Education / Applied AI

Adaptive Learning Engine: Bayesian Modelling of Learner Proficiency

Client Education and institutional training

Jungroo AI built an adaptive learning engine that goes beyond a single test score. Bayesian networks estimate each learner's proficiency in real time, Markov decision processes choose the best next step, and gaps in earlier concepts are found automatically.

The challenge

Training, education and compliance programmes often rely on static tests that produce a single score. They miss the order in which people learn, and cannot tell which earlier concept is causing a mistake.

The solution

Jungroo AI built an adaptive learning engine with four parts:

• Bayesian Proficiency Model: Bayesian networks infer each learner's proficiency across a knowledge map, updated with every response.
• Optimal Learning Paths: Markov decision processes choose the next activity for remediation and mastery, based on live interactions.
• Prerequisite Gap Detection: The engine traces mistakes back to the earlier concepts that cause them.
• Proficiency Dashboards: Visual dashboards that show each learner's growth and the gaps across a group.

The impact

Impact