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Computer adaptive practice of Maths ability using a new item response model for on the fly ability and difficulty estimation

机译:使用新的项目反应模型进行飞行能力和难度估计的数学能力的计算机自适应实践

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摘要

In this paper we present a model for computerized adaptive practice and monitoring. This model is used in the Maths Garden, a web-based monitoring system, which includes a challenging web environment for children to practice arithmetic. Using a new item response model based on the Elo (1978) rating system and an explicit scoring rule, estimates of the ability of persons and the difficulty of items are updated with every answered item, allowing for on the fly item calibration. In the scoring rule both accuracy and response time are accounted for. Items are sampled with a mean success probability of .75, making the tasks challenging yet not too difficult. In a period of ten months our sample of 3648 children completed over 3.5 million arithmetic problems. The children completed about 33% of these problems outside school hours. Results show better measurement precision, high validity and reliability, high pupil satisfaction, and many interesting options for monitoring progress, diagnosing errors and analyzing development.
机译:在本文中,我们提出了一种计算机化的适应性实践和监测模型。该模型在基于网络的监视系统Maths Garden中使用,其中包括一个挑战性的网络环境,供儿童练习算术。使用基于Elo(1978)评分系统的新项目响应模型和明确的评分规则,每个已回答的项目都会更新人员能力和项目难度的估计值,从而可以即时进行项目校准。在评分规则中,准确性和响应时间都被考虑在内。样本的平均成功概率为0.75,这使任务具有挑战性,但又不太困难。在10个月的时间内,我们的3648名儿童样本完成了超过350万个算术问题。在课余时间,孩子们完成了大约33%的这些问题。结果显示出更高的测量精度,较高的有效性和可靠性,较高的瞳孔满意度,以及用于监视进度,诊断错误和分析发展的许多有趣的选项。

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