In this paper, we describe the creation of a resource - ASAP++ - which is basically annotations of the Automatic Student Assessment Prize’s Automatic Essay Grading dataset. These annotations are scores for different attributes of the essays, such as content, word choice, organization, sentence fluency, etc. Each of these essays is scored by an annotator. We also report the results of each of the attributes using a Random Forest Classifier using a baseline set of task independent features. We release and share this resource to facilitate further research into these attributes of essay grading.
@InProceedings{MATHIAS18.373, author = {Sandeep Mathias and Pushpak Bhattacharyya}, title = "{ASAP++: Enriching the ASAP Automated Essay Grading Dataset with Essay Attribute Scores}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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