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<p>This study addresses the growing need for ethical guidelines for artificial intelligence (AI) in education research by testing and refining procedures for responsible experimentation with AI in educational settings. The researchers engaged 21 Dutch Institutional Review Board (IRB) members across two feedback rounds to evaluate available ethical procedures from the literature. These procedures focus on four key areas: gradual scaling, side-effects monitoring, proportional stopping rules, and stakeholder consultation, with different requirements based on levels of AI automation and human oversight. Results showed strong consensus among IRB members that AI experiments require specialized ethical procedures beyond standard human subjects protections. After incorporating feedback from the first round, including clarifying terminology, distinguishing between general-purpose AI and educational AI, and providing clearer process descriptions, the second round achieved unanimous agreement on the procedures' clarity and utility. Notably, while IRB members agreed on the need for specialized procedures, they believed regular IRBs could handle most cases rather than requiring automatic escalation to specialized committees. The study contributes practical, stakeholder-validated procedures that balance ethical rigor with bureaucratic efficiency, enabling IRBs to better assess AI education research while distinguishing between higher and lower risk experiments based on AI type and automation level.</p>

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Usable procedures for responsible experiments with artificial intelligence in education

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月26日

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  • Izaak Dekker,
  • Bhoomika Agarwal,
  • Bert Bredeweg,
  • Inge Molenaar,
  • Ibo van de Poel

摘要

This study addresses the growing need for ethical guidelines for artificial intelligence (AI) in education research by testing and refining procedures for responsible experimentation with AI in educational settings. The researchers engaged 21 Dutch Institutional Review Board (IRB) members across two feedback rounds to evaluate available ethical procedures from the literature. These procedures focus on four key areas: gradual scaling, side-effects monitoring, proportional stopping rules, and stakeholder consultation, with different requirements based on levels of AI automation and human oversight. Results showed strong consensus among IRB members that AI experiments require specialized ethical procedures beyond standard human subjects protections. After incorporating feedback from the first round, including clarifying terminology, distinguishing between general-purpose AI and educational AI, and providing clearer process descriptions, the second round achieved unanimous agreement on the procedures' clarity and utility. Notably, while IRB members agreed on the need for specialized procedures, they believed regular IRBs could handle most cases rather than requiring automatic escalation to specialized committees. The study contributes practical, stakeholder-validated procedures that balance ethical rigor with bureaucratic efficiency, enabling IRBs to better assess AI education research while distinguishing between higher and lower risk experiments based on AI type and automation level.