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? This volume 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; and 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.