Schooling Big Data: How Data Analytics Help Teachers & Schools
By Lloyd Marino
It wasn’t so long ago that the most advanced data system in most of America’s classroom was a gradebook with numbers written in pencil seen only by that teacher.
Today, educators’ ability to access complex computerized data has grown alongside the rise of the standards and accountability movement. Now big data helps teachers and school administrators track student progress and find the best ways to reach and teach each one. Through data analytics on student test scores district and state officials are able to learn which teachers are most effective and which schools to target for reforms.
Big Data Educates the Educators
Big data can help educators determine which students are at the most risk of dropping out and who most needs extra help and support. For instance, Spokane, Washington has created an Early Warning System that compares individual students with past dropouts’ records to predict future high school dropouts while they are still third graders. With this information, schools can intervene sooner and gauge programs’ success at moving potential dropouts back on track. According to Superintendent J. Alvin Wilbanks of Gwinnett County Public Schools (Georgia) in an IBM report, “Data analytics can help us both identify the child and create a better picture of who they are, what areas they’re deficient in, and point to things we can do differently.”
Big data also can help teachers guide students to an enjoyment of reading. Each year, nearly 10 million students take Accelerated Reader quizzes on books and articles they read—334 million quizzes in 2014. By tracking this data, teachers can determine how well students understand what they read and if they should recommend easier or more challenging readings for each student.
However, any analysis of data on children encounters a special risk. Parents who think nothing of allowing a grocery store to track their buying habits grow more fearful when schools share data on their children, even for beneficial reasons. When inBloom, a nonprofit organization, proposed partnering with schools to collect student data to help schools improve student achievement, parents protested, ultimately shutting the organization down.
Value Added Models with Big Data
Anyone who has ever spent time in a classroom recognizes that not all teachers are equally effective. But how can administrators sort out the wheat from the chaff? If schools judged teachers just by their students’ test scores, than teachers with the smartest students would appear better than the rest.
The solution is value-added models that use advanced data analysis to predict each student’s score on state standardized tests based on previous tests and how similar students have performed in the past. While still controversial, this method has been adopted by many urban districts, including Chicago and New York City, as a key component of their teacher evaluation systems along with more subjective measurements such as principals’ observations.
Depending on district policies, these metrics can influence teacher tenure decisions, determine performance pay, shape professional development practices, and even, if teachers fail to improve, lead to dismissal of low performers. Researchers are comparing teachers with high and low value-added scores to try to discover what makes the high scoring teachers more successful and to judge the effectiveness of various school reforms.
How data is shaping the future of schooling
The classroom of the future could engage more adaptive instruction in which computerized systems allow students to advance at their own pace with appropriate vocabulary and questions that grow more complex as students learn more. Teachers could receive daily progress reports comparing each student’s progress with the average for the student in the past and for the class as a whole, as well as other classes in the school, district, and/or state. Already, the Rocketship charter school network is pioneering a hybrid model in which students spend part of the day with teachers and part with adaptive software.
In the future, schools can go beyond data on attendance and test scores. A network of micro-schools in New York and California called AltSchool is experimenting with using cameras aimed at each student’s face to measure facial expressions to see which teaching techniques and sequence of activities create the greatest student focus and the highest levels of achievement.
Someday soon, big data will link students’ performance in college and careers back to their schools, enabling schools to alter instruction to better prepare students for their futures. Computerized instruction tied to common standards could measure students’ performance on each standard, alerting teachers when students fail to understand a concept so the human can explain it more.
Atari and Chuck E. Cheese Pizza Time Theatre founder Nolan Bushnell, who in 2013 launched BrainRush, a website that allows users to play, create, and share learning games that adapt to an individual’s learning level, says that all this recent technological innovation is heralding a much needed change in the way we think about and approach education. As he told Forbes Magazine, “The school systems have adopted a factory system of education, which says pretty much one speed, one complexity. As a result, there’s one person being taught at the right speed and the rest of the kids are bored or lost… The computer allows you to adapt to each student’s particular skills and speed. Instead of ABCDF, all kids end up totally mastering the subject. It’s a big change. What it really does is it levels the understanding gap in the factory model with really impressive outcomes.”
Ultimately, big data can play an expanded role all of this, individualizing education, keeping all students on track for graduation and success in college and careers, and helping schools work with their teachers to become more effective.
Image By: John-Mark Kuznietsov