A Machine Learning Artificial Intelligence Approach To Institutional Effectiveness In Higher Education

This book presents a practical, effective, and systematic approach to the measurement, assessment, and sensemaking of institutional performance. Included are strategies to measure and assess the performance of Curriculum, Learning, Instruction, Support Services, and Program Feasibility as well as a meaningful Environmental Scanning method.

The global adoption of technology in education is transforming the way we teach and learn. Artificial Intelligence is one of the disruptive techniques to customize the experience of different learning groups, teachers, and tutors. This book offers knowledge in intelligent teaching/learning systems, and advances in e-learning and assessment systems. The book highlights the broad field of artificial intelligence applications in education, regarding any type of artificial intelligence that is correlated with education. It discusses learning methodologies, intelligent tutoring systems, intelligent student guidance and assessments, intelligent education chatbots, and artificial tutors and presents the practicality and applicability implications of AI in education. The book offers new and current research along with case studies showing the latest techniques and educational activities. The book will find interest with academicians which includes teachers, students of various disciplines, higher education policymakers who believe in transforming the education industry, and research scholars who are pursuing their Ph.D. or Post Doc. in the field of Education Technology, Education, and Learning, etc. and those working in the area of Education Technology and Artificial Intelligence such industry professionals in education management and e-learning companies.

The ongoing struggle to increase literacy within our population is one of the defining goals of education. Educational environments continue to incorporate more and more technology into their cache of necessary tools as the lives of their students depend on these devices at a growing rate. Artificial intelligence (AI) and literacy education are bound to face a convergence that will be a transformative force. AI Approaches to Literacy in Higher Education delves into the synergies between advanced technology and the cultivation of literacy skills, illuminating innovative methodologies and applications that redefine educational paradigms. This book is a comprehensive analysis of AI's potential to elevate literacy among higher education students. The book strategically integrates research studies, case analyses, and theoretical perspectives to construct a nuanced understanding of AI's role in shaping literacy outcomes. This work uncovers the intricate interplay between technology and academic literacy by utilizing a tapestry of AI-driven tools, strategies, and techniques. Educators, researchers, instructional designers, and higher education professionals will find this book invaluable.

Within higher education, there are enormous untapped opportunities for product/services companies, administrators, educators, start-ups. and technology professionals to begin embracing artificial intelligence (AI) across the student ecosystem and infuse innovation into traditional academic processes by leveraging disruptive technologies. This type of human-machine interface presents the immediate potential to change the way we learn, memorize, access, and create information. These solutions present new openings for education for all while fostering lifelong learning in a strengthened model that can preserve the integrity of core values and the purpose of higher education. Impact of AI Technologies on Teaching, Learning, and Research in Higher Education explores the phenomena of the emergence of the use of AI in teaching and learning in higher education, including examining the positive and negative aspects of AI. Recent technological advancements and the increasing speed of adopting new technologies in higher education are discussed in order to predict the future nature of higher education in a world where AI is part of the fabric of universities. The book also investigates educational implications of emerging technologies on the way students learn and how institutions teach and evolve. Finally, challenges for the adoption of these technologies for teaching, learning, student support, and administration are addressed. Highlighting such tools as machine learning, natural language processing, and self-learning systems, this scholarly book is of interest to university administrators, educational software developers, instructional designers, policymakers, government officials, academicians, researchers, and students, as well as international agencies, organizations, and professionals interested in implementing AI in higher education.

This book presents a comprehensive, systematic approach to the development of curricula in higher education in which each component is configured to optimize learning. The approach is based in an analysis of the psychophysics of the learner and employs theories of learning, instruction, and environment to design each component.

The Psychophysics of Learning presents a learning system design approach that is formulated by the strategies and techniques the brain uses to process external information and make sense of that information to the learning ecology of all learners.

This book explains the interaction between artificial intelligence and higher education. It explores artificial intelligence’s tangible and intangible impact on higher education and scientific research and discusses how higher education and scientific research enhance the progress of artificial intelligence technologies. Based on systematic analysis with a multidisciplinary approach and a combination of theory and practice, the book brings original perspectives from the massive use of artificial intelligence in higher education and scientific research since the appearance of COVID-19. This book also discusses ethics in artificial intelligence, taking into consideration the recommendation on ethics of artificial intelligence adopted by UNESCO. This book explains the importance of technological sovereignty and new strategies to face current and future challenges related to e-learning, deep learning, and machine learning.