从开发到验证:探索Numetrive的效率,这是对数值推理的计算机自适应评估.
Marianna Karagianni1, Ioannis Tsaousis2
1Department of Psychology, School of Social Sciences, University of Crete, 74100 Rethymno, Greece.
Behavioral sciences (Basel, Switzerland)
|March 28, 2025
概括
Numetrive是一个新的计算机自适应测试系统,有效地测量数字推理. 蒙特卡洛模拟显示,它准确地评估了一些项目和低暴露率的能力.
科学领域:
- 心理测量 心理测量 心理测量
- 教育测量教育的测量
- 认知评估 认知评估
背景情况:
- 传统的测试方法可能缺乏效率和精度.
- 计算机自适应测试 (CAT) 为能力测量提供了一种更为动态的方法.
- 开发强大的CAT系统对于准确评估数字推理等认知技能至关重要.
研究的目的:
- 详细介绍 Numetrive 的评估方法,这是一种用于数值推理的新型 CAT 系统.
- 评估Numetrive系统的心理测量特性和有效性.
- 为了验证Numetrive系统在测量数值推理方面的性能.
主要方法:
- 开发了一个174个项目库,使用两参数物流模型 (2PLM) 校准.
- 实现了Numetrive的算法组合:最大概率估计与围 (MLEF),渐进限制标准误差 (PRSE) 和估计终止规则的标准误差.
- 通过蒙特卡洛模拟和有效性研究 (并发,收,分歧) 评估性能.
主要成果:
- 蒙特卡洛模拟显示出高效率,平均给5000个模拟者提供13.6个项目,但物品暴露率低.
- 能力评分估计的准确性非常高,由低偏差,平均绝对误差 (MAE) 和根平均平方误差 (RMSE) 证实.
- 验证性研究证实了Numetrive在评估数值推理中的稳定性和适用性.
结论:
- Numetrive是一个高效和准确的计算机化适应性测试系统,用于数值推理.
- 该系统表现出强大的心理测量特性和对能力估计的有效性.
- Numetrive为评估数值推理技能提供了一个强大而适用的解决方案.
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