This book, Innovative Trends in Personalized Software Engineering and Information Systems – The Case of Intelligent and Adaptive E-learning Systems, studies the development of personalized and knowledge-based systems with the purpose of developing fully-automated adaptive software, mainly focusing on enhancing digital learning.
The authors cover several integral phases of software engineering and their application in the effective implementation of sophisticated learning technology systems. Systems development and systems evaluation, tailored to adaptive e-learning, are examined in depth. More specifically, intelligent and knowledge-based techniques, such as artificial neural networks, fuzzy logic, genetic algorithms, pattern recognition, learning analytics and data mining, as well as evaluation frameworks adapted to digital learning software are presented.
This publication will be of interest to scientists from various disciplines, including computer science, artificial intelligence, education and psychology, and will help researchers working in computer science and engineering to build intelligent and adaptive learning technology systems by employing personalization techniques while following the basic concepts of software engineering and information systems. It will also serve as a valuable tool for junior and senior scientists, supporting their research activities in the field of personalized and knowledge-based software engineering, and instructors will be able to use the book as a guide to the effective design and development of intelligent systems in education.
Knowledge-based systems refer to computer programs that reason and use a knowledge base to solve complex problems and are an area of high interest by researchers. The attempt of these systems to represent knowledge explicitly allowing the emergence of new knowledge as well as the ever-increasing need of software to become even more individualized and adaptive to users’ needs and preferences can illustrate the motivation of the authors to explore this area. Christos Troussas and Cleo Sgouropoulou analyzed the case of intelligent and adaptive learning technology systems. In the light of new advancements in knowledge-based software engineering, the authors conducted a detailed research and worked towards addressing the resulting obstacles giving potential and robustness to the modern ways of e-learning through the incorporation of artificial intelligence and knowledge-based approaches.
This book explores several complex and sophisticated techniques that are used by e-learning software to build an individualized learning environment and offer a student-centric experience to the users. On top of that, the authors research evaluation models and frameworks that are tailored to assess the quality and effectiveness of knowledge-based systems.
Considering the above, I strongly believe that the authors made admirable effort to further explore this important research field and this monograph is a significant contribution to the pertinent literature. This book can be a valuable tool for junior and senior researchers as well as software developers that seek to implement learning technology systems of improved quality in terms of adaptivity and intelligence.
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