Big Data beckons policymakers, administrators and teachers with eye-popping analytics and snazzy graphics. Here is Darrell West of the Brookings Institition laying out the case for teachers and administrators to use Big Data:
Twelve-year-old Susan took a course designed to improve her reading skills. She read short stories and the teacher would give her and her fellow students a written test every other week measuring vocabulary and reading comprehension. A few days later, Susan’s instructor graded the paper and returned her exam. The test showed that she did well on vocabulary, but needed to work on retaining key concepts.
In the future, her younger brother Richard is likely to learn reading through a computerized software program. As he goes through each story, the computer will collect data on how long it takes him to master the material. After each assignment, a quiz will pop up on his screen and ask questions concerning vocabulary and reading comprehension. As he answers each item, Richard will get instant feedback showing whether his answer is correct and how his performance compares to classmates and students across the country. For items that are difficult, the computer will send him links to websites that explain words and concepts in greater detail. At the end of the session, his teacher will receive an automated readout on Richard and the other students in the class summarizing their reading time, vocabulary knowledge, reading comprehension, and use of supplemental electronic resources.
In comparing these two learning environments, it is apparent that current school evaluations suffer from several limitations. Many of the typical pedagogies provide little immediate feedback to students, require teachers to spend hours grading routine assignments, aren’t very proactive about showing students how to improve comprehension, and fail to take advantage of digital resources that can improve the learning process. This is unfortunate because data-driven approaches make it possible to study learning in real-time and offer systematic feedback to students and teachers (education technology west-1).
West sees teachers and administrators as data scientists mining information, tracking individual student and teacher performance and making subsequent changes based on the data. Unfortunately, so much of the hype for using Big Data ignores time, place, and people.
Consider what occurred when Nick Bilton, a New York University journalist and adjunct professor designed a project for his graduate students in a course called “Telling Stories with Data, Sensors, and Humans.” Could sensors, Bilton and students asked, be reporters, collect information, and tell what happened?
The students built small electronic machines with sensors that could detect motion, light, and sound. They then asked the straightforward question whether students in the high-rise classroom building used the elevators more than the stairs and whether they shifted from one to the other during the day. They set the device in some elevators and stairwells. Instead of a human counting students, a machine did.
Bilton and his graduate students were delighted with the results. They found that students seemed to use the elevators in the morning “perhaps because they were tired from staying up late, and switch to the stairs at night, when they became energized.”
That night when Bilton was leaving the building, the security guard who watched students set up the devices in elevators asked him what happened with the experiment. Bilton said that the sensors had captured students taking elevators in morning and stairs at night. The security guard laughed and told Bilton: “One of the elevators broke down a few evenings last week, so they had no choice but to use the stairs.”
In mining data, using analytics, and reading dashboards (see DreamBox) for classrooms and schools, the setting, time, and the quality of adult-student relationships count also. For Darrell West and others who see teachers and students profiting from instantaneous feedback from computers, context is absent. They fail to consider that the age-graded school is required to do far more than stuff information into students. They fail to reckon with the age-old wisdom (and research to support it) that effective student learning beyond test scores resides in the relationship between student and teacher.
And when it comes to evaluating individual teachers on the basis of student test scores, the context of teaching–as complex an endeavor as can be imagined, one that is only partially mapped by researchers–trumps Big Data even when it is amply funded by Big Donors.
Big Data, of course, will be (and is) used by policymakers and administrators for tracking school and district performance and accountability. But the seductive lure of mining data and creating glossy dashboards will entice many educators to grab numbers to shape lessons and judge individual students and teachers. If they do succumb to the seduction without considering the complex context of teaching and learning, they risk making mistakes that will harm both teachers and students.