Each year just before summer break, students across the country settle into their desks to take a series of standardized tests. While these end-of-the-year tests can serve a specific purpose, they do not offer insight for teachers eager to know how and what their students are learning during the school year.
According to Tonya Moon, professor at the University of Virginia School of Education and Human Development, teachers who take advantage of data that originates from their classroom over the course of the school year have an opportunity to make instructional pivots that help students succeed.
“Teachers have a class full of students, few of whom learn the same things at the same time in the same way,” said Moon. “The question we’re asking is: How can teachers use classroom assessment data to differentiate their instruction throughout the course of the school year to better meet the academic needs of their students?”
Differentiated instruction provides a framework for re-designing classroom instruction and assessment to place individual students at the center of learning. It reflects both the art and science of effective teaching. An important part of differentiated instruction is understanding what students have learned, what they are learning and what else they need to learn. Classroom-level data collection and interpretation are effective tools in answering those questions but require a unique set of skills.
We connected with Moon to learn more about what classroom data is, how teachers can best use it and how the School of Education is training future teachers to arrive in classrooms ready to use assessments to better inform their teaching.
Q: Can you describe what you mean by classroom-level data?
It is important to understand what we mean when we say classroom-level data and how this type of data fits into the larger space of data that schools and districts collect on a routine basis. Classroom-level data originate from formal or informal assessments and learning activities that students engage with on a regular basis (e.g., daily) and that are directly tied to a teacher’s instructional goals for a given lesson or unit. These data can provide two powerful sources of information about teaching and learning: 1. What was taught well and what needs improving and 2. What students learned and how learning can be improved.
Classroom-level assessments stem from an intentional, systematic process that is directly tied to instruction and provide information needed to adjust teaching and learning while they are happening. They are a type of formative assessments, or assessment for learning, that inform teaching as it happens.
Assessments of learning, or what we call summative assessments, are given at a particular point in time to inform the teacher about student learning relative to the content standards. Summative assessments can happen on both the classroom-level or at the state level through interim or year-end standardize testing, for example.
Q. How do teachers connect the data they’re collecting with their instruction?
It is well documented that this is the place where using data to inform instruction breaks down with many educators.
It is helpful for educators to improve their data analytic and interpretation skills and widen their conception of what data are. However, translating data interpretations into actionable instructional plans requires a different set of knowledge and skills.
For educators to successfully use data to inform their instruction, it requires a deep understanding of the content area and how that content develops in students. It requires an understanding of the methods of teaching, having a repertoire of instructional strategies, and being able to align powerful instructional strategies to what the data reveal about students. Finally, it requires an understanding of where students are developmentally relative to the topic under study.
This breakdown between data analytics and instructional planning is why my colleagues and I focus so much on formative assessment practices and connecting those practices to data-driven differentiation. Ultimately, our hope is to get away from a one-size-fits-all instructional approach, something that, in the end, rarely “fits” any student.
Q. Why isn’t this practice more common across classrooms?
While the use of data in service of student learning appears in federal and state legislation and is part of many educator licensure programs, it is well documented in the literature that both teachers and education leaders struggle to comprehend and interpret data, both of which are key components to linking data to instructional changes.
Given the breadth and depth of knowledge and skills required to effectively use data for instructional improvement, it is unsurprising that the majority of educators struggle with data use. Consequently, the use of data for real instructional improvement has been rarely documented in practice.
Q. How does this classroom-level data relate to other data being collected by schools, school divisions or even states?
Knowing the purpose of the data helps define the usefulness of the data for classroom instruction. Assessments and learning activities that produce classroom-centric data can be a powerful driving force for instruction by informing a teacher of what students have mastered and informing both the teacher and students of areas for growth. It can also help the teacher know what needs to be taught, when it should be taught, and how it should be taught. And it can inform the teacher on where instruction was successful and where it was less successful.
Aside from yearly or end-of-course accountability exams, districts often collect data from interim assessments or common formative assessments that are typically given on a set schedule, often quarterly, and that provide data on how well students are tracking for upcoming state accountability tests. These types of data are most often used for the evaluation of particular educational programs, revisions that may need to be considered to curricular materials, or for budgeting purposes concerning staffing, programming, etc. These types of data typically provide very little information on what students need on a day-to-day basis.
Q. How is the School of Education and Human Development preparing our students to collect and use this classroom-level data when they become teachers?
Students in the secondary Master of Teaching program take a semester-long course devoted entirely to classroom assessment that is designed to provide them with foundational knowledge and skills in classroom assessment and data literacy. Some of the Teacher Education program faculty are also working collaboratively across courses to better connect the assessment course to the methods courses that students take. Part of these efforts is to better prepare our students in making direct connections from analysis of student data to their instructional planning.
I think there will be several opportunities for the program faculty in the upcoming semesters to continue to collaborate and prepare the students for starting out their teaching careers using data to inform their instruction. And, of course, their skill set will continue to strengthen as they gain more teaching and assessment experiences.