2 resources

  • Mengxue Zhang, Neil Heffernan, Andrew La...
    |
    Jun 1st, 2023
    |
    preprint
    Mengxue Zhang, Neil Heffernan, Andrew La...
    Jun 1st, 2023

    Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score labels. However, since scoring is a subjective process, these human scores are noisy and can be highly variable, depending on the scorer. In this paper,...

  • Mengxue Zhang, Neil Heffernan, Andrew La...
    |
    Jun 1st, 2023
    |
    preprint
    Mengxue Zhang, Neil Heffernan, Andrew La...
    Jun 1st, 2023

    Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score labels. However, since scoring is a subjective process, these human scores are noisy and can be highly variable, depending on the scorer. In this paper,...

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