nlpscu/Analyzing-Demographic-Biases

--- language: - en task_categories: - text-classification task_ids: - text-scoring pretty_name: PERSUADE 2.0 & ASAP 2.0 Essay Scoring Datasets size_categories: - 10K<n<100K license: other tags: - essay-scoring - automated-essay-scoring - education - nlp --- # PERSUADE 2.0 & ASAP 2.0 — Essay Scoring Datasets Datasets for our NLP class project on Automated Essay Scoring (AES), combining two widely used student essay corpora. --- ## PERSUADE 2.0 A large-scale corpus of argumentative and persuasive student essays (grades 6–12), annotated with discourse elements and holistic essay scores (1–6). **Files:** - `persuade_corpus_2.0_train.csv` - `persuade_corpus_2.0_test.csv` **Key columns:** | Column | Description | |---|---| | `essay_id` | Unique essay identifier | | `full_text` | Raw essay text | | `holistic_essay_score` | Overall score (1–6) | | `prompt_name` | Writing prompt | | `grade_level` | Student grade (6–12) | --- ## ASAP 2.0 An updated version of the Automated Student Assessment Prize benchmark. Essays span 8 distinct prompts (argumentative, narrative, source-dependent) and are scored by human raters on prompt-specific rubrics. **Files:** - `ASAP_2_Final_github_train.csv` - `ASAP_2_Final_github_test.csv` - `ASAP2_train_sourcetexts.csv` — source texts referenced by source-dependent prompts **Key columns:** | Column | Description | |---|---| | `essay_id` | Unique essay identifier | | `essay_set` | Prompt ID (1–8) | | `full_text` | Raw essay text | | `domain1_score` | Primary human rater score | | `final_score` | Resolved score used for evaluation |