This class was a great extension of my school’s already in place PLC teams and great use of data. I felt that my school did a great job in the use of data and that this course would help me see the ways in which we used data effectively and might show me some small ways we could improve. The activities listed in the Data Coach provided me a better understanding and insight in my school’s Data Support Specialist role. At the same time, with this understanding and insight to support her in her role at our school and further guide others in direction for change.
The most valuable field experience in this course was the Data Overview. It represented project-based, authentic learning at its best. It made me aware that in addition to avoiding personal bias in my interpretation of data, I have to develop the skill of choosing the right data to interpret in the first place. In creating this project, I began further aware of how the use of data is important and the correct interpretation of the data. As my school district and state moves to teacher compensation and school success based upon student growth percentile developing this project around a 3 year cohort allowed me to gather, view and interpret a group of students and how this data is vital. The data reflected a clear picture of what our school’s success and where we needed to improve across the district and state to close achievement gaps.
While I believe our school is very successful in our PLC Data teams and using data to improve instruction and learning there is still room to grow stronger. It is important after review data whether it be state assessments or our school’s common content assessment clear Action Plans must be developed. These require time and to be effective time must be allocated to review, analyze, discuss, and conclude the right direction. I hope to work further with our Data Support Specialist to training the faculty deeper in seeing data as a means to improving data instead of as a way to judge teachers would allow for more positive teacher acceptance to the topic of data analysis.
Christa Evans Heath