Can data-driven, adaptive learning make a real difference in achievement?

In a recent policy report by The New American Foundation, Promoting Data in the Classroom, Innovative State Models and Missed Opportunities notes that since the No Child Left Behind (NCLB) act was passed in 2001, states have been compelled to develop more sophisticated methods of tracking information, and every state as of 2012 has at least the foundation for a system. 

However, most states do very little to train teachers and administrators in how to use these data to inform and improve classroom instruction.  That’s beginning to change now, with a number of Blended Learning Certificate Programs now available through associations, MOOCs, and government programs, like the Blended Learning Institute, part of the New York State Department of Education iZone program.

Real-time data is most effective to meet student needs and state standards

U.S. Secretary of Education Arne Duncan, a proponent of data-driven decision making in education, urged at an American Association of School Administrators Conference, “If your data collection is not providing the information you need to drive continuous improvement in the classroom, see which best practices you can beg, borrow, and copy from districts that are forerunners in data management.”

In fact, research has shown that if curricula and instruction plans at every level—county, district, classroom, and individual students—are based on information gathered from data collection, the probability that students will attain desired learning outcomes increases.

For example, California has implemented the Electronic Learning Assessment Resources (ELAR) that outlines a specific process to utilize data to inform instruction in an effort to meet student needs, California curriculum content frameworks, and Common Core State Standards. It provides a roadmap that’s driven by continuous assessment to inform and implement instruction.

Data-driven decision making process/ELAR

 

elar-process-chart

Source: Electronic Learning Assessment Resources 


Summative and formative assessments

Oregon and Delaware, to name two other states, now have federally funded efforts in place to collect classroom data and to implement it fully to improve instruction. They’ve found that summative assessments are administered too late in the year to use data to course-correct. Other assessments, particularly more timely formative assessments, allow for adjustments to better support struggling students, while formative assessments evaluate students’ skills in mid-academic unit. These assessments may provide more valuable information to teachers because they assess students’ learning as it happens, allowing teachers to change their instructional strategies accordingly. The latest technology can help provide an even more effective way to collect data and meaningfully inform instruction.

Intelligent Adaptive Learning™ and continuous formative assessment

For many school districts, Intelligent Adaptive Learning that continually assesses, collects data, and adapts make a difference in deep math learning and achievement in support of standards, including the Common Core State Standards. With current reporting of student data and continuous formative assessment, it’s possible to find the root causes of problems schools and students are facing, rather than simply ‘treating the symptoms.’ Educators can also use the data to modify programs or approaches that aren’t working, and develop innovative models for after-school programs, like mSchool, and summer school programs, like SummerAdvantage USA.

The system can customize lesson pacing and presentation, and offer a pedagogical approach that’s most appropriate to the individual student’s learning style. As Intelligent Adaptive Learning simultaneously assesses and instructs in real-time, it also tracks the millions of data points that it collects to provide current reporting for teachers and administrators. This gives educators immediate and actionable insights into student comprehension so additional support can be provided exactly when, where, and how it’s needed.

Adaptive learning technology and the data it collects give students the continuous improvement and personalized learning experience that schools would like to provide, but may have difficulty doing as classroom sizes increase and budgets decrease. You can learn more about data-driven decision making and its implementation in the white paper, A Continuous Improvement Framework, Data-Driven Decision Making in Mathematics Education.

How do you use data and adaptive learning to boost math achievement? Let us know at mystory@dreambox.com.