Modeling the left digit effect in adult number line estimation
Modeling the left digit effect in adult number line estimation
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DOI：
10.1016/j.cognition.2022.105257
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发表时间：
2022-10
期刊：
影响因子：
3.4
通讯作者：
A. Patalano;Kelsey Kayton;H. Barth
中科院分区：
文献类型：
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作者：
A. Patalano;Kelsey Kayton;H. Barth
数轴估计任务经常用于研究数字认知技能。在典型的有界数线任务中，目标数字必须放在仅在其端点标记的有界线上（例如，用0和100）。成年人的定位虽然非常准确，但却揭示了对目标数字高估和低估的周期性模式。这种模式建议使用比例判断策略，并被周期性权力模型很好地捕捉到。最近观察到的另一个系统的数轴偏差，但尚未在建模工作中考虑到，是左数字效应。最左边数字不同的数字（例如，39和41）在一条线上放置的距离比要求的要远。在本研究中（N= 60），在0-100数轴估计任务中获得了所有数字的成人估计，并比较了标准周期功率模型与两个修正模型的拟合。一个修改后的版本包括一个参数，该参数低估了右侧数字的位值（例如，这里的个位数），另一个使用相同的参数来低估数位的位值。我们发现，这两种修正都比标准模型更适合个人和中位数数据，我们讨论了它们的相对优点和认知解释。数据和模型表明，左数字偏差可能会影响整个数轴的估计。
Number line estimation tasks are frequently used to study numerical cognition skills. In a typical version, the bounded number line task, target numerals must be placed on a bounded line labeled only at its endpoints (e.g., with 0 and 100). Placements by adults, while highly accurate, reveal a cyclical pattern of over- and underestimation of target numerals. The pattern suggests use of proportion judgment strategies and is well-captured by cyclical power models. Another systematic number line bias that has recently been observed, but has not yet been considered in modeling efforts, is theleft digit effect. Numerals with different leftmost digits (e.g., 39 and 41) are placed farther apart on a line than is warranted. In the current study (N= 60), adult estimates were obtained for all numerals on a 0–100 number line estimation task, and fit of the standard cyclical power model was compared with two modified versions of the model. One modified version included a parameter that underweights the rightward digit's place value (e.g., the ones digit here), and the other used the same parameter to underweightalldigits' place values. We found that both modifications provided a considerably better fit for individual and median data than the standard model, and we discuss their relative merits and cognitive interpretations. The data and models suggest how a left digit bias might impact estimates across the number line.