Last night we held our first Curriculum Night for this school year. The focus of this curriculum night was data and how we at Levine Academy are using data to drive instruction in our classrooms on a daily basis. Data Driven Instruction is a methodical approach to improving student learning throughout the year. The sequence of data-driven instruction includes data collection, data analysis, and action and is a key framework for school-wide support of all student success. Data analysis provides a snapshot of what students know, what they should know, and what can be done to meet their academic needs. With appropriate collection, analysis and interpretation of data, educators can make well informed decisions that positively affect student achievement.
Research has shown that using data in instructional decisions can lead to improved student performance (Wayman, 2005; Wayman, Cho, & Johnston, 2007; Wohlstetter, Datnow, & Park, 2008). No single assessment can tell educators all they need to know to make well-informed instructional decisions, so researchers stress the use of multiple data sources. When it comes to improving instruction and learning, it's not the quantity of the data that counts, but how the information is used (Hamilton et al., 2009).
At our presentation last night we had an opportunity to share with parents our overall process of Data Driven Instruction at Levine Academy. When we think about data we naturally think tests, and while tests are an important source of data they are not the only source, we also use inventories, reading observations, writing samples, running records and exit tickets together with our more formal assessment such as our Fountas and Pinnell Benchmark Assessments and EM4 Unit Assessments. Another form of assessment is our ERB given in 5th-8th grade and MAP testing given in K-4th grade (Click HERE to see the handout from last night). These are norm-referenced tests given at the beginning of the year. These give us valuable information regarding areas of focus school wide for the school year. Taking the data from multiple sources and recording it in a meaningful way is the first step in our data driven instruction cycle.
The analysis of the data tells us the strengths and needs of individuals, small groups of students, and the entire class. Once we have analyzed our data it is time to take action and to make solid instructional decisions. Teachers at each grade level collaborate with their partner teacher or teacher teams to create appropriate lessons to address the needs of their students based on the data. This is where differentiation comes into play. Teachers differentiate content, instructional methods and product.
Data driven instruction is an ongoing process. At our November Parent-Teacher Conferences teachers will be sharing several different forms of student data with parents. We look forward to rich, productive conversations regarding your child's learning profile.
Ann & Nate Levine Academy