Search results for: transforming-teaching-and-learning-through-data-driven-decision-making

Transforming Teaching and Learning Through Data Driven Decision Making

Author : Ellen B. Mandinach
File Size : 26.87 MB
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Connect data and instruction to improve practice This book helps bridge the gap between classroom practice and the best of what is known from educational psychology. Teachers will find cutting-edge advances in research and theory on human learning, teaching, and instruction in an easily understood and transferable format. The authors provide detailed guidance for using data to inform practice and tools to align teacher preparation and professional development with today's best practices and most current research. This resource will provide valuable tools for: In-service teachers Pre-service teachers Instructional leaders School and district administrators

Transforming Teaching and Learning Through Data Driven Decision Making

Author : Ellen B. Mandinach
File Size : 36.22 MB
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Connect data and instruction to improve practice Gathering data and using it to inform instruction is a requirement for many schools, yet educators are not necessarily formally trained in how to do it. This book helps bridge the gap between classroom practice and the principles of educational psychology. Teachers will find cutting-edge advances in research and theory on human learning and teaching in an easily understood and transferable format. The text’s integrated model shows teachers, school leaders, and district administrators how to establish a data culture and transform quantitative and qualitative data into actionable knowledge based on: Assessment Statistics Instructional and differentiated psychology Classroom management

Transforming Teaching and Learning Through Data driven Decision Making

Author : Ellen Beth Mandinach
File Size : 26.96 MB
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Gathering data and using it to inform instruction is a requirement for many schools, yet educators are not necessarily formally trained in how to do it. This book helps bridge the gap between classroom practice and the principles of educational psychology. Teachers will find cutting-edge advances in research and theory on human learning and teaching in an easily understood and transferable format. The text's integrated model shows teachers, school leaders, and district administrators how to establish a data culture and transform quantitative and qualitative data into actionable knowledge based on assessment, statistics, instructional and differentiated psychology, and classroom management

Using Data to Improve Student Learning

Author : Graham S. Maxwell
File Size : 33.66 MB
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This book offers a coherent research-based overview and analysis of theories and practices in using data to improve student learning. It clarifies what 'use of data' means and differentiates the different levels of decision-making in education (relating to the system, district, school, classroom, or individual student). The relationship between data and decision-making is considered and various movements in the use of data to improve student learning are analysed, especially from the perspective of their assumptions and effects. This leads to a focus on effective educational decision-making as a social process requiring collaboration among all relevant participants. It also requires a clear understanding of educational aims, and these are seen to transcend what can be assessed by standardised tests. The consequences of this analysis for decision processes are explored and conclusions are drawn about what principles might best guide educational practice as well as what ambiguities remain. Throughout, the focus is on what existing research says about each of the issues explored.

Data Leadership for K 12 Schools in a Time of Accountability

Author : Mense, Evan G.
File Size : 20.3 MB
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The monitoring of data within educational institutions is essential to ensure the success of its students and faculty. By continually analyzing data, educational leaders can increase quality and productivity in their institutions. Data Leadership for K-12 Schools in a Time of Accountability explores techniques and processes of educational data analysis and its application in developing solutions and systems for instructional concerns and next-generation learning. Providing extensive research covering areas such as data-driven culture, student accountability, and data dissemination, this unique reference is essential for principals, administrators, practitioners, academicians, students, and educational consultants looking to maximize their institution’s performance.

Curriculum and Teaching Dialogue

Author : Chara Haeussler Bohan
File Size : 55.12 MB
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Curriculum and Teaching Dialogue is a peer-reviewed journal sponsored by the American Association for Teaching and Curriculum. The purpose of the journal is to promote the scholarly study of teaching and curriculum. The aim is to provide readers with knowledge and strategies of teaching and curriculum that can be used in educational settings. The journal is published annually in two volumes and includes traditional research papers, conceptual essays, as well as research outtakes and book reviews. Publication in CTD is always free to authors. Information about the journal is located on the AATC website http://aatchome.org/ and can be found on the Journal tab at http://aatchome.org/about-ctd-journal/

Artificial Intelligence in Education

Author : Carolyn Penstein Rosé
File Size : 46.72 MB
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This two volume set LNAI 10947 and LNAI 10948 constitutes the proceedings of the 19th International Conference on Artificial Intelligence in Education, AIED 2018, held in London, UK, in June 2018.The 45 full papers presented in this book together with 76 poster papers, 11 young researchers tracks, 14 industry papers and 10 workshop papers were carefully reviewed and selected from 192 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas.

