In summer data institutes in New Jersey, school practitioners were immersed in learning about the different kinds of analyses they could conduct using their LinkItI benchmark assessment system. The newest structures in the system were designed to make it easier to find the answers most helpful to teachers and administrators.
In the presence of so much and such varied data being available and the paradigm shift in how teachers historically have planned lessons, we gain perspective on the size of the challenge in listening to how Richard Elmore captured the dilemma facing schools “Most people who currently work in public schools weren’t hired to do this work, nor have they been adequately prepared to do it either by their professional education or by their prior experience in schools”
In spite of little under-graduate or graduate level preparation for teachers and administrators in using data to plan instruction, schools are providing the resources to acquire a repertoire of essential skills. In-service educators are learning to use their data to identify gaps in their curriculum, to identify areas where the rigor needs to increase and to identify inconsistent expectations for what mastery level performance looks like. They are learning that collaboration across leadership teams and use of evidence in teaching teams trumps teacher isolation and benefits the entire learning community as achievement levels rise and gaps between groups narrow for the first time ever. So teachers in schools are getting it!
While districts and schools are engineering the changes that need to happen, and practicing teachers are finding a new freedom in working together to pinpoint learning challenges from their data, principals are acutely aware of the loss of power when an experienced data using teacher leaves the ranks. That realization prompts exploring new conversations when interviewing candidates for staff position openings.
Interview questions are now designed to surface how much a prospective candidate understands about diagnostic, benchmark, and formative assessments and then how to use this information to influence lesson planning, grouping, and coordination across specialists.
- How would the candidate identify learning needs and design instruction to meet those targeted needs?
- What day-to-day strategies can be used to monitor student understanding?
- How capable is the candidate using reporting systems to enter data from classroom observations and assessments?
- What do they know and understand about how to create useful reports?
- Do they understand what could be learned from a student’s historical data or the trend for any cohort of students?
Janna Davis and Vicki Wilson, principals at Homer Elementary in Ada, OK, share that when they pose questions like these to prospective teachers and are met with blank stares, they know these aren’t the most desirable candidates for an opening. The teachers in their school routinely analyze diagnostic and progress-monitoring data to target small group and individual instruction. They are accustomed to seeing turn around in student results within six weeks.
In this situation would interviewing teachers with some previous classroom experience have the edge or is it possible that a newly graduated teacher might present a solid foundational understanding about the importance and use of data in planning instruction? Are schools of education ahead of the curve on preparing teachers to incorporate the use of data into their work as teachers?
What’s happening in the teacher preparation pipeline?
To understand the degree to which teacher preparation programs are responding to the changes in the field regarding the use of data by assimilating data literacy into their courses (or are part of a forward vanguard) we can glean some insights from a survey conducted by WestEd’s Ellen Mandinach and Edith Gummer at the Kauffman Foundation. They surveyed 808 teacher preparation programs representing the full range of types of institutions (Mandinach and Gummer, 2016). The survey results are a strong indication that in both stand-alone courses or when integrated across other courses, schools of education are including foundational knowledge (about data and data for instructional change) for students. It isn’t 100%, but getting closer. And by the types of courses offered we can infer that teacher preparation programs recognize that the use of data by educators is not what we learned in Statistics 101 (which might be the biggest contributor to teachers’ fears of using data).
To get a perspective on what it takes to move institutions of higher education into adopting new paradigms, we could look at parallels in how teacher preparation programs began to integrate emerging technologies in the late seventies and eighties. It was a long, slow, painful transformation and many would argue that the transformation hasn’t fully occurred even in 2016.
Today, the confluence of several factors is accelerating the pace and scope of course-offering changes related to data use or data literacy for pre-service education. These factors include changes in teacher standards, requirements for certification, and the addition of topics on exams required for licensure. All converge to influence the scope and pace of change. Of course, the practical experience and knowledge of the faculty designing and delivering courses must be factored into the change equation.
Our appreciation of the enormous task before schools of education and why it may not just be the addition of a new course, expands as we study the definition of teacher data literacy and to analyze a construct attempting to illuminate the relationships between skills, beliefs, and processes that are intertwined when teachers use data to focus and refocus their work.
WestEd, working with the Michael and Susan Dell Foundation and the Data Quality Campaign have hosted several advisory meetings to unpack the current state of data literacy in pre-service education. They interviewed school education faculty and created case studies to help define what this new professional practice is and what is being done to prepare teachers with data analytic skills and experience.
