Seattle, Washington (PRWEB) April 23, 2014
The University of Washington’s Center for Game Science (CGS), today announced new research showing dramatic improvements in math mastery for K-12 students. During the “Washington State Algebra Challenge,” a one-week event that introduced algebraic concepts to students through a game-based, adaptive platform, students achieved an average mastery rate of 93 percent after only 1.5 hours of participation. Students from more than 70 schools across 15 districts joined in the challenge. Although the content was 7th grade algebra, this outcome was achieved by all participating classrooms across grades K-12, including early elementary.
“One of the biggest outcomes from the Washington State Algebra Challenge,” explains Zoran Popović, Director of the Center for Game Science and Founder and Chief Scientist at Engaged Learning, “was the fact that mastery of linear equation-solving was reached in 1.5 hours, not just by higher grades, but even in elementary school. More importantly, this mastery was achieved by practically the entire classroom, as opposed to just a few students. This is shockingly good, but we think we can do even better.”
CGS’ research is focused on optimizing the interactive experience and exploring how that impacts the best learning outcomes.
With funding from The Bill & Melinda Gates Foundation and Hewlett Foundation, and a partnership with Engaged Learning – a new not-for-profit K-12 company – CGS aims to leverage its five years of cutting-edge research and product development in dynamic learning content and adaptive learning to revolutionize school outcomes around the world.
“We’re using real-time classroom data and curricula that adapt to automatically optimize learning for each unique student and each specific classroom,” says Popović. “And our global algebra challenges totally involve students, maximize their persistence, and get nearly 95 percent of them to full mastery of material. That’s an extraordinary result, because most curricula today fail to capture enough student attention and achieve much lower student mastery levels.”
In addition, says Popović, “the adaptive nature of the game was instrumental to achieving these high results. Only a tiny percentage of people finished without requiring customized remediation. Some grades required significantly more effort and adaptation than others. The game was able to adapt in real-time to each student in order to maximize likelihood of mastery. Compared to the non-adaptive content, the outcomes improved by over 60 percent. These results are unique in today’s courseware environment.”
CGS organized similar algebra challenges in Norway and Minnesota, with further improved outcomes.
“In Norway, with a much larger student population, students solved almost eight million equations in five days,” says Popović. “Students were so engaged with their learning that over 42 percent of all work was done outside of school hours, almost doubling the Washington out-of-school times. It may be the first time ever that an entire country of school kids voluntarily spent that much time on learning outside of school.”
Continues Popović: “A unique methodology behind the game automatically used data from previous challenges to further improve outcomes for new learners. In the Minnesota challenge, for example, the game figured out how to increase the mastery percentage over Washington and Norway by an extra 1.5 percent. We may get even closer to 100 percent than we thought possible. We look forward to the outcomes in the Brazil Algebra Challenge, perhaps the largest K-12 intervention ever conducted, with potentially 42 million students participating.”
Solving an Intractable Education Problem
Engaged Learning and CGS have joined forces to attack what has been an intractable problem in K-12 schools for years – providing seamless, effective and adaptive education that is differentiated for each and every child, as well as every teacher.
“The Engaged Learning / CGS partnership offers a completely new solution for several key reasons,” explains Popović. “First, we turn existing curricular content into an infinitely adaptable version capable of true and unique specialization for each learner. Second, we analyze the enormous number of variables that affect student learning in real time. And third, we use this data to continuously adapt and personalize – not just curriculum, but the entire learning process and ecosystem of students, teachers and even parents.”
Current efforts to successfully personalize learning in a scalable manner through adaptive curricula have failed because they are:
- Constrained by the fixed courseware content, unable to scale up to the 10x additional student-specific content required to exceed 95 percent classroom mastery numbers; this ability to generate content to fill out the potential learning grid is a key factor and true differentiator between Engaged Learning / CGS and its educational competitors
- Limited to student problem adaptivity, rather than adaptivity of the classroom structure and on-the-fly teacher lesson adaptation
- Focused only on student mastery while ignoring deep-engagement adaptations
- Limited to intermittent adaptation improvement based on manual analysis of data, rather than real-time automatic optimizations with every new classroom data point
Providing a Breakthrough Solution
The Engaged Learning / CGS solution, on the other hand, offers a self-adaptive, curriculum-agnostic platform that continuously identifies and refines personalized pathways through digital courseware, games and other learning tools – pathways that optimize both engagement and mastery for each learner, as well as best outcomes for teachers and classrooms as a whole.
To achieve this, the platform can convert any paper or digital courseware product into a parametric version capable of generating a virtually infinite number of problems within the original courseware design. By generating new content, and not just re-sequencing existing content, the platform can create and optimize pathways for virtually every learner. This ability to generate content to fill out the rest of the potential learning grid is a crucial differentiator. Using proprietary data analytics and machine learning, the platform continuously identifies ideal courseware parameters that achieve the best outcomes for a given student, and a given teacher, and then adapts them to optimize learning at every moment within the learning process in any classroom, school or school district.
In addition to creating and optimizing pathways for student learning, the platform recommends teacher interventions, instructional strategies and pivots, and other elements of the ecosystem that have been shown to be successful in similar classroom situations. As a self-adaptive system, the platform’s adaptation improves with each additional teaching and learning experience captured. And, as the platform continuously and automatically adapts based on real-time data, it accelerates the potential rate and degree of engagement and mastery in every learning opportunity.
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