Though in the past online learning was considered of poorer professional quality than classroom learning, it has become a useful and, in some cases, vital tool for promoting the inclusivity of education. Some of its benefits include allowing greater accessibility to educational resources previously unattainable by those in rural areas, and in current times, it has proven to be a critical asset as universities shut down due to natural disasters and pandemics. Examining the current state of distance learning and determining online assessment tools and processes that can enhance the online learning experience are clearly crucial for the advancement of modern education. The Handbook of Research on Determining the Reliability of Online Assessment and Distance Learning is a collection of pioneering investigations on the methods and applications of digital technologies in the realm of education. It provides a clear and extensive analysis of issues regarding online learning while also offering frameworks to solve these addressed problems. Moreover, the book reviews and evaluates the present and intended future of distance learning, focusing on the societal and employer perspective versus the academic proposals. While highlighting topics including hybrid teaching, blended learning, and telelearning, this book is ideally designed for teachers, academicians, researchers, educational administrators, and students.

This guidebook is designed to be the high school teacher's friend in addressing a wide variety of questions regarding the use of educational and instructional technologies. It can serve as a companion and guide through the myriad challenges and opportunities related to the effective use of technology in one's classroom and school. A sample of U.S. high school teachers provided us with detailed answers about their experiences with using technology in their teaching. Specifically, they shared their challenges, barriers, ideas, and suggestions for working successfully with administrators, technology specialists, students, fellow teachers, and parents when teaching with technology. We have organized the teachers' experiences and recommendations according to each stakeholder group. Rather than recommending or reviewing specific educational technology companies, applications, or tools, we provide a large number of strategies that are "built to last" and should be applicable regardless of the specific tool under consideration. We assume that it doesn't ultimately matter what the tool or technology is that you're using-it's how and why you're using it for teaching and learning that will determine whether it is successful or not. The "how" and "why" aspects encompass the built-to-last strategies included in this guidebook.

In today's modernized world, the field of healthcare has seen significant practical innovations with the implementation of computational intelligence approaches and soft computing methods. These two concepts present various solutions to complex scientific problems and imperfect data issues. This has made both very popular in the medical profession. There are still various areas to be studied and improved by these two schemes as healthcare practices continue to develop. Computational Intelligence and Soft Computing Applications in Healthcare Management Science is an essential reference source that discusses the implementation of soft computing techniques and computational methods in the various components of healthcare, telemedicine, and public health. Featuring research on topics such as analytical modeling, neural networks, and fuzzy logic, this book is ideally designed for software engineers, information scientists, medical professionals, researchers, developers, educators, academicians, and students.

Designed as a project and case-oriented approach to learning Excel, the emphasis of this book is on learning by doing. The book presents a series of progressively reinforcing problem sets, which allow the exploration of real-life business problems. First, the background, theory, formulas, and calculations are discussed, followed by the design of Excel spreadsheets, which support the creation of effective spreadsheets for these applications. Finally, the proper solution and other related aspects are discussed, forming a cohesive set of practical application problems. Some of the topics explored include amortization tables, weighted averages, cash flows, payroll calculations, break even analysis, and spreadsheet databases. Excel techniques include formulas and functions, cell addressing, conditional and lookup functions, graphs, sorting, and filtering. FEATURES Provides 30 projects, several How-to Guides, and Application Types to learn Excel skills using problems, applications, and case studies featuring practical business problems Explores formulas and functions, financial functions, cell addressing, conditional functions, lookup functions, graphs, sorting, and filtering, amortization tables, future values of an investment, weighted averages, cash flows, payroll calculations, break even analysis, economic order quantity, spreadsheet databases, and more Companion files with four Excel video tutorials and images from the text. Instructor resources available.

Updates the premier textbook for students and librarians needing to know the landscape of current databases and how to search them. Librarians need to know of existing databases, and they must be able to teach search capabilities and strategies to library users. This practical guide introduces librarians to a broad spectrum of fee-based and freely available databases and explains how to teach them. The updated 6th edition of this well-regarded text covers new databases on the market as well as updates to older databases. It also explains underlying information structures and demonstrates how to search most effectively. It introduces readers to several recent changes, such as the move away from metadata-based indexing to full text indexing by vendors covering newspaper content. Business databases receive greater emphasis. As in the previous edition, this book takes a real-world approach, covering topics from basic and advanced search tools to online subject databases. Each chapter includes a thorough discussion, a recap, concrete examples, exercises, and points to consider, making it an ideal text for courses in database searching as well as a trustworthy professional resource. Helps librarians and students understand the latest developments in library databases Looks not only at textual databases but also numerical, image, video, and social media resources Includes changes and trends in database functionality since the 5th edition

Artificial intelligence has been utilized in a diverse range of industries as more people and businesses discover its many uses and applications. A current field of study that requires more attention, as there is much opportunity for improvement, is the use of artificial intelligence within literary works and social media analysis. Artificial Intelligence Applications in Literary Works and Social Media presents contemporary developments in the adoption of artificial intelligence in textual analysis of literary works and social media and introduces current approaches, techniques, and practices in data science that are implemented to scrap and analyze text data. This book initiates a new multidisciplinary field that is the combination of artificial intelligence, data science, social science, literature, and social media study. Covering key topics such as opinion mining, sentiment analysis, and machine learning, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

Computational Methods in Drug Discovery and Repurposing for Cancer Therapy provides knowledge about ongoing research and computational approaches for drug discovery and repurposing for cancer therapy. The book provides detailed descriptions about target molecules and pathways and their inhibitors for easy understanding and applicability. Users will find discussions on tools and techniques such as integrated bioinformatics approaches, systems biology tools, molecular docking, computational chemistry, artificial intelligence, machine learning, structure-based virtual screening, biomarkers and transcriptome which are discussed in the context of different cancer types, such as colon, glioblastoma, endometrial and retinoblastoma, amongst others. This book will be a valuable resource for researchers, students and member of the biomedical and medical fields who want to learn more about the use of computational modeling to better tailor treatments for cancer patients.