Module 8 Reflection

This week's material focused heavily on the importance of data-driven decision making. As a middle and high school social studies teacher and team leader, I had the opportunity to work with a team of administrators and educators to gather and interpret various types of student data including TVASS data, iReady data, and general data for all course assessments.  Not only do assessment data points allow me to best understand what prior knowledge my students have, whether or not I am effectively teaching students, at what rate students are growing over time, and what needs each individual student has, but also data analyses from all areas of study coupled with regular communication with other team teachers allowed me to implement cross-curricular lessons into my curriculum.  In particular, I worked with the science teachers extensively to creatively bring science concepts into the social studies classroom. In addition to individual data analyses, I worked with colleagues in PDs and PLCs to analyze student data as a grade level then use research to implement new strategies to meet the discovered needs. Most of this data was already processed through the testing software that was used to collect the data, so access and interpretation were relatively easy.

 Data -driven decision making is an important best practice in the field of education. However, as I mentioned in the discussion section of Module 8, I think some school districts are very narrow minded when it comes to types of data they use to make their decisions. Often times, they rely on standardized testing scores to determine student placement without taking the extra time to evaluate the student's work ethic. I think often times, school districts rely on quantitative data because it's way more time efficient and expedient; however, the decisions that we make using data impact the the lives of human beings. Therefore, quality data may not always be a composite or average score. 

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