Cognition-Enhanced Machine Learning for Better Predictions with Limited Data.

ABSTRACT: The fields of machine learning (ML) and cognitive science have developed complementary approaches to computationally modeling human behavior. ML's primary concern is maximizing prediction accuracy; cognitive science's primary concern is explaining the underlying mechanisms. Cross-talk between these disciplines is limited, likely because the tasks and goals usually differ. The domain of e-learning and knowledge acquisition constitutes a fruitful intersection for the two fields' methodologies to be integrated because accurately tracking learning and forgetting over time and predicting future performance based on learning histories are central to developing effective, personalized learning tools. Here, we show how a state-of-the-art ML model can be enhanced by incorporating insights from a co

SUBMITTER: Sense F 

PROVIDER: S-EPMC9786646 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature