Literature DB >> 26335207

How to estimate how well people estimate: evaluating measures of individual differences in the approximate number system.

Dana Chesney1, Par Bjalkebring2,3, Ellen Peters2.   

Abstract

At a glance, one can tell that there are more individual fruits in a pile of 100 apples than in a pile of 20 watermelons, even though the watermelons take up more space. People's ability to distinguish between such nonsymbolic numerical magnitudes without counting is derived from the approximate number system (ANS). Individual differences in this ability (ANS acuity) are emerging as an important predictor in research areas ranging from children's understanding of arithmetic to adults' use of numbers in judgment and decision making. However, ANS acuity must be assessed through proxy tasks that might not show consistent relationships with this ability. Furthermore, practical limitations often confine researchers to using abbreviated measures of this ability, whose reliability is questionable. Here, we developed and tested several novel ANS acuity measures: a nonsymbolic discrimination task designed to account for participants' lapses in attention; three estimation tasks, including one task in which participants estimated the number of dots in a briefly presented set, one in which they estimated the ratio between two sets of dots, and one in which they indicated the correct position of a set of dots on a "number-line" anchored by two sets of dots, as well as a similar number-line task using symbolic numbers. The results indicated that the discrimination task designed to account for lapses in participants' attention holds promise as a reliable measure of ANS acuity, considered in terms of both internal and test-retest reliability. We urge researchers to use acuity measures whose reliability has been demonstrated.

Entities:  

Keywords:  Approximate number system; Estimation; Individual differences; Nonverbal counting; Numeracy

Mesh:

Year:  2015        PMID: 26335207     DOI: 10.3758/s13414-015-0974-6

Source DB:  PubMed          Journal:  Atten Percept Psychophys        ISSN: 1943-3921            Impact factor:   2.199


  3 in total

1.  Risk approximation in decision making: approximative numeric abilities predict advantageous decisions under objective risk.

Authors:  Silke M Mueller; Johannes Schiebener; Margarete Delazer; Matthias Brand
Journal:  Cogn Process       Date:  2018-01-22

2.  Ratio effect slope can sometimes be an appropriate metric of the approximate number system sensitivity.

Authors:  Attila Krajcsi
Journal:  Atten Percept Psychophys       Date:  2020-05       Impact factor: 2.199

3.  Comparing Numerical Comparison Tasks: A Meta-Analysis of the Variability of the Weber Fraction Relative to the Generation Algorithm.

Authors:  Mathieu Guillaume; Amandine Van Rinsveld
Journal:  Front Psychol       Date:  2018-09-11
  3 in total

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