|By Keith Cawley||
|August 5, 2014 11:15 AM EDT||
Behavioral economists theorize that "when presented with many options and little information, people find it difficult to make wise choices." This is the root of the movement to incorporate Big Data into the classroom. By compiling student data from an early age, we are able to better understand learning processes and identify issues, ultimately resulting in wiser, more informed decisions. Now when a teacher threatens that "this will go down on your permanent record," they really mean it.
The widespread adoption of tablets and devices in schools lets us track key performance indicators like how long a student hovers over a question before answering, how digital activity during a homework assignment relates to their understanding of the subject matter, and therefore identify what lessons were most and least successful. Publishers receive feedback regarding textbooks, based on length of time students spent on certain chapters and their overall grasp of the subject matters, so the books can be revised easily and often.
Skeptics argue that using this data will turn students into numbers in a dehumanized system where their personal information is practically public and teachers are replaced by machines. A premature overreaction perhaps, but it's these serious concerns versus the potentially astounding benefits that have us all wondering what our own digital trail of breadcrumbs would have revealed and how Big Data can make its way into the classrooms of the future.
Effective data use lets teachers pinpoint how specific initiatives impact a student's future successes immediately, instead of relying on yearly standardized testing to gauge their students' progress. Nationwide analysis would generate far more detailed and accurate comparisons of school districts, than disparate data that can easily be seen out-of-context.
The time and energy alone we put into ensuring children receive a good education seems to increase at triple the rate of inflation. Each year things get a little bit more competitive, and more expensive. Parents start saving for their children's college education at birth, if not sooner. Four year olds are "interviewing" for acceptance into Pre-K programs which begin the college prep they'll endure throughout their next 13 academic years. Yet despite all of these efforts, many capable students find themselves utterly unprepared when they reach freshman year of college. In 2013 only 71.9% of those freshman returned for their sophomore year and a mere 52.6% will actually graduate from a four year university within five years. Faced with hundreds of majors to choose from and classes that all sound the same on paper, students are overwhelmed and many end up spending extra time and money making up for poor decisions they made early on.
Many college campuses are testing the use of Big Data, including Arizona State University (ASU) and Austin Peay University in Tennessee, to help students make better choices when it comes to their education. At ASU, freshmen are required to declare a major early on. After this, eAdvising (a digital education platform) tracks the courses they take and the grades they receive, to ensure they remain "on track" to graduate in four years. The roadmap feature displays required courses for the entire four year degree timeline, frontloading key courses so that the students can determine early on if the major is not the right fit. Even then, the program will suggest alternate routes based on the student's interests and past successes. If a student fails to maintain course requirements or their grades for two semesters in a row they are deemed "off track" and required to choose a new course of action.
Austin Peay developed a similar program which gives students suggestions on classes that they have the highest chance of success in, based on their past performances. Recommended courses are presented using the familiar star ranking system, much like you would see on Netflix. The goal is to take a decision that involves hundreds of variables and break it down into actionable advice. Students are aware of the course requirements for their majors but often there are multiple choices that will fulfill that one requirement. The algorithm pools the student's grades, high school GPA, and ACT scores along with data from other students who have taken courses in the past, then uses the data to predict the courses in which you are statistically most likely to succeed.
Will these intuitive programs result in a generation of students who are more focused because they spent less time and money paying for mistakes they made during college, or will it end up crippling college grads by essentially making tough decisions for them? It will take years to know the answers to such questions, but the use of business intelligence in education is quickly becoming the norm.
Have you experienced the effects, positive or negative, of data use in the classroom? What do you think the future of Big Data in the academic world should look like?
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