Personalized Learning Through Adaptive Systems And Intelligent Tutoring
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Personalized Learning Through Adaptive Systems and Intelligent Tutoring
Artificial intelligence (AI) transforms e-learning through tools like personalized online learning experiences, adaptive learning systems, and intelligent tutors. AI-driven technologies adjust the content based on the individual learner’s needs, enhancing engagement and learning outcomes. As these intelligent tools utilize data to gain insight into the user and user needs, it is imperative that the data be kept private. Further research is important to address issues concerning algorithmic bias impacting equality. Personalized Learning Through Adaptive Systems and Intelligent Tutoring delves into natural language processing for content generation and student feedback, as well as AI’s role in enhancing learner engagement and motivation through gamification and virtual environments. It addresses future trends and innovations in AI for education, featuring case studies and contributions from researchers, educators, and platform developers. Covering topics such as recommendation systems, educational disparities, and metacognitive awareness, this book is an excellent resource for teachers, e-learning platform developers, computer scientists, professionals, researchers, scholars, academicians, and more.
Building Intelligent Interactive Tutors
Computers have transformed every facet of our culture, most dramatically communication, transportation, finance, science, and the economy. Yet their impact has not been generally felt in education due to lack of hardware, teacher training, and sophisticated software. Another reason is that current instructional software is neither truly responsive to student needs nor flexible enough to emulate teaching. The more instructional software can reason about its own teaching process, know what it is teaching, and which method to use for teaching, the greater is its impact on education. Building Intelligent Interactive Tutors discusses educational systems that assess a student's knowledge and are adaptive to a student's learning needs. Dr. Woolf taps into 20 years of research on intelligent tutors to bring designers and developers a broad range of issues and methods that produce the best intelligent learning environments possible, whether for classroom or life-long learning. The book describes multidisciplinary approaches to using computers for teaching, reports on research, development, and real-world experiences, and discusses intelligent tutors, web-based learning systems, adaptive learning systems, intelligent agents and intelligent multimedia. *Combines both theory and practice to offer most in-depth and up-to-date treatment of intelligent tutoring systems available *Presents powerful drivers of virtual teaching systems, including cognitive science, artificial intelligence, and the Internet *Features algorithmic material that enables programmers and researchers to design building components and intelligent systems
E-Learning Systems
Author: Aleksandra Klašnja-Milićević
language: en
Publisher: Springer
Release Date: 2016-07-19
This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques.