Student Assessment : Better Evidence, Better Decisions, Better Learning

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.

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.