Data, what is it good for?
My daughter’s answer, when I recently asked her this question was, “to keep track of things.” Great answer for an 8-year-old, but unfortunately it captures a still-too-common view that data is for measuring and tracking, rather than informing and guiding. Only using data to measure and track is like putting a car in drive while navigating with the rear view mirror.
Data has always been a part of education; recently, the concurrent and self-reinforcing trends of standards-based reform and technological innovation are yielding a more useful application of data beyond mere measurement. Indeed, the instructional information now available to teachers to guide the educational process in real (or near-real time), as well as to evaluate the performance of various products, services, and methodologies, could well be an inflection point in the modern educational system.
In a bit of edu-irony, the move to standardize content standards, assessments, and expectations led to the current efforts to truly personalize education. The long-overdue focus is to hold the same high expectations of students to be college or career-ready, able to master a core curriculum at a sufficiently rigorous level.
The emphasis in personalized learning on the place, path, time, and pace in student acquisition of knowledge of skills is directly due to the intentional, daily use of high quality and timely data.
This personalization of learning is enabled primarily through organized models of blended learning that systemically collect and report out high-quality data generated through formative, interim, and summative assessment tools, while providing teachers effective training and ongoing support in the analysis and use of data.
By incorporating the explicit use of data to guide and inform, through the smart use of systems of support and appropriate (often technology-enabled) tools, a number of schools and school systems are maximizing outcomes in blended learning environments such as FirstLine Schools, Aspire Public Schools, and Rocketship public charter schools.
Another effective use of data, although not in a blended learning setting, is DC Prep, which provides for actionable data to guide teachers and has master teachers whose whole job it is to help classroom teachers use data in the classroom.
What all these examples have in common is the building and instituting of a culture where teachers consistently look first to data to guide instruction. This is time- and energy-intensive to do well, but is more important than the technology.
The differentiated learning – through the sophisticated use of data – that digital content allows can certainly provide educational value by connecting students’ work online to support classroom teachers and providing actionable data on student progress and achievement to assist in targeting interventions, enrichment, and support.
This data “feedback loop” can be a powerful tool in the hands of trained educators, one which has been shown to accelerate learning and student outcomes in remarkable fashion when working smoothly and consistently in the hands of teachers trained to leverage its potential. The strength of the opportunity for students depends on the details of how schools implement their model and content, that the model and content be well matched for the school’s educational needs, and how well schools support their teachers in doing so.
The use of data to inform decisions about student readiness for new content, adjust the sequence or difficulty of content, modify instructional practice, and understand outcomes has been a quiet revolution in some schools and districts. By examining the practices and outcomes of some of the schools and systems mentioned above, there is hope that the list of those embracing this use of data will continue to grow and produce results.
The word ‘data’ is the plural of datum, which in Latin means “something given.” Data is a tool that when used both strategically and tactically, can give incredible insight, power, and results to students, teachers, and schools.
It is possible to identify four Levels of Data Use, from relatively simple to increasingly complex: Collect results; Analyze trends; Plan instruction; and Personalize learning. When done effectively, these levels of data use are embedded in a continuous feedback loop.
Schools and teachers need to start at Level 1 (Collect), but often get stuck there, or at Level 2 (Analyze), where analysis paralysis can set in. Some, though, get to the next levels with great results.
An example of highly-effective Level 3 (Plan) data use is DC Prep, a District of Columbia charter school network where 80 percent of students at every DC Prep campus are eligible for free or reduced-price meals. Administrators and educators make good use of a customized data system, Lumos,that provides teachers with “accessible, accurate, and actionable” data on student academic progress on formative and summative assessments.
This approach to data use is working for DC Prep schools, as they routinely score among the highest schools in the District of Columbia. On the DC CAS assessment, 81% of 4th-8th grade students scored proficient in reading and 92% proficient in Math, 56% of whom were at the advanced level.
DC Prep’s use of their Lumos system exemplifies the use of the first three levels of data utilization. Using data at Level 3 to plan instruction for a class can be powerful, but going deeper by using technology in a structured blended learning model that develops and supports teachers is Level 4 data use: personalizing learning.
Effective blended learning models use data in clearly articulated ways, such as creating data feedback loops of on- and off-line data to better target intervention, enrichment, and support, and to consistently group and re-group students based on readiness and mastery of standards-based content and skills. Schools must systemically support teachers with the use of data, not simply rely on individual teachers to crunch all the data, especially from different digital content providers. Blended learning allows teachers to use data to continuously modify their instruction in straightforward, sustainable ways.
For many schools and districts, using data across all four levels in a coherent blended learning model implementation is a radically new way to approach teaching and learning, but it is one that has seen success.
A school district making strong use of Level 4 data is Horry County Schools (HCS), an economically diverse district in South Carolina.
HCS uses data from many sources, including various content providers, as well as NWEA’s Measures of Academic Progress (MAP) and state assessments in its blended learning settings to differentiate classroom instruction and measure outcomes.
HCS provides a dashboard for both teachers and for students, giving them comprehensive data on student progress. Teachers use the data to develop lesson plans with small-group differentiated instruction, collaborative work, and individual practice and review of concepts using online content.
HCS facilitates professional learning communities and collaborative planning sessions for educators and administrators to analyze and discuss data on student achievement and progress to take meaningful action to improve outcomes.
HCS is seeing results. For middle schools, which are the furthest along with blended learning and Level 4 data use, growth scores for math and reading increased more than in those grades/subjects not using blended learning and Level 4 data. Two HCS middle schools were named National Blue Ribbon Schools in the category of Exemplary High Performing Schools, meaning they were among South Carolina’s highest achieving schools. Overall, in 2014, HCS made gains in each grade and each content area, except science, on South Carolina state assessments (SCPASS); the percentage of HCS students scoring “Met” and “Exemplary” is higher than the state at all grades in all areas.
Leaders and teachers should embrace using all four Levels of Data Use in a feedback loop as a fundamental part of teaching and learning to produce engaging, effective educational outcomes. The schools highlighted above show that the effort to weave data into the fabric of existing school processes and structures, if well-planned and executed, can have a measurable impact on student learning.
Written by Doug Mesecar