Driven By Data by Paul Bambrick Santoyo, (00) Introduction, Notes

Post date: Mar 20, 2019 1:31:43 PM

Driven By Data by Paul Bambrick Santoyo

Introduction

• • Work with students on areas of weakness. Support them in their learning and be a forthteller--help them see the direction in which they are headed. This gives them a sense of purpose--the result of the successful implementation of best practices that increase student achievement as a well as a data driven instructional model designed to increase learning.

  • To reach proficiency is to open doors for future opportunity to succeed in college and in life. Data-centered methods, used properly, clearly define the most effective pathways to academic excellence. When applied correctly, gains in performance are dramatic. Focus on the core drivers that matter:

    1. A framework to guide actions

    2. Proof that it works

    3. Concrete tools put into action

  • Put plans into practice. The subtlest analyses and most nuanced action reports are worthless if they don’t lead to real change. Effective leadership and teacher training are the two most fundamental factors that shape a school’s ability to make data-driven instruction a reality. Teachers must be taught how to use data in their schools and classrooms. When schools make student learning the ultimate test of teaching, teaching improves to produce better learning. Teaching and learning must walk hand in hand.

  • The Framework: What does it mean to be data driven? The philosophy: Schools should consistently focus on one question: Are our students learning? The emphasis is on a clear-eyed, fact based focus on what students actually learned.

  • The Four Key Principles

• • 1. Assessment: Create rigorous interim assessments that provide meaningful data.

    2. Analysis: Examine the results of assessment to identify the causes of both strengths and shortcomings.

    3. Action: Teach effectively what most students need to learn.

    4. Culture: Create an environment in which data-driven instruction can survive and thrive.

• • The Eight Mistakes that Matter - These mistakes are common and must be vigilantly guarded against as they all pose a serious problem.

• • 1. Inferior interim assessment - interim assessment is the lifeblood of data-driven instruction. Without thoughtful and carefully crafted tests, an effective analysis of student strengths and weaknesses is impossible. Setting the bar too low, failing to align end-goal tests and neglecting open ended response sections are all common shortcomings. Effective data-driven instruction is only possible with an investment in creating or acquiring excellent interim assessments.

       • Key Drivers

         • Develop all aspects of the data driven implementation rubric.

         • Principal and leadership are in complete alignment and all are trained in leading effective analysis meetings.

         • Aligned to state test rigor - ‘beef up’ any assessments that are inferior.

    2. Secretive Interim Assessment - If interim assessment drives rigor, then teachers must know the end goal before they can work toward it.

    3. Infrequent Assessment - Interim tests need to be interim. If they aren’t regularly being assessed, there is no way to track progress through the year and no way to identify problems in time to correct them.

    4. Curriculum-Assessment Disconnect - The curriculum scope and sequence need to precisely match the standards on the interim assessment. Assessment results need to give data on what actually occurred in the classroom, otherwise the data is worthless.

    5. Delayed Results - Even the most nuanced assessment is of zero benefit if it isn’t graded and analyzed in a timely manner. Every day that passes between assessment and analysis of results is another day in which teachers present new material without correcting errors.

    6. Separation of Teaching and Analysis - Data driven instruction succeeds only when it is teacher owned. Teachers must analyze their own classroom’s data. Fundamental improvements are made when teachers take ownership for their own data.

    7. Ineffective follow up - a clear, simple system to implement specific plans at specific times after the results have been analyzed needs to be in place in order to make real change at the classroom level.

    8. Not making time for data - Structure and schedule time to assess and analyze data and to follow up. If not specifically embedded in the calendar, it will be overlooked and ignored--and ineffective. Leaders must also embrace the process and make it a priority in their own scheduling. We must all practice what we preach.

• • Roadside Distraction: False Drivers - Beware of false drivers. False drivers are surface changes that have little to do with actually improving, mistaken as root causes and pathways to excellence. Only invest in initiatives that lead to direct student excellence. False drivers, although important in some respects and not undesirable, take away from scarce time and resources. The three most commonly traveled ‘false’ paths:

• • 1. The pursuit of total buy-in: Time and effort invested in making people love an unproven idea are almost always wasted. Create buy in, don’t require it. At least be willing to try out the methods. Focus on fundamentals, achieve results and faith in the program will follow.

    2. Reliance on poorly implemented professional learning communities: It is critical that teachers share strategies and knowledge, but collaboration for collaboration’s sake is not inherently valuable. What matters most is not how much time is used for faculty collaboration but rather how meaningful the time is employed. Professional learning communities must be explicitly focused on analyzing student learning and identifying key action steps based on that analysis.

    3. Year end assessment analysis - What purpose does it serve to conduct an exhaustive analysis after the child is gone and nothing can be done to improve his or her learning at that point?

       • “The difference between a formative and a summative assessment is the difference between a physical and an autopsy.” -- Rick Dufour

       • Figure out what’s making a child ‘sick’ during the school year and provide the right medicine to attack the disease rather than analyze at the end when some student have already died (failed to learn.) Focus on interim assessment and avoid failures all together.

• 1. Identifying the Real Drivers: An Effective Methodology - The real drivers are the steps that reliably lead to outstanding student achievement. Data-driven schools use data to focus on ‘what was learned rather than ‘what was taught.’ Data-driven instruction is based on effective assessment analysis, action and culture. School failure with implementation of data-driven instruction is usually due to one of eight critical factors. Resources are often wasted on false drivers.

  2. Introduction: Reflection and Planning

     1. What are the most common mistakes and false drivers that make people struggle at your school?

     2. What are the first action steps that you could take to address these pitfalls?

     3. Who are the key people in your school -- the ones you need to share these steps with for data-driven instruction?

     4. How are you going to get people on board?