Here’s a common misconception: scheduling is a task for spring and summer.
The reality is that late spring is often too hectic, while summer is too late to make change. To be more effective, school leaders should use the fall and winter to get smart about scheduling.
It’s important to use these few months before scheduling starts to become a data detective; patterns detected now can have a huge impact in the future.
Here are five suggested tasks to help improve your scheduling.
Do a Scheduling Debrief
Gather the scheduling team together and document what worked and what didn’t. Spend time talking about the pain points. (Refer to our sample scheduling analysis guide.)
The key to a successful scheduling season is having a plan. Learn from prior problems and document the causes. Celebrate what worked well, and develop a plan to protect it in future schedules. A scheduling debrief will help you set some goals for improvement and improve upon what worked.
Expand Your Use of Data
End-of-year grades and teacher recommendations are the most common data points used to place students into next year’s courses. But are they the best indicators of success, or are they just the easiest?
Use the fall to dig a little deeper into your data. You may find a new data point that is a stronger indicator of future success.
- Look at available common assessments. You may find that writing tasks or unit exams are better indicators of future success than the final grade. Expand your search outside the content area, perhaps an ELA exam in 10th grade is the best indicator of success in an 11th grade history class.
- Consider the strength of more holistic data points like GPA. Sometimes a single grade from a single grading period is not a strong indicator of student readiness. GPA or another composite data point may prove to be a better indicator of student readiness for a future academic workload.
- Expand beyond grades and test scores. Additional data points such as attendance, social-emotional indicators, and learning style inventories may improve the accuracy of data-centered placement decisions.
- Move beyond the binary in teacher recommendations. Allow teachers to provide more helpful feedback. Allow teachers to rate student readiness on a scale of 1-4, or describe a student’s academic, work habits and emotional preparedness as three discrete values.
Expanding the types of data doesn’t have to complicate the scheduler’s job. Use your data system to sort and group students. (In Illuminate, complex data can be tamed through custom reporting and On Track configurations.)
Help Your Teachers Take the Long View
You got all the students into classes, but did you get them into the right classes?
Teachers rarely get the chance to dig into the data of former students. Find data points from the first grading period that are good indicators of student success. Provide teachers with current data about their students from last year, and help them identify patterns.
Teachers crave the longitudinal data about their students, so use the fall and winter as time to reflect on the growth students have made after passing through a teacher’s class. Analysis of longitudinal data may spark conversations about placement criteria and inform instructional practices.
Talk Openly About Change
Don’t wait until May to discuss changing the bell schedule or common planning periods. Fall and winter are perfect times to when those ideas should be discussed openly.
Change can be unsettling for our teachers, parents or students. Start the conversations early so stakeholders have time to mentally prepare. Systemwide changes, like a new bell schedule or adding an intervention period, can have major impacts on the scheduling cycle. These ideas need to be discussed before the collection of course requests.
Find Your Pre-Built Controlled Experiments
Sometimes we have to move students between classes to make the schedule work. There are times when we schedule students in a way that creates a controlled experiment within your student population. With some smart tracking, you’ll find opportunities to test your placement criteria and the effectiveness of your instructional program. For example:
- You may have 46 students that qualify for a math support course, but you only have 28 spots. Eighteen students qualified for the program, but will not receive the course. You now have a control and experimental group. Select appropriate indicators of success, and track all 46 students. Did the 28 students in the support class show growth? Did they outperform their peers who did not receive support?
- Placement in an advanced math course requires a score of 90 points or higher on the math placement exam. This year, only 21 students qualified, but you need to fill the class to 30 students. So, you find nine students with the next highest scores on the exam and schedule them for the course. You now have an experimental group, testing the validity of that 90 point cut score. Perhaps 88 points on the placement exam was adequate all along?
A student-driven and dynamic schedule doesn’t just happen in the spring. The best instructional leaders know the scheduling cycle is a yearlong process. Fall and winter are the time to do your research and dig a little deeper into the data. Great leaders will use the start of the academic year to reflect and validate any scheduling decisions they made last year, and look for opportunities for improvement.
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