top of page
Computer Keyboard

Analysis

Applications

Mostly focused on K-12 Math and Sciences(ALEKS, DreamBox, Aida, Knewton, etc), early languages (ex. Duolingo), and test prep (ex. Blueprint for LSAT). 

What differentiates products?

With quite a few adaptive learning technology on the market today, what makes each of them different? ​

  • User Interface - simplicity, interactivity

  • "Content is King" - the teaching content, tips

  • Algorithm - what factors are considered in personalizing the experience

Benefits For Teachers

Data-driven class management

Data from adaptive learning can help spot unclear concepts and lesson speed for the class. 

Better monitor student progress

From student mistakes and progress, teachers can more easily identify what students need help with. 

Saves time

Adaptive learning systems help save time from class preparation, administrative tasks, and feedback/evaluation. The extra time can be used for professional development and increase interaction with students.  

13h

per week of a teacher's time can be saved by using  technology

(Bryant et el (McKinsey), 2020)

Benefits & Limitations of Adaptive Learning

Benefits For Students

Learn at your own pace

Adaptive learning systems will adjust content type and difficulty and revisit concepts if needed. Students will no longer be left behind. 

Focused and personalized learning content

Content that targets weaknesses and suits student learning styles. This also helps keep students engaged and saves time from practicing what they already know.

Improved academic performance

Many studies has shown improvement in grades with the use of adaptive learning systems. Human-machine competitions also show that AI teaching can be more effective in raising scores. 

Immediate feedback

Timely intervention from adaptive learning systems help students see their mistakes right away and gives tips when they are needed. 

84%

of students using adaptive technology indicated moderate to major improvement in grades

(McGraw Hill, 2016)

Mobility Perspective

  • AI-assisted adaptive learning systems can be easily accessed on mobile devices. Most systems are browser-based, but systems are becoming increasingly mobile, with tablet compatibility (DreamBox, ALEKS) and mobile applications (Duolingo, Aida). 

  • In areas where teaching resources are limited or nonexistent, adaptive learning systems can be used to provide personalized, quality education, giving students a chance to develop important skills. By reducing the need for a physical classroom, this data-based approach is making learning more mobile. 

  • The current downside to adaptive learning from a mobility perspective is the need for a device and connectivity. 

  • In the future, perhaps data collection can happen in a more mobile method as well instead of only on the learning platforms. This would enable more informal mobile learning. 

bottom of page