Using Data to Revise Plans
This post provides a deeper look into the ideas of the continuous improvement cycle, one of JumpRope’s Core Values.
Reflecting on my work has always been an important part of my teaching practice. When I first began teaching, and for many years beyond that time, my reflection largely relied on qualitative data -- observations, interactions, conversations. It also relied on my own rough interpretation of the quantitative data in my (hard copy) grade book. Teachers, schools, and school districts now have available to them all the qualitative data they have always had, but they also have easily consumable quantitative data through resources like JumpRope, Google, and myriad other online sources. As we consider steps in the continuous improvement cycle, it makes sense that we use all of the data available to us to increase our effectiveness. The InTASC Teaching Standards, written to “outline what teachers should know and be able to do to ensure every PK-12 student reaches the goal of being ready to enter college or the workforce in today’s world. name practices,” specifically names the following practices for teachers
6(c) The teacher works independently and collaboratively to examine test and other performance data to understand each learner’s progress and to guide planning.
7(d) The teacher plans for instruction based on formative and summative assessment data, prior learner knowledge, and learner interest.
7(f) The teacher evaluates plans in relation to short- and long-range goals and systematically adjusts plans to meet each student’s learning needs and enhance learning.
In short, the InTASC Standards require that we engage with the continuous improvement cycle as we move through the arc of the school year and also as we move from one year to the next. We need to look at our data so we can be better teachers and our students can be better learners.
The smaller of the data sets are those that come from classroom formative and summative assessments. Those assessments should give us information about students’ attainment of targets, indicators, and ultimately standards, but they consider students in relatively small groups and instruction across short periods of time. These are the data we look at to know, at a classroom level, how to group our students for further targeted instruction, or if a series of lessons has effectively prepared students for an assessment. They help us guide our students to reflect on their own achievements and set goals for areas they are still working on. These are the data of the day-to-day and week-to week. They help us to be nimble and show us where we need to be flexible, spend more time, revisit topics, pick up or slow down our pace. Here is an example of how JumpRope helps teachers collect data for habits of work and learning as well as academics.
We typically look at larger data sets (think school district, whole school, grade level, etc.) at some natural endpoint. That endpoint is sometimes the summer, but it might also be once the results of a common assessment are available, or at another strategically chosen time. This examination of data is intended to help us see trends across schools or teachers. It helps us see which of our outcomes, standards, or indicators were met and which ones were not met or met inconsistently. When we see standards that were not fully met, we can ask ourselves some important questions:
Is this standard at the right grade level?
Are we well calibrated around the rigor or demands of this standard?
Is the language of the standard clear to teachers and students?
Are there pre-requisite skills that need to be addressed/added to standards at an earlier grade?
What do teachers emphasize and deemphasize in instruction? Are we “lite” in some way with this standard?
In what ways do we provide opportunities for students to demonstrate their understanding of this standard? Could that be improved?
If achieving better results with a particular standard is a priority, how will we support teachers to do that?
Looking at a larger data set from a district or school level is deeply important for several reasons. As noted above, these data give us insight into student learning across the institution. That insight helps us make curricular decisions around the standards we address, the professional development we provide, and the resources we use. Examining the larger data set and sharing conclusions and actions with our colleagues provides a model for them to do the same in their own work. If the district or school clearly values the use of data to reflect on its successes and shortcomings, it will be easier for teachers to embrace the same in their classrooms.
Considering qualitative data and quantitative data at every level is an important step in the continuous improvement cycle. Arguably, it is central to that process. When we look honestly at the strides we’ve made toward helping students meet the expectations of the standards, we see what we have to celebrate. But more important still is uncovering the spots we still need to work on and developing a plan to make that work happen.
Council of Chief State School Officers. (2013, April). Interstate Teacher Assessment and Support Consortium InTASC Model Core Teaching Standards and Learning Progressions for Teachers 1.0: A Resource for Ongoing Teacher Development. Washington, DC: Author.