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Estimating student ability and problem difficulty using item response theory (IRT) and TrueSkill

机译：使用项目反应理论（IRT）和TrueSkill估算学生的能力和问题难度

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PurposeThe purpose of this paper is to investigate an efficient means of estimating the ability of students solving problems in the computer-based learning environment.Design/methodology/approachItem response theory (IRT) and TrueSkill were applied to simulated and real problem solving data to estimate the ability of students solving homework problems in the massive open online course (MOOC). Based on the estimated ability, data mining models predicting whether students can correctly solve homework and quiz problems in the MOOC were developed. The predictive power of IRT- and TrueSkill-based data mining models was compared in terms of Area Under the receiver operating characteristic Curve.FindingsThe correlation between students ability estimated from IRT and TrueSkill was strong. In addition, IRT- and TrueSkill-based data mining models showed a comparable predictive power when the data included a large number of students. While IRT failed to estimate students ability and could not predict their problem solving performance when the data included a small number of students, TrueSkill did not experience such problems.Originality/valueEstimating students ability is critical to determine the most appropriate time for providing instructional scaffolding in the computer-based learning environment. The findings of this study suggest that TrueSkill can be an efficient means for estimating the ability of students solving problems in the computer-based learning environment regardless of the number of students.
机译：目的本文旨在研究评估学生在计算机学习环境中解决问题能力的有效方法。将设计/方法论/方法项目反应理论（IRT）和TrueSkill应用于模拟和实际问题解决数据以进行估计学生在大规模开放在线课程（MOOC）中解决家庭作业问题的能力。根据估计的能力，开发了预测学生是否可以正确解决MOOC中的家庭作业和测验问题的数据挖掘模型。根据IRT和TrueSkill的数据挖掘模型的预测能力，根据接收器工作特征曲线下的面积进行了比较。结果从IRT和TrueSkill估计的学生能力之间的相关性很强。此外，当数据包含大量学生时，基于IRT和TrueSkill的数据挖掘模型显示出可比的预测能力。虽然IRT无法估算学生的能力并且无法在数据包括少量学生的情况下预测其解决问题的能力，但TrueSkill并未遇到此类问题。基于计算机的学习环境。这项研究的结果表明，无论学生人数多少，TrueSkill都是评估学生在基于计算机的学习环境中解决问题的能力的有效手段。

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