Deep Learning In Adaptive Learning Educational Behavior And Strategy

The Smart Innovation, Systems and Technologies book series encompasses the topics of knowledge, intelligence, innovation and sustainability. The aim of the series is to make available a platform for the publication of books on all aspects of single and multi-disciplinary research on these themes in order to make the latest results available in a readily-accessible form. This book is devoted to the “Intelligent and Adaptive Educational-Learning Systems”. It privileges works that highlight key achievements and outline trends to inspire future research. After a rigorous revision process twenty manuscripts were accepted and organized into four parts: Modeling, Content, Virtuality and Applications. This volume is of interest to researchers, practitioners, professors and postgraduate students aimed to update their knowledge and find out targets for future work in the field of artificial intelligence on education.

In recent years, the integration of Artificial Intelligence (AI) into educational systems has marked a transformative shift in how learning is delivered and experienced. AI technologies, ranging from intelligent tutoring systems to adaptive learning platforms, offer unprecedented opportunities for personalized and efficient education. However, this rapid evolution also brings new challenges, particularly concerning students' behavioral and emotional well-being. The purpose of this book is to explore the complex interplay between AI and maladaptive behaviors in educational settings. While AI has the potential to revolutionize education by tailoring learning experiences to individual needs, it also has the capacity to influence student behavior in ways that may be detrimental to their overall development. As educators, policymakers, and researchers, it is crucial to understand and address these potential impacts to create a more supportive and balanced learning environment.

Just like any new technology, what perplexes many is the question of how to apply Deep Learning in a business context. Technology that is disruptive does not automatically imply that the development of valuable use cases are apparent. For years, many people could not figure out how to monetize the World Wide Web. We are in that same situation with Deep Learning AI. The developments are mind-boggling but the monetization is far from being obvious.Deep Learning Artificial Intelligence involves the interplay of Computer Science, Physics, Biology, Linguistics and Psychology. In addition to that, it is technology that can be extremely disruptive. Furthermore, the ramifications to society and even our own humanity can be immense. There are few subjects that are as captivating and as consequential as this. Surprisingly, there is very little that is written about this new technology in a more comprehensive and cohesive way. This book is an opinionated take on the developments of Deep Learning AI.

This book contains the latest researches on advanced intelligent systems applied in the field of education presented during the second edition of the International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD’2019) held on July 08–11, 2019, in Marrakech, Morocco. The book proposes new approaches and innovative strategies for the manipulation of data and big data collected from the educational environment, exploiting the analysis tools, algorithms of artificial intelligence, and machine learning techniques, in order to extract results, which allow improving the performance and effectiveness of the education field, which is a strategic lever for sustainable development. The book deals with concepts, strategies, and approaches developed on various current axes of scientific research in the field of education, such as smart e-learning, smart education (smart classroom, smart assessment and smart teaching and learning technologies), massive open online courses (MOOC), courseware design, and development for smart learning, cloud learning, and mobile learning. The book is intended for all actors in the educational sector, namely students, professors, academic researchers, and stakeholders. It constitutes a large-scale forum for the exchange of ideas, approaches, and innovative techniques between these actors on the development and innovation of the field of education with the revolution 4.0. The authors of each chapter report the state of the art of the various topics addressed and present results of their own research, laboratory experiments, and successful applications. The purpose of this session is to share the idea of advanced intelligent systems with appropriate tools and techniques for modeling, management, and decision support in the field of education.

The shift to virtual education has presented numerous challenges, including maintaining student focus and participation. Traditional methods of instruction often need to catch up in capturing the attention of digital learners, leading to disengagement and reduced learning outcomes. However, there is a solution at hand. AI Algorithms and ChatGPT for Student Engagement in Online Learning offers a comprehensive approach to leveraging artificial intelligence (AI) algorithms and ChatGPT to enhance student engagement in digital classrooms. This book addresses the pressing need for innovative strategies to keep students actively involved in their online learning journey. By harnessing the power of AI algorithms, educators can personalize learning paths to suit individual student needs, ensuring that content is relevant and engaging. Additionally, ChatGPT serves as a virtual assistant, providing students with instant feedback and support, fostering a sense of connection to the learning process.

Data Analytics and Adaptive Learning offers new insights into the use of emerging data analysis and adaptive techniques in multiple learning settings. In recent years, both analytics and adaptive learning have helped educators become more responsive to learners in virtual, blended, and personalized environments. This set of rich, illuminating, international studies spans quantitative, qualitative, and mixed-methods research in higher education, K–12, and adult/continuing education contexts. By exploring the issues of definition and pedagogical practice that permeate teaching and learning and concluding with recommendations for the future research and practice necessary to support educators at all levels, this book will prepare researchers, developers, and graduate students of instructional technology to produce evidence for the benefits and challenges of data-driven learning.

As explored in this open access book, higher education in STEM fields is influenced by many factors, including education research, government and school policies, financial considerations, technology limitations, and acceptance of innovations by faculty and students. In 2018, Drs. Ryoo and Winkelmann explored the opportunities, challenges, and future research initiatives of innovative learning environments (ILEs) in higher education STEM disciplines in their pioneering project: eXploring the Future of Innovative Learning Environments (X-FILEs). Workshop participants evaluated four main ILE categories: personalized and adaptive learning, multimodal learning formats, cross/extended reality (XR), and artificial intelligence (AI) and machine learning (ML). This open access book gathers the perspectives expressed during the X-FILEs workshop and its follow-up activities. It is designed to help inform education policy makers, researchers, developers, and practitioners about the adoption and implementation of ILEs in higher education.

This latest volume in the Deep Learning Manual series presents an architecture and roadmap for implementing, on a nationwide basis, a deep learning-based education platform. The proposed platform combines adaptive learning software and behavioral neuroscience in a unique and powerful way. The author's motivation for this approach comes from decades of observing classroom behaviors that limit rather than advance our individual and collective capacity for self-discovery. Many of these behaviors reinforce longstanding inequalities. Education need not be difficult in our current age, regardless of a person's socio-economic background. Much of the basis for students' struggles, especially in college-level mathematics, is the over-emphasis on rote memorization at the expense of understanding the topics in ways that make sense to the individual student. For this reason, sense-making tools and practices form a key aspect of the proposed platform. Prueitt's approach is based on the premise of having a "sense of location" as a student navigates a "knowledge space" of topics, moving from those that are "comfortable" to those that are "uncomfortable." This book paints both a vision and a roadmap to the future, where first principles of science and mathematics are communicated through a "learning medium" that builds upon traditional books and research publications. The goal is to create a national and even global network of knowledge media that improves an average citizen's capacity for lifelong learning. Design Principles is richly illustrated with anonymized images of real handwritten narratives from freshman college mathematics students who have gone from struggling with and disdain toward the subject to feeling knowledgeable and empowered to apply the learned principles in future classes, work, and life.