According to a February 2014 policy brief from the Data Quality Campaign, the vast majority of teachers are not given the resources or training they need to make use of the wealth of student data they are collecting.
This can result in teachers who want to improve their data literacy but are not quite sure where to start. In this article, we will explore several ways for educators to quickly and easily blend learning analytics into the classroom routine and promote a data-driven culture amongst peers and families alike.
1) Turn Anecdotes into Metrics for Parent-Teacher Conferences
Make your parent-teacher conferences stand out with data-based innovations. Your parents will be thrilled to see charts and graphs of individual and class progress alongside supplementary notes and insights from teachers.
2) Identify Individual Coaching Opportunities
As exemplified in the preceding video, simple data analysis makes it easy for teachers to pick out specific areas of opportunity for each student and personalize instruction accordingly. By now, most teachers should have the tools to identify "at-risk" factors in time to act on them. Proper use of data and technology in this area can ensure that no students slip through the cracks.
After grades for the mid-term were entered into the Student Information System, Miss Jackson saw that three students had fallen below the early-warning threshold she had put into place at the beginning of the year. She pulled up her gradebook and drilled down to find that each of the students seemed to be struggling for a different reason.
Veronica has been performing consistently until a flurry of absences within the past two weeks resulted in poor marks on two writing assignments and the recently completed midterm. Miss Jackson decided that she would give Veronica a chance to catch up with the class through some added attention over the course of the next week.
Chase, on the other hand, had been skirting the line for most of the year, only falling below the threshold after a particularly poor showing on the test. It was time for an intervention, and Miss Jackson began brainstorming ways to match him up with one of her more proficient students for after-school tutoring. She knew he was passionate about his role on the football team, so she decided to have a discussion with the coach in order to work out a study program that could fit around his offseason workout schedule and help keep him eligible going forward.
James’ data showed a vast inconsistency between assignment and test grades. He was an active participant in class, but always seemed especially nervous when the clock was ticking. Miss Jackson made a note to compile some helpful test-taking resources to boost his confidence, including some practice exercises that he would be able to work on at home.
3) Try Out a New Approach
Most of us are wary about trying something new after we have grown comfortable with our existing routines. If we believe our methodology has been working for years, there often seems to be little sense in tinkering with it. More and more, we are seeing teachers step out of their comfort zone to try new techniques that have been suggested to them by others in their personal learning networks. Continuous, timely access to data allows these innovative educators to examine their results empirically and self-adjust as needed.
Mr. Romano, a high school chemistry teacher, has been urged by a few of his most trusted colleagues for several years now to try the flipped learning approach. He has never liked the idea of using his students as guinea pigs, but before the start of this school year, his district rolled out an advanced learning analytics system that will allow him to track his students’ progress against the Next Generation Science Standards and compare results to the previous year. With the knowledge that he can easily drop the flipped approach if his students show any sign of falling behind, he decides that the time is right to try something new.
After one month, Mr. Romano sits down to pore over the data from all of his course sections, comparing average progress against standards to the previous year. Not only do the charts seem to indicate that his students are about a week ahead of where he would expect them to be with the traditional approach, but he is also able to gain some insight into how the change has benefited his AP classes in comparison with his College Prep sections. As a result, he decides to make some slight adjustments to his approach for both and makes plans to reevaluate after the next interim assessment.
4) Aggregate for Self-Reflection
Great teachers engage in self-reflection all the time. Sometimes, it's as simple as pondering whether something could have been said differently in that first period conversation. Other times, it is driven by a question of a larger scope, like whether or not an assignment could have been structured differently to increase student engagement.
With the experience that comes from spending time in the classroom, these processes are often automatic and based on some combination of training and observation.
Data can fill the gaps in the self-reflection process by confirming suspicions and challenging personal beliefs. Regardless of how a teacher might feel about reducing students to mere points on a graph, the ability to analyze measurable goals outside the boundaries of observational bias is crucial to 21st century instruction.
Mrs. Potter has just completed her first year in her own classroom. All of the college classes and practicums in the world could not have prepared her for the highs and lows that she experienced, but she knows now, more than ever, that she chose the right profession. As part of her end-of-year routine, she decides to pull up some aggregate reports to determine areas that she might improve on in the year to come.
The data provides some useful insights for Mrs. Potter, including a direct correlation between sudden spikes in absences and lower average assignment scores. She makes a note to go back and review her calendar to determine how best to work around these problematic dates in the future. She is also able to identify a number of sporadic dips in overall performance and compare it to the curriculum being covered during those time periods in order to determine whether she could be presenting the material in a way that better sets her students up for success.
Mrs. Potter’s grade level is not subject to any standardized testing at the end of the school year, but her review of aggregate performance data is able to provide her with a more holistic understanding of her students’ achievement and progress than any test could hope to achieve. She saves the graphs to her computer with the intention of discussing her analysis with a mentor and obtaining instructional feedback in the areas where she might have missed an opportunity.
Data-driven instruction is a complicated and oft-misunderstood concept. For many, the use of data in the classroom is closely entwined with an overreliance on standardized testing, making it a lightning rod for controversy and criticism. The truth is, data can be a valuable day-to-day resource with or without standardized tests. Actionable information can be gleaned by reviewing metrics on attendance, formative assessments, and assignment completion rates, just to name a few.
Even in the most progressive data-driven cultures, analytics do not represent a substitute for qualitative observation. They merely act as a secondary resource to help teachers understand the big picture of their instructional efficacy, from the entire classroom all the way down to the individual student level.
With the right combination of support from peers, supervisors, and technology, data analysis can enable teachers to have an even greater impact on every student that walks through their doors.
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