An empirical investigation of neural methods for content scoring of science explanations

Brian Riordan, Sarah Bichler, Allison Bradford, Jennifer King Chen, Korah J. Wiley, Libby F. Gerard, Marcia C. Linn. An empirical investigation of neural methods for content scoring of science explanations. In Jill Burstein, Ekaterina Kochmar, Claudia Leacock, Nitin Madnani, Ildikó Pilán, Helen Yannakoudakis, Torsten Zesch, editors, Proceedings of the Fifteenth Workshop on Innovative Use of NLP for Building Educational Applications, BEA@ACL 2020, Online, July 10, 2020. pages 135-144, Association for Computational Linguistics, 2020. [doi]

@inproceedings{RiordanBBCWGL20,
  title = {An empirical investigation of neural methods for content scoring of science explanations},
  author = {Brian Riordan and Sarah Bichler and Allison Bradford and Jennifer King Chen and Korah J. Wiley and Libby F. Gerard and Marcia C. Linn},
  year = {2020},
  url = {https://www.aclweb.org/anthology/2020.bea-1.13/},
  researchr = {https://researchr.org/publication/RiordanBBCWGL20},
  cites = {0},
  citedby = {0},
  pages = {135-144},
  booktitle = {Proceedings of the Fifteenth Workshop on Innovative Use of NLP for Building Educational Applications, BEA@ACL 2020, Online, July 10, 2020},
  editor = {Jill Burstein and Ekaterina Kochmar and Claudia Leacock and Nitin Madnani and Ildikó Pilán and Helen Yannakoudakis and Torsten Zesch},
  publisher = {Association for Computational Linguistics},
  isbn = {978-1-952148-18-7},
}