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taisazero/socratic-debugging-benchmark

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Citation text from the card

@inproceedings{al-hossami-etal-2023-socratic,
    title = "Socratic Questioning of Novice Debuggers: A Benchmark Dataset and Preliminary Evaluations",
    author = "Al-Hossami, Erfan  and
      Bunescu, Razvan  and
      Teehan, Ryan  and
      Powell, Laurel  and
      Mahajan, Khyati  and
      Dorodchi, Mohsen",
    booktitle = "Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.bea-1.57",
    pages = "709--726",
    abstract = "Socratic questioning is a teaching strategy where the student is guided towards solving a problem on their own, instead of being given the solution directly. In this paper, we introduce a dataset of Socratic conversations where an instructor helps a novice programmer fix buggy solutions to simple computational problems. The dataset is then used for benchmarking the Socratic debugging abilities of GPT-based language models. While GPT-4 is observed to perform much better than GPT-3.5, its precision, and recall still fall short of human expert abilities, motivating further work in this area.",
}

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dataset_licence({ "id": "taisazero/socratic-debugging-benchmark" })
signal: "permissive"
stated_licence: "mit"
sources: 0