How “Big Data” Can Improve Educational Outcomes

Our news media frequently inundates us with study upon study of how the American education system trails most other advanced countries in math and science, graduation rates, or some other metric of education performance.  I disagree strongly with most of these studies for reasons I won’t go into, except to say that many of their researchers cherry-pick data and then use the most alarming findings for media sound bites.  But, let us take these studies at face value for a moment and assume their findings are correct.  What then do we do about our “failing” education system?

Big Data to the Rescue

Education is a treasure trove of data; only recently have schools been making use of this data to improve outcomes in education, and much of their work to date is only scratching the surface.

Schools collect data on several attributes: a student’s progress in each subject over time; the teacher for each subject; the instruction styles for each teacher; the student’s likes and dislikes; whether students drop out or graduate; demographic, neighborhood, and socioeconomic characteristics of each student; teacher tenure and training; and so on.  Consider the ways schools might use such data to improve educational outcomes:

  • Identify factors that drive subject failure or school dropout, and predict which students are at highest risk of either event, and intervene;
  • Enhance professional development of teachers by identifying areas of their teaching styles and methods that more most and least effective;
  • Identify the types of environments under which individual students perform best and tailor their curriculum accordingly;
  • Identify ineffective curricula and instruction and direct school resources to ones that are more effective;
  • Determine whether underperforming students are clustered within a particular classroom and drill down to determine whether the teacher needs additional training or resources, or if he/she has a larger number of students with special needs; and
  • Predict whether a student is more likely to succeed in a college-preparatory or vocational environment and tailor his or her curriculum accordingly.

This list is far from comprehensive. Keep in mind, however, just as with business situations, educational institutions must use “Big Data” judiciously in trying to enhance educational outcomes; the constraints under which the schools operate, especially those governing the use of student and teacher data, must still be taken into account before a school undertakes a data mining effort and again before taking action based on the findings from that effort.  Getting buy-in from parents and other community stakeholders is essential to ensuring that a school’s data mining efforts are successful.

As I said earlier, I don’t believe a lot of the studies about the performance of U.S. schools.  If their findings are indeed true, then “Big Data” can be quite useful in identifying and rectifying problem areas; if the findings are not true, then the data mining effort can make the performance of our schools even better.  But as with any organization wishing to use data mining, school administrators must decide what problem or problems they want data mining to solve and follow the steps as described in my last blog post.  The rules, caveats, and benefits of “Big Data” apply just as much to public sector industries like education as they do to for-profit industries.

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