data-based decision making
Data analysis and decision making occur at all levels of RTI implementation and all levels of instruction. Teams use screening and progress monitoring data to make decisions about instruction, movement within the multi-level prevention system, and disability identification (in accordance with state law).
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aboutData-based decision making is a process of collecting and analyzing data from a variety of sources to guide a range of decisions to help improve the success of students and schools. Today’s best educators use data extensively to define needs, set goals, plan interventions, and evaluate progress. Data-based decision making involves three important steps that help to improve the success of schools and students. Data is first gathered, reviewed, and analyzed to help educators identify priority areas that need to be focused on. By analyzing the data collected, educators can then form a hypothesis to decide how best to use the information. Basing educated guesses upon data is an important step to improving school and student success. Once priority areas are identified realistic goals are made and moving into action becomes the next step (Data Driven Decision Making, p.1).
The level of the system being addressed should determine when data-based decision are made. For an individual data-based decisions should be made daily or weekly, for the school monthly or quarterly, for the district three times a year, and for the state decisions should be made annually. Data provides educators with an overview of the strengths and weaknesses in a target area. When these target areas are identified, educators can prioritize their resources and professional development to produce more efficient and effective programs (Data Based Decision Making). data-based decision making and rtiData-based decision making plays a crucial role in Response to Intervention (RTI) and is instilled in all components of an RTI practice. In a tiered process, the first level of data collection is screening. At this level, data is used to make decisions about which students are at risk of their needs not being met. The data collected during screening helps educators determine the existence and significance of a learning or behavioral problem. It will also inform the school whether or not the problem exists as a result of the classroom environment or poor curricula design by a teacher. In tier II, progress monitoring gives educators data that can be used to make decisions about the effectiveness of interventions. Data is also used to make decisions regarding the fidelity of implementation. Decisions to increase or decrease levels of interventions within a tiered service delivery model are based on student performance data. Data-based decision making is critical in an RTI practice because it leads to appropriate support and strategic instruction for all students. Knowing why and what purpose data is being collected is imperative to an educator. When the purpose and intent of data collection is known, the data can be used to make important educational decisions throughout the RTI process (Data-Based Decision Making).
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