3 resources

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

  • Sami Baral, Anthony Botelho, Abhishek Sa...
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    Jul 5th, 2023
    |
    journalArticle
    Sami Baral, Anthony Botelho, Abhishek Sa...
    Jul 5th, 2023

    Teachers often rely on the use of a range of open-ended problems to assess students' understanding of mathematical concepts. Beyond traditional conceptions of student open-ended work, commonly in the form of textual short-answer or essay responses, the use of figures, tables, number lines, graphs, and pictographs are other examples of open-ended work common in mathematics. While recent developments in areas of natural language processing and machine learning have led to automated methods to...

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