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Analyze the instruction practice in three schools

In recent years, several high schools have adapted a new way of guiding their students in what is known as data driven instruction. Here, an educator uses measurable goals and observations to develop quantifiable data that is later employed to determine the academic progress of a student (Mertler 2014). The three major data categories employed in data driven instruction so as to improve reading and writing instruction are demographic data, disciplinary data and student learning data.

Hallandale Sr. High School’s faculty employs data driven instruction in several ways. The faculty is concerned with the performance of its students as well as making sure that the students are participating in extra curricula activities. The school’s demographic data is well distributed and there are numerous clubs and activities that promote the all-round development of the students.

Miramar Sr. High is known as an “A” school. The school’s faculty has successfully achieved this by the successful implementation of data driven instruction. With this, student’s participation and performance in activities is impressive as well as academic performance throughout the year. Disciplinary actions are strict and this has helped the school gain good reputation for its disciplined students.

South Broward Sr. High has employed data driven instruction to beat Miramar Sr. High, Hallandale Sr. High and other schools in Florida as having the best mix and range of extracurricular activities as well as having the most socio-economical and ethical diversity.  The school’s performance academically is above average.

One can simply never go wrong with data driven instruction. Among its many advantages is that schools make informed decision from data gathered over a period of time and analysed in a way as to provide the best solutions possible to difficult situations (Latta & Wunder 2012). However complex it is, data driven instructions prepares students well for analytical thinking. This should come as a welcomed strategy for avoiding “shoot first then ask questions later” kind of scenarios. Students therefore learn to understand the consequences of their actions before irrationally acting upon them.

Data-driven instruction seeks to abolish poor decision making procedures in schools and I believe that it does so very well by the time-consuming quantitative research process undertaken before making decisions (Mertler 2014). With data-driven instruction, wrong doers can rarely hide from mistakes. With the right questions asked and wise decisions made over time, accountability is a virtue that everyone must uphold.

 

References

Mertler, C. A. (2014). The Data-Driven Classroom: How do I use student data to improve my instruction? United States: ASCD.

Latta, M. M. Wunder, S. A. (2012). Placing Practitioner Knowledge at the Center of Teacher Education: Rethinking the Policies and Practices of the Education Doctorate. Charlotte, North Carolina: IAP.

Mocombe, P. C. (2001). A Labor Approach to the Development of the Self Or Modern Personality: The Case of Public Education. United States: Universal-Publishers.

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