A New Model To Help Learners Succeed In Math: Just-In-Time, Adaptive Remediation
Concurrent Session 5
Foundational math courses are an obstacle to student persistence and graduation. American Public University System is addressing this challenge at scale with Just-In-Time Adaptive Remediation, providing learners with personalized guidance and scaffolding to address their individual knowledge gaps. The program has positively impacted student success, with results to be shared at the presentation.
APUS’ Just-In-Time Adaptive Remediation framework uses the features and functionality of the adaptive learning engine from Realizeit to deliver students targeted guidance and scaffolding on concepts not yet learned through additional personalized content and practice exercises. The system uses machine learning to recognize the student’s strengths and weaknesses, serving material to the student and alerts to the faculty based on each student’s unique learning needs. The framework allows students to succeed where previously they have not.
The data to date, which will be shared in the presentation, illustrate that the Just-In-Time framework is making a positive impact on student success in Math 110, with students demonstrating consistent, steady growth in mastery and progress throughout the course.
Through attending this presentation, participants will be able to:
- Apply adaptive learning concepts to online learning
- Review a framework for just-in-time remediation for adult learners
- Understand how the faculty role is enhanced using the adaptive engine dashboard
- Be able to apply the concepts and framework to your remedial courses