The Dell Foundation and Data Quality Campaign provide a useful definition for what it means to be data literate. Data literacy reaches well beyond looking at reports, and requires far more than one early release day exercise. Administrators and those responsible for providing professional development for in-service teachers can use the definition and diagram to create a roadmap of the work to be done in order to contruct a collaborative culture of ongoing data use that leads to student achievement growth.
Case studies created by WestEd and the Dell Foundation and my own experiences in the field as Director of Using Data Solutions, offer further evidence into the changes occurring in our schools of education (https://www.msdf.org/blog/2016/01/training-data-literate-teachers/). On opposite sides of the country, two schools provide mature examples of schools of education where data-driven decisions are informing their programs, and helping them continue to define their understanding about what new teachers need to know and be able to do.
On the East Coast, Adelphi University on Long Island began by examining data about their graduates. Where were their graduates’ strengths and weaknesses on the New York State teacher exam? Additionally, faculty took apart the New York State teacher standards. Informed by both of these sources, they mapped backwards to determine where existing opportunities in their course of study were and if they needed to consider entirely new courses.
On the West Coast, Western Oregon University also began by investigating data about their graduates beginning with data about who was in their teacher preparation program.WOU’s belief is that they must connect the student who begins to prepare for a career in teaching to real world practice and ultimately to their future students performance. Is our teaching producing learning? WOU faculty describe their Teacher Work Sample as the crux of their program. Beginning with examining context data from the students’ in their field experience classrooms, in order to more fully understand their learners, WOU students develop an assessment plan beginning with formative data that is the start of a road map connecting the curriculum and learning goals to student learning.
In Oklahoma we see a third example of emerging practice about how a teacher preparation program that began as a Normal School, is preparing students to use data to plan literacy interventions. Dana Jordan, an instructor at East Central University in Ada, OK and formerly a fifth grade mathematics teacher at Homer Elementary School in Ada, requires her students in her Diagnosis and Remediation in Reading course to collect data for a group of struggling readers at Homer Elementary School. The undergraduates do an analysis of the data and plan a targeted series of lessons based on what the formative assessment revealed about students’ needs. Their intervention lesson plans must include plans for what data the pre-service students will collect as they teach the lessons in order to monitor the progress of the elementary students toward the learning goals.This hands-on course experience is proving effective. Homer Elementary students made strong gains in 2015-16 and these aspiring teachers, many of whom will teach in small rural schools, are fully prepared to learn from their students’ data.
While schools of education deepen their own understanding of the where and how to insert teacher data literacy skills, there are other developments that may actually overtake the pace of change. Data warehouses and reporting systems have made great strides in designing tools more in tune with cycles of teaching and learning, thus elevating the information most useful to teachers. Smarter applications make it easier to collect and analyze more than just student assessment results.
Smart Tools Painlessly Support Sophisticated Use of Data
The widespread use of electronic grade books, strongly aligned benchmark assessment systems and report generators that provide analytics more aligned to the critical questions teachers want to ask, are reducing the high hurdles and frustrations experienced by teachers and make it easier for them to assimilate the practice in real time, not dependent on seat time in a course. The common symbols and menu layouts that support our use of smart phones, tablets, and ATM machines have increased our familiarity and comfort levels with applications that no longer require a course to operate.
Variables That Bring It All Together
Schools that are beginning to recognize the great priority of providing time for teachers to collaborate, analyze data and plan instruction together are beginning to represent the norm. When these schools successfully create schedules and resources to support that professional learning time, veteran and new teachers alike are raising the questions most in need of answers. They know the data they need and when they get it, they have a keen sense of whether it’s valid and reliable. What we need are policy makers who are as data literate.
Reprinted by permission of the Publisher, From Ellen B. Mandinach and Edith S. Gummer, Data Literacy for Educators: Making It Count in Teacher Preparation and Practice, New York: Teachers College Press: Copyright ©2016 by WestEd. All rights reserved.
Data Literacy A Working Definition
Data Literate Teachers:
- Define “data” broadly to include standardized test data as well as broader academic, socioeconomic, situational, behavioral and environmental data that affect student performance.
- Understand how to identify and apply critical grade-level standards in the context of individual students’ needs.
- Prioritize and validate relevant student data as it relates to learning and standards mastery.
- Develop high-quality informal and formal assessments in order to collect usable data on students’ progress against those standards.
- Administer assessments on an ongoing basis to monitor student understanding.
- Develop responsive lesson plans and differentiate instruction based on assessment and other contextual data.
- Use data-informed insights to communicate student achievement and needs to students and their families.
- Use data appropriately, knowing what conclusions can be drawn from what types of assessments.
- Understand that, although data is important, data alone does not define a student. Empathy and relationships matter.
Michael and Susan Dell Foundation and the Data Quality Campaign