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New dataset EduWild reveals common failures in teacher-configured educational chatbots

By PulseAugur Editorial · [1 sources] ·

A new dataset called EduWild has been released, containing 1,726 conversations with 217 teacher-configured educational chatbots. The dataset, along with the configuration behind each bot, reveals that the most common failures involve chatbots not adhering to teacher intent, such as skipping steps or providing too much information. Researchers developed a prompt-based harness that significantly reduced these failures by 65.2% in a study with 200 college students. AI

IMPACT Identifies key failure modes in educational chatbots, guiding improvements for better AI-driven learning tools.

RANK_REASON The cluster contains a research paper detailing a new dataset and findings on educational chatbots. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New dataset EduWild reveals common failures in teacher-configured educational chatbots

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The cluster contains a research paper detailing a new dataset and findings on educational chatbots. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Ziqi Liu, Ruiwei Xiao, Yuxuan Li, John Stamper ·

    EduWild: How Teacher-Configured Chatbots Fail in Real-World Use and How to Fix Them

    arXiv:2610.23530v1 Announce Type: new Abstract: Teachers increasingly configure educational chatbots through natural-language instructions, but how these bots fail in real-world use remains poorly understood. We introduce EduWild, a dataset of 1,726 conversations with 217 teacher…

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