对于有边界但不是无边界的数列线估计,感知和生产版本之间的潜在分离
Regina Miriam Reinert1, Venera Gashaj2, Matthias Hartmann3
1University of Tübingen, Tübingen, Germany.
Trends in neuroscience and education
|June 12, 2023
概括
数字直线估计 (NLE) 任务根据其版本评估不同的认知技能. 无界限的NLE任务始终测量大小估计,而有界限的NLE任务则涉及比例判断.
科学领域:
- 认知心理学 认知心理学
- 数学教育的数学教育.
背景情况:
- 数字直线估计 (NLE) 任务用于评估数字认知.
- 不同版本的NLE任务可以测量不同的底层结构.
研究的目的:
- 调查有限和无限NLE任务的生产和感知版本之间的关联.
- 检查NLE任务性能和算术能力之间的关系.
主要方法:
- 比较生产和感知NLE任务 (有界和无界) 之间的相关性.
- 评估NLE绩效与算术技能之间的关系.
主要成果:
- 无界限的NLE任务显示出生产和感知版本之间的相关性比有界限的NLE任务更强.
- 仅在有限的NLE任务的生产版本中,NLE性能和算术之间发现了显著的关联.
结论:
- 无限制的NLE任务始终测量大小估计.
- 有限的NLE任务,特别是制作版本,可能依赖于比例判断策略,与算术的联系有限.
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