Data Vs. Data Support Instruction Essay

With data driving instructional practices students achieve more, and with students achieving more school move closer

As a teacher I use formative and summative data to drive my instruction. As I start with the state standard for the lesson and plan a formative assessment on that skill before a summative assessment. In years prior our school district used the platform of Performance Matter to collect data of that grade level standards three times a year. This type of information set in with Dr. Scott McLeod (20??) essential concepts. “The five major elements of data-driven instruction are: good baseline, measurable instructional goals, frequent formative assessment, professional learning communities, and focused instructional interventions (pp. 1-2, 20??). The assessment gave teachers a baseline, mid-year, and end year focus. When the teacher delved into the platform each question was broken down each standard and concept, thus allowing teacher to provide adequate instructional goal to meet the students’ needs. Teachers would also look at past state standardized testing to determine what if any remediation is needed. As a principal, he/she/I needs to understand the data elements to schedule necessary people and aid for the professional development communities.

Our students come from a wide range of elementary and middle schools and enter our building without consistent levels of instruction that they would receive if they were all coming from a feeder middle school, which leads us to have students with an incredibly wide range of abilities and skills sets when they enter our doors. In response, we have had to create strong structures that hold teachers accountable to sharing and using data to modify their lessons because it is infeasible for us to level our classes perfectly. To do so, we have our instructional coaches work one on one with our teachers to create and update 6-week plans every single week to ensure that their instruction is actually meeting the needs of the learners that are in front of them. Due to these strategies, we had the highest growth in our entire network on the PSAT in quarter one for our ninth and tenth grade cohorts and we are on track to exceed our growth goals for the year. However, it is important to note, that our students have a high level of learning and emotional needs, which means that we have to approach classroom management and social work services differently than another school might. Our classroom management system has to incorporate a high emphasis on relationship and coalition building. It also means that we must approach our instruction in a way that is culturally responsive, culturally sustaining, and data driven. Another strategy that we have implemented to ensure that students have access to rigorous and challenging work is to consistently use data not solely to tell them where they are, but to empower and reinforce to students their worth and capabilities on a daily level. We have VIP lunches, ceremonies that recognize growth, and jobs well done. It is imperative to create a culture of celebration when it comes to acknowledging their hard

The methods our school organization uses to ensure accuracy of organizational data, information, and knowledge have been very effective. Before the state and our school organization came out with data collection observation tools, a lot of the information was inaccurate between content areas and educators. One educator would be evaluated one way and another a different way, thus proving inaccuracy amongst educators and fairness in the data that was being collected by school leadership. Now we have specific observation tools that are used and every educator knows that they are going to be evaluated and observed using the same data collection and observation tools as every educator in the building. This eliminates the opportunity

Suppose that the data for analysis include the attribute age. The age values for the data

The article, Code Red: The Danger of Data-Driven Instruction, the author, Susan Newman provides ineffective uses of data-driven instruction. The author highlights the use of worksheets, spreadsheets, and teaching to the test strategies as weak time consumers that detract from the active learning and classroom engagement. Data-driven instruction is a tool to guide education to increase student performance with researched based practices, rigorous teaching modalities, and differentiated individualized instruction.

Data-driven instruction means teaching needs to be based on data. The No Child Left Behind Act holds schools and districts responsible for student’s achievement, which implemented schools to collect, store, and manipulated data to modify the instructions. Teachers are held responsible for student reaching their goals. The teacher is able to show improvement by using the data that is collected. In attention, the teacher is about to use the data to show improvement. The data could also be used to modify instructions. The teacher is able to use the collected data to modify instruction to meet the students’ needs. For example, if the teacher is collecting

Richards, we discussed how the teachers within our school study the data of each student. She explained that data needs to be collected for all interventions and that it is very important to have at least six to eight weeks of data. The intervention should have specific target skills and goals. Student goals should be created so that they can have quantifiable data. For example they should be written as “Jimmy will read 40 out of 46 sight words” instead of “Jimmy will increase his reading skills.” Also the goals should be created so that the target is something that is attainable in a six to eight week intervention period. Many teachers create an intervention binder or folder for their students to collect data in. The school district I am in uses a form that has the goal, skill, date of intervention, data of progress, and other components on it so that teachers use a uniform data sheet that can be understood by everyone (H. Richards, personal communication, March 16,

