Learning Patterns in Higher Education


Book Description

Learning Patterns in Higher Education brings together a cutting edge international team of contributors to critically review our current understanding of how students and adults learn, how differences and changes in the way students learn can be measured in a valid and reliable way, and how the quality of student learning may be enhanced. There is substantial evidence that students in higher education have a characteristic way of learning, sometimes called their learning orientation (Biggs 1988), learning style (Evans et al. 2010) or learning pattern (Vermunt and Vermetten 2004). However, recent research in the field of student learning has resulted in multi-faceted and sometimes contradictory results which may reflect conceptual differences and differences in measurement of student learning in each of the studies. This book deals with the need for further clarification of how students learn in higher education in the 21st century and to what extent the measurements often used in learning pattern studies are still up to date or can be advanced with present methodological and statistical insights to capture the most important differences and changes in student learning. The contributions in the book are organized in two parts: a first conceptual and psychological part in which the dimensions of student learning in the 21st century are discussed and a second empirical part in which questions related to how students’ learning can be measured and how it develops are considered. Areas covered include: Cultural influences on learning patterns Predicting learning outcomes Student centred learning environments and self-directed learning Mathematics learning This indispensable book covers multiple conceptual perspectives on how learning patterns can be described and effects and developments can be measured, and will not only be helpful for ‘learning researchers’ as such but also for educational researchers from the broad domain of educational psychology, motivation psychology and instructional sciences, who are interested in student motivation, self-regulated learning, effectiveness of innovative learning environments, as well as assessment and evaluation of student characteristics and learning process variables.




Learning Patterns in Higher Education


Book Description

Learning Patterns in Higher Education brings together a cutting edge international team of contributors to critically review our current understanding of how students and adults learn, how differences and changes in the way students learn can be measured in a valid and reliable way, and how the quality of student learning may be enhanced. There is substantial evidence that students in higher education have a characteristic way of learning, sometimes called their learning orientation (Biggs 1988), learning style (Evans et al. 2010) or learning pattern (Vermunt and Vermetten 2004). However, recent research in the field of student learning has resulted in multi-faceted and sometimes contradictory results which may reflect conceptual differences and differences in measurement of student learning in each of the studies. This book deals with the need for further clarification of how students learn in higher education in the 21st century and to what extent the measurements often used in learning pattern studies are still up to date or can be advanced with present methodological and statistical insights to capture the most important differences and changes in student learning. The contributions in the book are organized in two parts: a first conceptual and psychological part in which the dimensions of student learning in the 21st century are discussed and a second empirical part in which questions related to how students’ learning can be measured and how it develops are considered. Areas covered include: Cultural influences on learning patterns Predicting learning outcomes Student centred learning environments and self-directed learning Mathematics learning This indispensable book covers multiple conceptual perspectives on how learning patterns can be described and effects and developments can be measured, and will not only be helpful for ‘learning researchers’ as such but also for educational researchers from the broad domain of educational psychology, motivation psychology and instructional sciences, who are interested in student motivation, self-regulated learning, effectiveness of innovative learning environments, as well as assessment and evaluation of student characteristics and learning process variables.




Teaching as a Design Science


Book Description

Teaching is changing. It is no longer simply about passing on knowledge to the next generation. Teachers in the twenty-first century, in all educational sectors, have to cope with an ever-changing cultural and technological environment. Teaching is now a design science. Like other design professionals – architects, engineers, programmers – teachers have to work out creative and evidence-based ways of improving what they do. Yet teaching is not treated as a design profession. Every day, teachers design and test new ways of teaching, using learning technology to help their students. Sadly, their discoveries often remain local. By representing and communicating their best ideas as structured pedagogical patterns, teachers could develop this vital professional knowledge collectively. Teacher professional development has not embedded in the teacher’s everyday role the idea that they could discover something worth communicating to other teachers, or build on each others’ ideas. Could the culture change? From this unique perspective on the nature of teaching, Diana Laurillard argues that a twenty-first century education system needs teachers who work collaboratively to design effective and innovative teaching.




Big Data and Learning Analytics in Higher Education


Book Description

​This book focuses on the uses of big data in the context of higher education. The book describes a wide range of administrative and operational data gathering processes aimed at assessing institutional performance and progress in order to predict future performance, and identifies potential issues related to academic programming, research, teaching and learning​. Big data refers to data which is fundamentally too big and complex and moves too fast for the processing capacity of conventional database systems. The value of big data is the ability to identify useful data and turn it into useable information by identifying patterns and deviations from patterns​.




Accomplishing Change in Teaching and Learning Regimes


Book Description

This book uses social practice theory to offer a new perspective on the professional world of higher education. It presents a practice sensibility that helps to identify the successful paths to changes for enhancement in teaching and learning regimes.




Patterns for College Writing with 2021 MLA Update


Book Description

This ebook has been updated to provide you with the latest guidance on documenting sources in MLA style and follows the guidelines set forth in the MLA Handbook, 9th edition (April 2021). Patterns for College Writing provides instruction, visual texts, diverse essays, and student writing examples to help you develop your writing skills using rhetorical patterns like narration, description, argumentation, and more.




Demographics and the Demand for Higher Education


Book Description

"The economics of American higher education are driven by one key factor--the availability of students willing to pay tuition--and many related factors that determine what schools they attend. By digging into the data, economist Nathan Grawe has created probability models for predicting college attendance. What he sees are alarming events on the horizon that every college and university needs to understand. Overall, he spots demographic patterns that are tilting the US population toward the Hispanic southwest. Moreover, since 2007, fertility rates have fallen by 12 percent. Higher education analysts recognize the destabilizing potential of these trends. However, existing work fails to adjust headcounts for college attendance probabilities and makes no systematic attempt to distinguish demand by institution type. This book analyzes demand forecasts by institution type and rank, disaggregating by demographic groups. Its findings often contradict the dominant narrative: while many schools face painful contractions, demand for elite schools is expected to grow by 15+ percent. Geographic and racial profiles will shift only slightly--and attendance by Asians, not Hispanics, will grow most. Grawe also use the model to consider possible changes in institutional recruitment strategies and government policies. These "what if" analyses show that even aggressive innovation is unlikely to overcome trends toward larger gaps across racial, family income, and parent education groups. Aimed at administrators and trustees with responsibility for decisions ranging from admissions to student support to tenure practices to facilities construction, this book offers data to inform decision-making--decisions that will determine institutional success in meeting demographic challenges"--







Patterns and Profiles of Promising Learners from Poverty


Book Description

Patterns and Profiles of Promising Learners From Poverty provides a comprehensive review of the issues surrounding the education and inclusion of promising students from poverty in gifted and talented programs. Patterns and Profiles of Promising Learners From Poverty covers a variety of topics pertinent to the education of students from low-income families, including the role of culture in education, curriculum for promising learners, psychosocial stressors that affect these learners, professional development for teachers of low-income students, and state policy implementations that affect these students' educations. Chapters look specifically at several types of learners from poverty, including rural and urban-area students, African American students, Caucasian students, and high nonverbal, low verbal students. This book combines research and experience from leading scholars in the field of gifted education in a convenient guide for teachers, administrators, and gifted education program directors.




How Learning Works


Book Description

Praise for How Learning Works "How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning." —Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching "This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching." —Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education "Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues." —Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching "As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book." —From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning