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English(EN) From Student Risk Prediction to SC2R: Semantics-Constrained Counterfactual Recourse for Educational Decision Support

新的SC2R框架为有风险的学生提供语义上可行的干预措施

研究人员开发了SC2R,一个旨在为被识别为有学业表现不佳风险的学生提供可操作且符合约束条件的干预措施的新框架。该系统结合了预测建模和整数规划来生成可行的干预计划,并使用RDF和SHACL进行语义验证,以确保计划符合时间、预算和可用性等教育约束。在OULAD数据集上的评估表明,SC2R能够大规模生成紧凑的计划,并识别出更简单的优化方法可能忽略的语义上不可行的建议。 AI

影响 该框架可以通过确保建议不仅具有预测性,而且在现实世界的约束条件下也切实可行,从而提高教育支持系统的运行效率。

排序理由 该集群包含一篇详细介绍教育决策支持新框架的研究论文。

在 arXiv cs.IR (Information Retrieval) 阅读 →

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新的SC2R框架为有风险的学生提供语义上可行的干预措施

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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Ngoc Luyen Le, Marie-H\'el\`ene Abel, Bertrand Laforge ·

    从学生风险预测到SC2R:面向教育决策支持的语义约束反事实追溯

    arXiv:2608.17618v1 Announce Type: cross Abstract: Learning analytics models can identify students at risk of poor performance, but they do not directly indicate which interventions are feasible, actionable, and compatible with educational constraints. This paper introduces SC2R, …

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Bertrand Laforge ·

    从学生风险预测到SC2R:用于教育决策支持的语义约束反事实追溯

    Learning analytics models can identify students at risk of poor performance, but they do not directly indicate which interventions are feasible, actionable, and compatible with educational constraints. This paper introduces SC2R, a semantics-constrained counterfactual recourse fr…