Handbook of Educational Psychology

Author : Lyn Corno
File Size : 86.81 MB
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The third edition of the Handbook of Educational Psychology is sponsored by Division 15 of the American Psychological Association. In this volume, thirty chapters address new developments in theory and research methods while honoring the legacy of the field’s past. A diverse group of recognized scholars within and outside the U.S. provide integrative reviews and critical syntheses of developments in the substantive areas of psychological inquiry in education, functional processes for learning, learner readiness and development, building knowledge and subject matter expertise, and the learning and task environment. New chapters in this edition cover topics such as learning sciences research, latent variable models, data analytics, neuropsychology, relations between emotion, motivation, and volition (EMOVO), scientific literacy, sociocultural perspectives on learning, dialogic instruction, and networked learning. Expanded treatment has been given to relevant individual differences, underlying processes, and new research on subject matter acquisition. The Handbook of Educational Psychology, Third Edition, provides an indispensable reference volume for scholars in education and the learning sciences, broadly conceived, as well as for teacher educators, practicing teachers, policy makers and the academic libraries serving these audiences. It is also appropriate for graduate level courses in educational psychology, human learning and motivation, the learning sciences, and psychological research methods in education and psychology.

Data Literacy for Educators

Author : Ellen B. Mandinach
File Size : 47.54 MB
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Data literacy has become an essential skill set for teachers as education becomes more of an evidence-based profession. Teachers in all stages of professional growth need to learn how to use data effectively and responsibly to inform their teaching practices. This groundbreaking resource describes data literacy for teaching, emphasizing the important relationship between data knowledge and skills and disciplinary and pedagogical content knowledge. Case studies of emerging programs in schools of education are used to illustrate the key components needed to integrate data-driven decisionmaking into the teaching curricula. The book offers a clear path for change while also addressing the inherent complexities associated with change. Data Literacy for Educators provides concrete strategies for schools of education, professional developers, and school districts. Book Features: Defines data literacy for teaching and outlines the knowledge and skills it comprises. Uses examples and case studies that tie theory to practice. Provides a roadmap for integrating data literacy into teacher preparation programs. Covers emerging trends, such as virtual and hybrid courses and massive open online courses. “This thoughtful, well-organized book raises the challenges that beginning and experienced teachers face in becoming more data literate to increase their pedagogical effectiveness in their classrooms.” —From the Foreword by Barbara Schneider “Deans of colleges of education, practicing teachers, education advocates, and many others will find useful information here.” —Benjamin Riley, Deans for Impact “This work should join the ‘common core’ of teacher education and professional development programs.” —Lee S. Shulman, The Carnegie Foundation for the Advancement of Teaching “The authors lay out a compelling call to action to ensure that every teacher in this country has the skills, knowledge, and disposition in knowing how to use data to inform effective teaching.” —Aimee Rogstad Guidera, Data Quality Campaign

Design Recommendations for Intelligent Tutoring Systems Volume 7 Self Improving Systems

Author : Benjamin Goldberg
File Size : 87.20 MB
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This book on self-improving systems is the seventh in a planned series of books that examine key topics (e.g., learner modeling, instructional strategies, authoring, domain modeling, assessment, impact on learning, team tutoring, self-improving systems, data visualization) in intelligent tutoring system (ITS) design. This book focuses on self-improving systems. The discussion chapters in this book examine topics through the lens of the Generalized Intelligent Framework for Tutoring (GIFT). GIFT is a modular, service-oriented architecture created to reduce the cost and skill required to author ITSs, distribute ITSs, manage instruction within ITSs, and evaluate the effect of ITS technologies on learning, performance, retention, transfer of skills, and other instructional outcomes.