The grouping algorithm employed by School of One assigns students a new lesson every day based on the student's most current learning needs. The algorithm actually learns the students' needs from the previous day's exit ticket. One of the learning styles or lesson types, Live Investigation, assigns students to me who are ready for whatever the assigned skill is. However, within that group, there are still varying levels of ability. I can see all of this on my data report and then I can group within my group. I call this micro-grouping.
During Personalized Small Group Instruction, I work closely with a small group of students while other students are engaging in activities independently at different stations. Based on my learning objective, I group my students differently for Small Group Instruction every day. Sometimes students are grouped homogeneously, according to specific needs, and sometimes they are grouped heterogeneously. This strategy, which is enabled by my station rotation blended model, allows me to spend individual time with each student on a regular basis.
A blended teacher’s personal mindsets shape his decisions as an educator. These mindsets influence general pedagogies, instructional approaches, and short-term decision making, alike. Check out how Aaron’s mindsets have helped to shape his blended instruction.
TOAST is an acronym that stands for "Time Owed After School Today." It's a very simple and non-punitive consequence that we implement for students who don't follow the rules: 1) Respect all people, property, and ideas; 2) Follow directions the first time; 3) Be prepared. I make it very clear at the beginning of the year that TOAST does not mean I'm mad at you or that you're a bad person; however, there are consequences for your actions that are not consistent with our community expectations. Paying with time and doing some community service or making a plan to change student actions have been effective ways to turn negative student behavior into a positive.