Process / pipeline

Automated Essay Scoring (AES)

Automated Essay Scoring (AES) is a natural-language-processing task in which a computational model assigns scores to student-written essays across dimensions such as grammatical correctness, coherence, content richness, and organisation — replicating, at scale, what a human rater would do. The approach was formalised as a research field by Shermis and Burstein (2013) and has been transformed since 2019 by transformer language models, particularly BERT, which allow AES systems to leverage deep contextual representations of text.

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Sources

  1. Shermis, M.D. & Burstein, J. (2013). Handbook of Automated Essay Evaluation. Routledge. link
  2. Devlin, J., Chang, M.-W., Lee, K. & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. NAACL-HLT, 4171-4186. DOI: 10.18653/v1/N19-1423

Related methods

ScholarGateAutomated Essay Scoring (Automated Essay Scoring (AES)). Retrieved 2026-06-04 from https://scholargate.app/en/text-mining/automated-essay-scoring