Student Assessment

Better Evidence, Better Decisions, Better Learning
1. Auflage 2024
ISBN: 978-1-0719-0936-2
Verlag: Sage Publications

Buch, Englisch, 176 Seiten, Format (B × H): 173 mm x 251 mm, Gewicht: 378 g

Fuel student-driven success and enhance learning with better assessment

What if there was a better way to collect and interpret assessment data that could strengthen the link between teaching and learning? Student Assessment: Better Evidence, Better Decisions, Better Learning is the innovative guide to show you how it's done and done right. This unique book offers a new assessment model focused on decision-driven data collection and provides an arsenal of tools for collecting better evidence to increase student learning. You will learn:

- the importance of assessment in the teaching and learning process

- what a decision-driven data collection assessment model looks like and how it differs from a more traditional data-driven decision-making model

- how to effectively establish learning intentions and success criteria within assessments to actively engage students in their own learning

- how to implement an array of assessment tools that yield better evidence and improve decision-making

- how to address the challenge of ensuring authenticity in students' responses when AI-generated content is becoming more common

With this guide in hand, you'll be ready for a better approach to assessment—armed with practical tools and strategies to ensure students can analyze, synthesize, adapt, critique, and most importantly, take charge of their own learning.

Autoren/Hrsg.

Wiliam, Dylan

Fisher, Douglas

Frey, Nancy

Fachgebiete

• Sozialwissenschaften Pädagogik Schulen, Schulleitung Schulleitung, Schulentwicklung Schulevaluation, Schulinspektion

Inhaltsverzeichnis

Praise Page
Publishers Acknowledgements
Table of Contents
Introduction
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
References
Index

Über Autor(innen)

Fisher, Douglas
Douglas Fisher is professor and chair of educational leadership at San Diego State University and a teacher leader at Health Sciences High and Middle College. Previously, Doug was an early intervention teacher and elementary school educator. He is a credentialed English teacher and administrator in California. In 2022, he was inducted into the Reading Hall of Fame by the Literacy Research Association. He has published numerous articles on reading and literacy, differentiated instruction, and curriculum design, as well as books such as The Teacher Clarity Playbook 2/e, Your Introduction to PLC+, The Illustrated Guide to Teacher Credibility, The Teaching Reading Playbook, and Welcome to Teaching!.

Wiliam, Dylan
Dr. Dylan Wiliam is emeritus professor of educational assessment at the UCL Institute of Education. He started his career teaching in urban London schools before transitioning to educational research. He was dean of the School of Education at King’s College London, senior research director at the Educational Testing Service in Princeton, US, and deputy director of the Institute of Education, University of London. His research has focused on the use of assessment to support learning (sometimes called formative assessment), and he now works with groups of teachers all over the world on developing formative assessment practices. Dylan’s recent books include Creating the Schools Our Children Need and Embedded Formative Assessment.

Frey, Nancy
Nancy Frey is a Professor in Educational Leadership at San Diego State and a teacher leader at Health Sciences High and Middle College. She is a credentialed special educator, reading specialist, and administrator in California. She is a member of the International Literacy Association’s Literacy Research Panel. Her published titles include The Illustrated Guide to Visible Learning, Welcome to Teaching Multilingual Learners, Teaching Foundational Skills to Adolescent Readers, and RIGOR Unveiled: A Video-Enhanced Flipbook to Promote Teacher Expertise in Relationship Building, Instruction, Goals, Organization, and Relevance.