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.

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 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.

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.

Using Generative AI Effectively in Higher Education explores how higher education providers can realise their role and responsibility in harnessing the power of generative artificial intelligence (GenAI) ethically and sustainably. This rich collection of established and evaluated practices from across global higher education offers a practical guide to leading an agile institutional response to emerging technologies, building critical digital literacy across an entire institution, and embedding the ethical and sustainable use of GenAI in teaching, learning, and assessment. Including reflections from stakeholders testifying to the value of the approaches outlined, the book examines how higher education can equip staff and students with the critical-digital literacy necessary to use GenAI in work, study, and social life responsibly and with integrity. It provides an evidence-based resource for any kind of higher education (HE) provider (modern, college-based, and research-focused) looking for inspiration and approaches which can build GenAI capability and includes chapters on the development of cross-institutional strategy, policies and processes, pedagogic practices, and critical-digital literacy. This resource will be invaluable to educational leaders, educational developers, learning developers, learning technologists, course administrators, quality assurance staff, and HE teachers wishing to embrace and adapt to a GenAI-enabled world.