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Lecture Notes in Computer Science
In this paper, we present a novel approach to leverage the power of Neural Tensor Networks (NTN) for student answer assessment in intelligent tutoring systems. The approach was evaluated on data collected using a dialogue based intelligent tutoring system (ITS). Particularly, we have experimented with different assessment models that were trained using features generated from knowledge graph embeddings derived with NTN. Our experiments showed that the model trained with the feature vectorsdoi:10.1007/978-3-030-52237-7_16 fatcat:gd6b3obtyzbvvblhv3o7p6nltm