Operational momentum in multiplication and division?
Operational momentum in multiplication and division?
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DOI：
10.1371/journal.pone.0104777
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Knops A
中科院分区：
文献类型：
--
作者：
Katz C;Knops A
在数字认知中，偏向是很常见的。运算动量(OM)效应表明，对加法和减法问题的反应在运算的整数方向上是有偏差的。目前还不知道其他算术运算是否存在这种偏差。为了确定在标量运算中是否存在OM，我们测量了进行符号(阿拉伯数字)和非符号(点)乘法和除法问题的成年人的反应偏差。在看到两个带有乘号(×)或除号(？)的操作数后，参与者从五个反应选项中进行选择。在多元回归分析中，非随机的表现特征和两个操作数对预测值的显著贡献都表明，成年人能够使用数字信息来近似这两个符号的结果，尽管他们在符号问题上更准确。在非符号问题上的表现受到正确选择相对于选择的大小的影响。让人想起加法和减法的偏差，我们发现对非符号问题有显著的反应偏差。非符号乘法问题被高估，除法问题被低估。这些结果表明，运算动量在非符号乘法和除法中存在。考虑到正确选择相对于备选方案的大小的影响，启发式偏差和近似计算之间的交互作用是可能的。
Biases are commonly seen in numerical cognition. The operational momentum (OM) effect shows that responses to addition and subtraction problems are biased in the whole-number direction of the operation. It is not known if this bias exists for other arithmetic operations. To determine whether OM exists in scalar operations, we measured response bias in adults performing symbolic (Arabic digits) and non-symbolic (dots) multiplication and division problems. After seeing two operands, with either a multiplication (×) or division (÷) sign, participants chose among five response choices. Both non-random performance profiles and the significant contribution of both operands in a multiple regression analysis predicting the chosen values, suggest that adults were able to use numerical information to approximate the outcomes in both notations, though they were more accurate on symbolic problems. Performance on non-symbolic problems was influenced by the size of the correct choice relative to alternatives. Reminiscent of the bias in addition and subtraction, we found a significant response bias for non-symbolic problems. Non-symbolic multiplication problems were overestimated and division problems were underestimated. These results indicate that operational momentum is present in non-symbolic multiplication and division. Given the influence of the size of the correct choice relative to alternatives, an interaction between heuristic bias and approximate calculation is possible.
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影响因子：
3.8
作者：
Knops A;Zitzmann S;McCrink K
通讯作者：
McCrink K
影响因子：
5.4
作者：
Gebuis, Titia;Reynvoet, Bert
通讯作者：
Reynvoet, Bert
影响因子：
2.6
作者：
Barth, Hilary;Baron, Andrew;Carey, Susan
通讯作者：
Carey, Susan
影响因子：
4.1
作者：
LeFevre, JA;Bisanz, J;Sadesky, GS
通讯作者：
Sadesky, GS
影响因子：
25
作者：
Fischer, MH;Castel, AD;Pratt, J
通讯作者：
Pratt, J