Data has been growing on a massive scale, in everything from business, engineering, science, entertainment, and policy, transforming the way we think about the world. On the education front, many initially viewed data as a disruption, and not an ally, to the classroom. And as the American higher-ed system has faced a myriad of post-recession challenges, such as shrinking budgets and increased competition, educators have had to rethink and reimagine what they do – including embracing the potential of technological “trends” like data analytics in the era of the digital classroom.
Check out four key facts behind the big data movement and its impact on education:
Big data is more than just another trend. Advances in education technologies have enabled teachers and administrators to gather more data than ever before. Data is definitely here to stay; however, as with many other things, data isn’t always definitive. The concept of being “data informed” rather than “data driven” is probably the best way to consider data’s role for teachers. Big data offers unique value for K-12 and higher ed in the way of realistically measuring and assessing the learning process in real time, so that classroom learning and instruction can evolve with the times.
Big data offers value in assessing complex skills. Conventional assessments are often infrequent or constrained by design, relying on multiple choice and standardized exams. The progress in digital assessments have allowed more direct review of relevant and authentic performance. For instance, many MOOCs are able to capture data on how students solve complex problems or assignments as part of their regular coursework. This richness of information can provide a better picture of problem-solving skills and collaborative activity, which had served as a launching point for the analytical tools that came later to capture similar insights on student learning.
There’s a positive shift towards a problem-solving based approach. Big data can offer the freedom for teachers and students, breaking away from the standardization model in favor of a more creativity or problem-solving approach, with the focus on individualized learning. As the student body continues to evolve and diversify in the coming years, the chance to identify and solve learning problems with the help of data will become critical (e.g., identifying at-risk students).
“Little data” has a big payoff. While big data offers to better inform decisions on improving classroom practices, some advocates of analytics are urging teachers to not overlook the value of “little data” – the information collected every day on each student’s academic progress – to personalize learning. Big data aims to predict trends; for example, Amazon recommends similar books based on a customer’s purchase history. Little data can help the student learn something about their reading habits, while enabling the teacher to identify their strengths and weaknesses and develop a personalized lesson plan. Even with all the data in the world, educators won’t be able to change student outcomes, unless they have a way to connect with data on a personal level.