All of the data can be extremely confusing to teachers and can lead them astray. Therefore, as Blankstein points out the, “No. 1 priority was for school communities to start with the “purpose” of the data” (164). Without understanding the true purpose behind the data or what the data can tell about a student there is no true reason for collecting it. Therefore, the real work, as mentioned with collaboration, comes after the data is collected. The use of data can drive instruction and promotes intervention or enrichment for targeted students to become more successful, but only if there is a goal in mind when the data is collected. Also, as Blankstein mentions, data should come from different sources, be relevant in relation to the school’s mission and vision, and must be consistent (174-175). By having data from a variety of sources, the scores can paint a clear picture of each individual student rather than relying on just one snapshot at one particular moment in time. This seems crucial considering how students’ lives often interfere with testing and how teachers are critical of assessments because a student is pigeonholed based solely on one test on one day. By curating data from multiple places, over a span of time, in a way that is relevant to the students, teachers can have a better picture of each student and more importantly, how to grow that

Coming from the middle school perspective, middle grade classrooms must focus on challenging and engaging lessons, student driven activities, and assessment-centered classrooms. Although assessments have been given a negative connation (just test and move on) in my building, effective assessments allow middle school teachers a way to create an instructional classroom where differentiation and accommodation can take place throughout the learning process. This process can be supported by data driven instruction with the use of external and internal

The data provided can provide a comparative analysis for states, districts, schools, teachers and parents to use as a measurement of a student’s knowledge at the time of testing, which can benefit the learning and assist in using the information to identify areas of concern in the students learning. The data can be one part of the whole looking at the student and monitoring for areas of weakness and strength in the students’ academic studies. Additionally, these tests provide a system of accountability and data collection. Which applied in this framework is useful as a tool to evaluate students’ progress, identify gaps and what an intentional teacher could use to assist student education (Alber, 2017). An additional use of the standard test information, suggested by Alber (2017) is to use the information to assess how you can group students in a way to promote and guide classroom learning and teaching, optimizing differentiation in the classroom. Instead of using high-stakes standardized tests to determine effectiveness, which has the potential of educational systems being influenced to spend more time teaching to the tests, versus teaching individual students according to their need, time devoted to using the gathered data more efficiently could occur. Such a shift would minimize

I agree with the statement "Leaders need to use data responsibly and habitually for it to be useful." I would like to believe that all teachers collect some type of data as way of evaluating student success and progress. Using data responsibly involves not prejudging students’ abilities based on prior indicators. However, many students are ability grouped based on their FSA scores. My wife and I have advocated at our school that FSA scores should not determine who’s class you’re in at the elementary level. Middle and high school maybe, but not at the elementary level. Another issue is the collection of non-academic data to determine future success. We should always deter and refuse to participate in the grouping of students based on

The people that should be at the presentation include Vicki Nguyen, senior sales associate at Alta Data, Mike Smith, regional sales manager at Alta Data, product manager at Alta Data, Bethany O’Meara, chief purchasing officer at Burtell, Jon Aaronson, head of research and development at Burtell, and Brad Alexander, chief financial officer at Burtnell. Vicki has important executives on Burtell’s purchasing team with their main concerns on her mind, while knowing that Brad Alexander is the crucial decision maker to convince that investing in Alta Data is worth it.

Data is always the best resource for trying to improve student achievement. The data will help guide continuous improvement of a plan. There are four types of data that will be beneficial to any team during the planning phase of the school improvement process.

The objective of this chapter is to describe the procedures used in the analysis of the data and present the main findings. It also presents the different tests performed to help choose the appropriate model for the study. The chapter concludes by providing thorough statistical interpretation of the findings.