Kidaptive Launches ALP Lite to Accelerate Personalization of Educational Applications
The Company Is Seeing Early Traction for the Platform in Countries like China (Zibot), India (IxamBee), and Mexico (YouLeader)
Kidaptive, Inc. announced the release of ALP Lite to help developers of educational applications personalize learning experiences and understand the efficacy of their products. ALP Lite makes it easy to enhance educational products with powerful features like content recommendations and score prediction. The platform also enables rich psychometric student profiles. ALP Lite is a managed service that trains, modifies, and deploys Machine Learning models. Customers receive results via an Application Programming Interface (API) and only pay for what they use.
Through its Adaptive Learning Platform (ALP), Kidaptive has pioneered the use of Machine Learning for recommendation and personalization in education for more than five years. Traditionally, access to ALP’s capabilities has required a deep integration. Today’s general availability of ALP Lite provides a major step toward putting the power of Kidaptive’s experience in Machine Learning into the hands of educational app developers with minimal integration efforts.
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“Building accurate models for recommendation and score prediction that work across many different types of learning environments requires expertise in both learning science and data science,” said Dr. Josine Verhagen, Senior Director of Psychometrics and Data Science. “At Kidaptive, we are using AI to democratize access to the latest learning science; it’s almost like having a learning scientist analyze every study session.”
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Launched in beta in early 2019, ALP Lite has gained traction in two different segments: K-12 education, where the Recommendations feature is vital for teachers to customize lessons; and test prep, where developers utilize the Score Prediction report to tailor educational paths. The goal of both features is to increase engagement and optimize learning.
