Personalized Learning: The Moment is Now

Personalized learning is one-on-one instruction between a teacher and student, and is a key to transforming rote learning to comprehension and mastery of subject matter. But in today’s public schools, that option has become increasingly unrealistic—although it is needed more than ever, particularly to raise national math scores. For example, less than half of the 2012 graduating class that took the ACT college entrance exam scored at the level that predicts earning a “C” or better in math as freshman in college.

Budget cuts and larger classes:

At the same time as we need even more personalized learning, class sizes are growing. According to a late 2012 Brookings Institution study Class Size and Student Outcomes, Research and Policy Implications schools in all 31 states were projecting a combined $55 billion in shortfalls for their 2013 budget year. Large by historical standards, these numbers are dwarfed by the combined $538 billion in shortfalls that states had to close in the previous four years—an average of $135 billion per year. The response has mostly taken the form of deep spending cuts. These cuts have consequently led to larger class sizes, or new legislation that threatens to take away class size limits from coast to coast.

For example, In New York City, as the teaching force has declined through attrition, the number of elementary school students in classes with 30 or more students has tripled since FY09, according to a New York City Public Schools report published in March 2012 by City Council member Brad Lander of the 39th District, and those numbers are predicted to rise even higher with new proposed budgets

How we can personalize learning with fewer resources:

Faced with these challenges, how can we bring greater personalization to more elementary math students with less money and fewer teachers? We must leverage technological tools that make the most of both money and time. One of these tools is math software that delivers up-to-the-minute data, and adapts according to that data to intensely personalize the math learning experience for the individual student.

Intelligent Adaptive Learning with ‘in the moment’ assessment:

DreamBox Personalized Learning is enabled by Intelligent Adaptive Learning™ to continuously monitor, assess and respond to every interaction at the time it occurs. As Nigel Green, Director of Personalization for DreamBox Learning, Inc., notes, “The very next thing that happens for the student after they provide a response is based upon that specific response combined with an assessment of what they need to see/hear/experience at that moment. No delays. For example, if a student makes the same error multiple times, he or she may get different responses from DreamBox, depending upon the current context, operation and achievement level — even within the same lesson.”

Learn about DreamBox personalized learning right now:

DreamBox lessons are designed from the very moment of initial design to be intelligently adaptive, and run on a platform that constantly analyzes student actions, resulting in tens of thousands of calculations and data points for each student, every hour they are working within DreamBox. This allows the platform to inform lesson response, while at the same time fine-tuning difficulty, context, and any support scaffolding needed by that student at that moment. The result is steady guidance and ‘natural’ mastery that gives students confidence and improves achievement.

Want to learn more about DreamBox’s intelligent adaptive learning? Take a moment to download our latest personalized learning white paper.

Nigel Green

Director of Personalization @DreamBox_Learn | Developer of Continuous Assessment and Adaptation | Former Teacher | Professional Musician | Bellevue, WA