If you've not been in a K-12 school in a while, you may not know a new buzzword associated with learning, called data driven education, or individualized, differentiated or personalized learning. What this means is that students are tracked, via data, on everything they do, including commuting too and from school. Millions of pieces of data are compiled about their study habits, what they read, their interests, hobbies
Proponents of the program say that the data has made it possible to understand the student better, gain knowledge of how the child learns and guide the student in ways they could not before. The data also help to see potential learning opportunities for the student they couldn't assess in the past. The more they know about the student, the better the educators can help the student achieve.
The system is mostly automated. Teachers fill in student data into a state information system as usually once a day. A statewide aggregator extracts that information daily and generates weekly and monthly reports.
This isn't new as schools have always compiled basic data on students such as grades, attendance, disciplinary behavior. Now, these records are are digital and because of that, schools can better spot trends and patterns.
Companies, like Pearson PowerSchool, one of the main organizations, gathers data on children all over the world. It uses a web-based information system that follows 13 million students in all 50 states as well as 65 countries.
PowerSchool uses a learning software program that claims to collect data points on how a child learns every day. Yet, there are laws that allow parents to limit what student data is collected and who can see it.
What does this mean for parents? Who has this data and how is it being used?
The protection of this information limits the data and in some cases, parents can "opt out."
What does this mean for California?
In an article by Adam Stone in Government Technology, Stone said the data collected on students gives California educators a 360-degree view of a student’s performance.
He suggests that instead of combing through individual statistics on performance, attendance and test scores, educators can find and sort what they are looking for instantly. It's a way to measure how a student is learning and if they need to make adjustments to their program.
However, in a study conducted by Stanford University Institute for Research and Education Policy and Practice, there are questions about how well this program is doing and whether the investment in public schools are accomplishing the state’s desired goals
Through the No Child Left Behind Act (NCLB), the federal government required different kinds of information about teachers, students, teachers, districts, schools, and states. This information put new pressure on California to design a new integrated, longitudinal information system.
The Stanford study finds that California is lagging behind most other states in developing its education data system. At this time it is not capable of assisting policymakers to understand how schools are doing and how resources can be used most effectively to increase student learning.
California just started in the past few years to collect data. It emphasized collecting it in a discrete, disconnected data “silo” that address reporting and monitoring requirements, but the data process in California is not usable for the new more "robust" systems. The data collection process can't be integrated for analyses that can guide policy and program improvement.
The Stanford study concluded that California needs to work on several issues in terms of its funding, leadership, and the accessibility of data if it is to have access to a data driven education program.
Further, the study concluded, it is unlikely that the state can build a data system with the capability to support the policy and funding without long-term support from California leaders.
The study referenced California’s history of mild support for the data system development and raises questions about whether the state will make the ongoing, long-term commitment to communication and training that appears critical to the success of complex data systems.