We compared our approach on the Automated Student Assessment Prize data set, in both in-domain and crossdomain settings, with several state-of-the-art approaches (<cite>Phandi et al., 2015</cite>; Dong and Zhang, 2016; Tay et al., 2018) . Overall, the in-domain and the cross-domain comparative studies indicate that string kernels, both alone and in combination with word embeddings, attain the best performance on the automatic essay scoring task. Using a shallow approach, we report better results compared to recent deep learning approaches (Dong and Zhang, 2016; Tay et al., 2018) .