Using Data to Improve Learning
While the prospect of tailoring learning to each individual student has brought a great deal of attention to personalized learning as of late, what could be discussed more is the role that personalized learning has to play in using data to improve learning (popularly known as data-driven instruction). An educational approach from the era of the No Child Left Behind Act, data-driven education strives to use concrete numbers derived from student test scores to inform teachers’ approaches to classroom practice.
School administrators and teachers are increasingly being held accountable for student achievement, and data-driven decision-making is designed to give them the information they need to implement and monitor action plans that will increase students’ academic success. While much of the data are derived from standardized testing, many school districts also rely upon the real-time data provided by adaptive learning programs to inform instructional decisions.
There’s no doubt that the data-driven approach to instruction is controversial – some people are advocates of this educational practice while others are staunchly opposed. As with any approach to education, there are two sides to every story. The question is, what are the pros and cons?
PRO: Helps students meet academic standards
While students have always been expected to meet certain academic standards in order to move onto the next grade level or graduate from high school, data can indicate to teachers whether or not students are actually reaching those goals at more useful intervals of time. It can also show educators which areas may need improvement, thereby focusing instructional time and personalizing learning. With the introduction of the Common Core State Standards, many students around the country will be asked to meet even higher academic expectations, which also come with their own version of online testing. The questions on these tests can guide teachers as they write curricula designed to help students meet the standards.
CON:Sometimes data come before students
Because this approach to education relies so heavily on data to inform decisions, there is the danger of test scores taking precedence over students. In other words, when teachers are held accountable for the scores that their students get on a variety of standardized tests, they may become more concerned with teaching content than actually ensuring that students learn and understand material that will help them be successful when they graduate.
PRO: Provides accountability
Many advocates of data-driven education believe that teacher accountability is a good thing. After gathering data, school administrators are able to reference concrete numbers when attempting to determine how effective the curriculum and instruction have been. Analysis of test results can identify some of the challenges that students are facing and help principals pinpoint opportunities for professional development or curriculum improvement.
CON: Testing can take up class time
Data-driven education requires a certain amount of standardized testing, and administering these exams can take up valuable class time. In addition, teachers often devote a period of instruction to ensuring that students are prepared. However, teachers who want immediate access to data related to whether or not students are grasping the concepts that will help them be successful can use adaptive learning programs to analyze student learning in real-time and tailor instruction accordingly.
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