Grade Level Filtering for Learning Object Search using Entity Linking

Abstract

More and more Learning Objects like lessons, exercises, worksheets and lesson plans are available online. Finding them, however, is a challenge as they often lack metadata concerning format, content and, in the K-12 context: grade-levels or age ranges for which they are appropriate. This work studies the automatic content-based assignment of this last aspect of Learning Object metadata. For this purpose, we (a) collected a dataset of physics lessons, (b) explored a set of text-based features for their automatic analysis (derived from both dense vector representations and entity linking methods) and (c) trained a machine learning model with different subsets of these features to predict a resource’s target grade level. We compare and discuss the results.