Author: David Kirp Publisher: Oxford University Press ISBN: 019086222X Category : Education Languages : en Pages : 185
Book Description
Higher education today faces a host of challenges, from quality to cost. But too little attention gets paid to a startling fact: four out of ten students -- that's more than ten percent of the entire population - -who start college drop out. The situation is particularly dire for black and Latino students, those from poor families, and those who are first in their families to attend college. In The College Dropout Scandal, David Kirp outlines the scale of the problem and shows that it's fixable - -we already have the tools to boost graduation rates and shrink the achievement gap. Many college administrators know what has to be done, but many of them are not doing the job - -the dropout rate hasn't decreased for decades. It's not elite schools like Harvard or Williams who are setting the example, but places like City University of New York and Long Beach State, which are doing the hard work to assure that more students have a better education and a diploma. As in his New York Times columns, Kirp relies on vivid, on-the-ground reporting, conversations with campus leaders, faculty and students, as well as cogent overviews of cutting-edge research to identify the institutional reforms--like using big data to quickly identify at-risk students and get them the support they need -- and the behavioral strategies -- from nudges to mindset changes - -that have been proven to work. Through engaging stories that shine a light on an underappreciated problem in colleges today, David Kirp's hopeful book will prompt colleges to make student success a top priority and push more students across the finish line, keeping their hopes of achieving the American Dream alive.
Author: Ken Yale Publisher: Elsevier ISBN: 0124166458 Category : Mathematics Languages : en Pages : 824
Book Description
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Author: Mohd Azlishah Othman Publisher: Springer ISBN: 303020717X Category : Technology & Engineering Languages : en Pages : 110
Book Description
This book gathers the proceedings of a symposium on the role of Internet technologies and how they can transform and improve people’s lives. The Internet is essentially a massive database where all types of information can be shared and transmitted. This can be done passively in the form of non-interactive websites and blogs; or it can be done actively in the form of file sharing and document up- and downloading. Thanks to these technologies, a wealth of information is now available to anyone who can access the Internet. Moreover, Internet technologies are constantly improving: growing faster, offering more diverse information, and supporting processes that would have been impossible in the past. As a result, they have changed, and will continue to change, the way that the world does business and how people interact in their day-to-day lives. In conclusion, the symposium and these proceedings provide a valuable opportunity for leading researchers, engineers and professionals around the globe to discuss the latest advances that are helping the world move forward. They also facilitate the exchange of new ideas in the fields of communication technology to create a dialogue between these groups concerning the latest innovations, trends and concerns, practical challenges and potential solutions in the field of Internet technologies.
Author: John M. Braxton Publisher: John Wiley & Sons ISBN: 111821661X Category : Education Languages : en Pages : 116
Book Description
Student departure is a long-standing problem to colleges and universities. Approximately 45 percent of students enrolled in two-year colleges depart during their first year, and approximately one out of four students departs from a four-year college or university. The authors advance a serious revision of Tinto's popular interactionalist theory to account for student departure, and they postulate a theory of student departure in commuter colleges and universities. This volume delves into the literature to describe exemplary campus-based programs designed to reduce student departure. It emphasizes the importance of addressing student departure through a multidisciplinary approach, engaging the whole campus. It proposes new models for nonresidential students and students from diverse backgrounds, and suggests directions for further research. Academic and student affairs administrators seeking research-based approaches to understanding and reducing student departure will profit from reading this volume. Scholars of the college student experience will also find it valuable in defining new thrusts in research on the student departure process.
Author: Derya Birant Publisher: BoD – Books on Demand ISBN: 183968318X Category : Computers Languages : en Pages : 214
Book Description
Data mining is a branch of computer science that is used to automatically extract meaningful, useful knowledge and previously unknown, hidden, interesting patterns from a large amount of data to support the decision-making process. This book presents recent theoretical and practical advances in the field of data mining. It discusses a number of data mining methods, including classification, clustering, and association rule mining. This book brings together many different successful data mining studies in various areas such as health, banking, education, software engineering, animal science, and the environment.
Author: Aboul Ella Hassanien Publisher: Springer Nature ISBN: 303059338X Category : Computers Languages : en Pages : 648
Book Description
This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.
