educational technology.

This book is a valuable resource for researchers, software developers, educators, instructional designers, and technologists at the intersection of human-computer interaction, augmented intelligence, and educational innovation. With its comprehensive framework and practical insights, it offers the tools to design adaptive, inclusive, and impactful learning systems for the future.