Engaged Learning Joins U. of Washington’s Center For Game Science
Seattle, WA (PRWEB) May 20, 2014—Engaged Learning– a new not-for-profit K-12 company – announced that it is partnering with the University of Washington’s Center for Game Science (CGS), whose research is focused on the optimization of the interactive experience and how that impacts the best learning outcomes. The new partnership is backed by funding from the Bill and Melinda Gates Foundation.
Starting in 2014, Engaged Learning will help build upon the most compelling and transformative research from CGS and bring the new end products to the global K-12 market.
Goals and Objectives
Based on five years of research and product development in dynamic learning content and adaptive learning at CGS, Engaged Learning and CGS are now harnessing the power of real-time classroom data and curricula that is both generative and adaptive across subjects to automatically optimize learning for each unique student, teacher and classroom.
“Engaged Learning and CGS are determined to transform school outcomes around the world,” says Zoran Popović, Founder and Chief Scientist at Engaged Learning, and Professor of Computer Science and Director of the Center for Game Science. “We believe that our expansive data and breakthrough technology can dramatically improve student engagement and learning, teacher effectiveness and courseware efficacy everywhere they’re deployed.”
Solving a Critical Problem
Engaged Learning and CGS have joined forces to attack what has been an intractable problem in K-12 schools for years – providing education that is differentiated for each and every child, teacher and classroom.
“The Engaged Learning/CGS partnership offers a completely new solution for several key reasons,” explains Popović. “First, we can turn existing static curricular content into an infinitely adaptable version capable of true and unique specialization for each learner. Second, we can then 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.”
Improving Adaptive Learning For the 21st Century
Engaged Learning and CGS are redefining the notion of adaptive learning for the 21st century.
Adaptive Learning 1.0 is essentially the ability to re-sequence pre-existing, finite curriculum or courseware based on a student’s progress/success. The students cycle through the same content until an assessment indicates that they are ready to proceed to a pre-determined next section.
Unfortunately, however, that pre-existing content is inadequate to address the needs of all learners – no matter how it is sequenced. And there are three central reasons for this:
- Research has shown that some students need as much as 10x the content or practice to reach mastery as other students. No fixed or finite curriculum addresses this hugely variable need of learners to achieve mastery. Moreover, this extra context needs to be highly specialized for each student to optimize engagement, mastery and persistence.
- Any single expert-generated curriculum only addresses a fraction of the paths a learner may take or exercise to learn a concept. Every path that is left out, by definition, decreases the degree to which that curriculum can be optimized for all learners. The paths by which some students will learn best will not be included. When you choose between a few fixed options, you limit, rather than expand, learning paths.
- Even when including the variability of student engagement, persistence and learning dimensions, the optimal results will not be reached. This is because an effective teacher-led learning process can drastically improve collective classroom learning and engagement. But to date, no curriculum delivery mechanism is capable of real-time adaptation of teacher activities that lead toward optimal student outcomes.
“To optimize for every type of learner, you have to fill in the rest of the grid,” explains Mullin. “You have to provide access to 10x the relevant content, and the ability to sequence it, to cover virtually every possible pathway for learning. This is problem generation, not just adaptation. And when you have Generative Adaptation, you can then fill in the grid of potential learning paths and optimize for all learners.”
Delivering a Next-Generation Solution
The Engaged Learning/CGS solution 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, paper or digital courseware products can be converted into parametric versions capable of generating a virtually infinite number of problems within the original courseware design. 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.
This adaptation includes adjusting sequences of content, interventions, recommended instruction, blended classroom configurations and other elements of the ecosystem determined to optimize a student’s learning process. As a self-adaptive system, the platform’s adaptation improves with each additional 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.
For more information, see full press release.