As classrooms celebrate Black History Month throughout the month of February, we wanted to share a collection of assignments created by teachers in our community.
As English language arts teachers know best, teaching students to read is multi-faceted and incredibly complex. One of the best professional development (PD) experiences I have had was Close Reading led by Doug Lemov and the Teach Like a Champion team. At this PD they emphasized and re-emphasized the importance of text selection when teaching students to read. Specifically, they shared what they have coined, “The 5 Plagues of the Developing Reader” and the need for teachers to choose texts that target these five plagues. By exposing students to the five plagues in a setting where the teacher and peers can dialogue and analyze the texts together, we are then teaching students how to comprehend and analyze complex texts on their own
We began the “Data Series” blog posts emphasizing the importance of daily independent practice, then explored 5 concrete steps to ensure your lessons are aligned to state standards, and most recently the 3 types of meaningful data that will help increase results in your classroom. In the latest post, the second type of data discussed was daily classroom data: data that a teacher collects during the lesson in one class period. This type often helps determine who is on track for mastering the daily objective and who needs immediate remediation. The game-changing strategy used to collect data daily is where we will end our “Data Series” posts. Educators, allow me to introduce you to Aggressive Monitoring.
“The goal is to turn data into information, and information into insight.” ~Carly Fiorina, former executive, president, and chair of Hewlett-Packard Co.
Raise your hand if you use intuition and a gut feeling more often than concrete data to make decisions.
If you didn’t raise your hand and you use data to make all of your decisions, then skim the rest of this post and leave a reply at the bottom with a how-to guide so that we can all become more data-driven humans.