New for Back-to-School 2025: Our Personalized Mastery Learning system for MMA and MRA has been significantly improved with an AI-enhanced rebuild that makes the system faster, more accurate, and more responsive. Students now begin using each program with a faster and more accurate placement test, then seamlessly move to more accurate personalized learning path that drives more efficient skills growth, as students now stay in their Zone of Proximal Development (ZPD) longer.
Adaptive learning, also known as adaptive teaching, creates individualized learning experiences based on a student’s real-time, in-game performance. Rather than one-size-fits-all, My Reading Academy (MRA), My Math Academy (MMA), and My Reading Academy Español (MRA-E) continually gather information for each student and provide a custom learning experience that adapts as they learn.
Our Personalized Mastery Learning System provides the right content at the right time for each student. The system ensures that students have a strong foundation based on Architecture of Understanding.
Here are the benefits of our adaptive system:
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Initial Placement Activities: When new students start playing, we know very little about them and therefore cannot precisely recommend lessons to these students. To overcome this challenge, our optimized system quickly assesses each student through a series of placement activities. It gathers data as the students work on these activities, evaluates their skill level, and places each student at the most appropriate starting point on their personalized learning path. New for 2025-2026: our placement testing is faster and more accurate than ever.
- Grade Level Affects Placement: It is important to note most students will be placed within their grade-level curriculum; some may be placed up or down a grade level based on testing; no students will be placed more than 2 grade levels above or below the grade they are rostered. So make sure that grade level is accurate for any student you are concerned about.
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Personalized Learning Paths: The system recommends which game to play next by selecting three targeted options in a game hub for students to choose from. The system uses each child’s game-play performance to decide what they are ready to learn next, ensuring every student gets a customized learning path. The student performance history and the behind-the-scenes "node map" structure are used to make these recommendations. A node map is a network of games and their prerequisite relationships. Students move forward and backward on this map as they demonstrate more skills or knowledge, or need additional support. As students complete activities their placement is regularly reassessed, and they may be moved ahead or back within the curriculum based on the skills they are able to demonstrate.
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- New Faster Adaptive Adjustments: Activity selection is now more responsive and able to make greater leaps across the map when a student's knowledge has substantially changed since the last time they used our products.
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- Dynamic Scaffolding and In-Game Customizing: The program scaffolds to successfully complete a problem before allowing students to move on. It reduces the cognitive load of the task, allowing the student to focus on key concepts. The system also customizes datasets inside games. For example, when a student replays a game, we give them a different dataset compared to the first play-through. This helps us ensure that students don't just memorize the correct answer to pass a game.
Adaptivity Requires Completion
Teachers should be aware that to get the best results from My Math Academy or My Reading Academy, it’s important for students to complete every activity—even ones that feel too hard.
Sometimes, students may be given activities that are beyond their current skill level. When this happens, they might choose to cancel out of the activity rather than try it. But skipping the activity means the program doesn’t get the information it needs to adjust. Without that signal, the same kind of activity may keep showing up.
That’s why it’s important for teachers to encourage students to play through all assigned activities, even if they don’t know the answer or get things wrong. Struggling with a skill provides a valuable signal to the system. The program uses this signal to adjust the difficulty and guide the student to the right level.
Let students know: It’s okay not to get everything right!
When students play—even if they don’t succeed—the system can respond appropriately by:
Lowering the level if needed
Providing more practice
Offering additional supports
By contrast, if a student exits an activity before engaging with it, the system has no evidence of struggle and will assume the activity is appropriate.
Key takeaway for teachers:
If a student says something is “too hard,” that’s a cue to encourage completion, not cancellation. The program can only adapt if it sees the struggle.