Author: Aboul Ella Hassanien Publisher: Springer Nature ISBN: 3030311295 Category : Technology & Engineering Languages : en Pages : 1093
Book Description
This book presents the proceedings of the 5th International Conference on Advanced Intelligent Systems and Informatics 2019 (AISI2019), which took place in Cairo, Egypt, from October 26 to 28, 2019. This international and interdisciplinary conference, which highlighted essential research and developments in the fields of informatics and intelligent systems, was organized by the Scientific Research Group in Egypt (SRGE). The book is divided into several sections, covering the following topics: machine learning and applications, swarm optimization and applications, robotic and control systems, sentiment analysis, e-learning and social media education, machine and deep learning algorithms, recognition and image processing, intelligent systems and applications, mobile computing and networking, cyber-physical systems and security, smart grids and renewable energy, and micro-grid and power systems.
Author: Samira ElAtia Publisher: John Wiley & Sons ISBN: 1118998219 Category : Computers Languages : en Pages : 351
Book Description
Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates. Initial series of chapters offer a general overview of DM, Learning Analytics (LA), and data collection models in the context of educational research, while also defining and discussing data mining’s four guiding principles— prediction, clustering, rule association, and outlier detection. The next series of chapters showcase the pedagogical applications of Educational Data Mining (EDM) and feature case studies drawn from Business, Humanities, Health Sciences, Linguistics, and Physical Sciences education that serve to highlight the successes and some of the limitations of data mining research applications in educational settings. The remaining chapters focus exclusively on EDM’s emerging role in helping to advance educational research—from identifying at-risk students and closing socioeconomic gaps in achievement to aiding in teacher evaluation and facilitating peer conferencing. This book features contributions from international experts in a variety of fields. Includes case studies where data mining techniques have been effectively applied to advance teaching and learning Addresses applications of data mining in educational research, including: social networking and education; policy and legislation in the classroom; and identification of at-risk students Explores Massive Open Online Courses (MOOCs) to study the effectiveness of online networks in promoting learning and understanding the communication patterns among users and students Features supplementary resources including a primer on foundational aspects of educational mining and learning analytics Data Mining and Learning Analytics: Applications in Educational Research is written for both scientists in EDM and educators interested in using and integrating DM and LA to improve education and advance educational research.
Author: Leigh N. Wood Publisher: Springer ISBN: 9811027919 Category : Education Languages : en Pages : 364
Book Description
This book explores successful transition strategies to, within and from university for students from around the globe, with Macquarie University, a large Australian university, studied in depth. It addresses the meaning of success taking a variety of perspectives, including student, staff and employer views. The chapters present a series of initiatives that have proven to be successful in assisting students in developing their academic potential throughout university and beyond. The authors of the chapters use a variety of methodologies and approaches reflecting the diverse local contexts and requirements. These international perspectives demonstrate a triumph of practice that has led to the empowerment of individuals and groups. The approaches from twelve universities located in eight different countries stem directly from the coalface and provide many valuable lessons and tools that colleagues in the sector will be able to consider and adapt in their own contexts. Small interventions matter, from a mentor of a nervous student who goes on to achieve greatness, to the use of a curriculum design model that hooks a whole group of students into learning and achievement. This book covers both the small, individual victories and the larger scale strategies that support success. Contributions emanate from Australia, Bangladesh, India, China, New Zealand, United Kingdom, Canada, USA, Uruguay and South Africa.
Author: Jaime Lester Publisher: John Wiley & Sons ISBN: 1119478464 Category : Education Languages : en Pages : 155
Book Description
Learning analytics (or educational big data) tools are increasingly being deployed on campuses to improve student performance, retention and completion, especially when those metrics are tied to funding. Providing personalized, real-time, actionable feedback through mining and analysis of large data sets, learning analytics can illuminate trends and predict future outcomes. While promising, there is limited and mixed empirical evidence related to its efficacy to improve student retention and completion. Further, learning analytics tools are used by a variety of people on campus, and as such, its use in practice may not align with institutional intent. This monograph delves into the research, literature, and issues associated with learning analytics implementation, adoption, and use by individuals within higher education institutions. With it, readers will gain a greater understanding of the potential and challenges related to implementing, adopting, and integrating these systems on their campuses and within their classrooms and advising sessions. This is the fifth issue of the 43rd volume of the Jossey-Bass series ASHE Higher Education Report. Each monograph is the definitive analysis of a tough higher education issue, based on thorough research of pertinent literature and institutional experiences. Topics are identified by a national survey. Noted practitioners and scholars are then commissioned to write the reports, with experts providing critical reviews of each manuscript before publication.
Author: David Kirp
Author: Ken Yale
Author: Mohd Azlishah Othman
Author: John M. Braxton
Author: Derya Birant
Author: Aboul Ella Hassanien
Author: Aboul Ella Hassanien
Author: Samira ElAtia
Author: Leigh N. Wood
Author: Jaime Lester