Design And Implementation Of Higher Education Learners Learning Outcomes Hello
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Design and Implementation of Higher Education Learners' Learning Outcomes (HELLO)
The Higher Education Learners’ Learning Outcomes (HELLO) project offers a comprehensive solution to the challenge of creating comparative metrics of learning outcomes that are valid across various cultures, languages, and higher education institution types. Traditional methods of assessing learning outcomes in higher education have limited institutions' abilities to compare student performance to that of their peers, hindering efforts to improve teaching practices and enhance student learning. This project creates learning outcome measures that are culturally and linguistically appropriate for different types of higher education institutions, enabling institutions to compare student performance to that of their peers as part of efforts to improve teaching practices and enhance student learning. Design and Implementation of Higher Education Learners’ Learning Outcomes (HELLO), edited by Kuntal Barua, Neyara Radwan Mohammed, Virendra Singh, and Ronnie Figueiredo, provides a persuasive account of the HELLO project and is intended for all students, teachers, administrations, and higher education institutions interested in improving teaching practices and enhancing student learning outcomes. The book presents the challenges in traditional methods of assessing learning outcomes, the limitations of diverse attempts to fill the quality information gap, and the rationale for HELLO beyond collegial approaches and student-centered learning. The book also explores key challenges in developing and executing HELLO, such as the risks of ranking and value-added methodologies. By offering a comprehensive overview of the HELLO project, this book provides higher education institutions with the information and motivation they need to participate in the project and enhance their students' learning outcomes.
Interdisciplinary Approaches to AI, Internet of Everything, and Machine Learning
Artificial intelligence (AI), the Internet of Everything (IoE), and Machine Learning (ML) are transforming modern society by driving innovation and improving efficiency across diverse fields. These technologies enable seamless connectivity, intelligent decision-making, and data-driven solutions that address complex global challenges. From revolutionizing industries like healthcare, education, and transportation to enhancing communication and resource management, their applications are vast and impactful. Interdisciplinary approaches are critical for unlocking their full potential, fostering collaboration across sectors to develop sustainable, ethical, and inclusive solutions. As these technologies continue to shape the future, they hold the promise of advancing societal progress while addressing pressing issues. Interdisciplinary Approaches to AI, Internet of Everything, and Machine Learning explores interdisciplinary approaches to harnessing AI, IoT, and ML to address complex challenges and drive innovation across various fields. It emphasizes collaborative strategies to develop sustainable, ethical, and impactful technological solutions for a rapidly evolving world. Covering topics such as artificial neural networks, management information systems, and supply chain management, this book is an excellent resource for researchers, technologists, industry professionals, educators, policymakers, and more.
Role of Internet of Everything (IOE), VLSI Architecture, and AI in Real-Time Systems
The Internet of Things (IoT) is revolutionizing manufacturing by enabling interconnected systems that enhance data collection, human-machine interaction, and intelligent control processes. However, the complexity of modern industrial environments presents challenges for signal processing, a critical component of IoT efficiency. Advances in intelligent, cost-effective, and energy-efficient signal processing algorithms are essential for overcoming these limitations and driving IoT innovation. Moreover, integrating IoT with technologies like artificial intelligence (AI), deep learning, and VLSI has expanded its applications, enabling more reliable, scalable, and compact solutions. These developments not only optimize industrial processes but also open new economic opportunities, reinforcing the importance of IoT in shaping the future of business and technology. Role of Internet of Everything (IOE), VLSI Architecture, and AI in Real-Time Systems explores the role of intelligent signal processing (ISP) and cutting-edge technologies like AI, deep learning, and VLSI in advancing IoT applications within manufacturing and business systems. It emphasizes innovative approaches to overcoming IoT challenges, focusing on cost-effective, energy-efficient solutions that drive reliability, scalability, and economic growth. Covering topics such as security systems, financial risk management, and workforce management, this book is an excellent resource for academicians, researchers, graduate students, practitioners, professionals, and more.