43 research outputs found

    CEML data management policy

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    This is the Data Management Policy document of the CEML, which accompanies the blog post Data management – from a section in the grant proposal to a day-to-day reference manual.</p

    CEML Data Policy - training video

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    This is a training video on data management for CEML, which is a supplementary material to the blog post "Data management – from a section in the grant proposal to a day-to-day reference manual"</p

    CEML Variable Dictionary Template

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    This is the Centre for Early Mathematics Learning (CEML) variable dictionary template, which is a supporting material to the blog post Data management – from a section in the grant proposal to a day-to-day reference manual.</p

    CEML Variable Dictionary

    No full text
    This is a variable dictionary document for the Centre for Early Mathematics Learning, published as a supplementary material to the blog post Data management – from a section in the grant proposal to a day-to-day reference manual</p

    Finding the SNARC instead of hunting it: A 20*20 monte carlo investigation

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    © 2017 Cipora and Wood. The Spatial Numerical Association of Response Codes (SNARC) effect describes a stimulus-response association of left with small magnitude and right with large magnitude. Usually, it is estimated by means of regression slopes, where the independent variable only has a limited number of levels. Inspection of the literature reveals that it is not difficult to detect a SNARC effect within a group, but it has been quite unusual to find group differences. Is the SNARC effect as it is usually estimated using regression slopes largely insensitive to group differences, and are there design parameters necessary to increase sensitivity in group comparison analyses? Using numerical simulations, we provide evidence that both sample size and the number of stimulus repetitions, as well as intra-individual variability, contribute in a substantial way to the probability of detecting an existing SNARC effect. Our results show that the adequate choice of either sample size or number of repetitions per experimental cell does not fully compensate for a poor choice of the other parameter. Moreover, repeated failures to find significant group differences in the SNARC effect can be explained by insufficient power. Fortunately, increasing the number of repetitions to about 20 and testing at least 20 participants provides in most cases sufficient sensitivity to reliably detect the SNARC effect as well as group differences. Power plots are provided, which may help to improve both the economy and sensitivity of experimental design in future SNARC experiments, or, more generally when regression slopes are estimated intra-individually

    Is the SNARC effect related to the level of mathematics? No systematic relationship observed despite more power, more repetitions, and more direct assessment of arithmetic skill

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    The SNARC (spatial-numerical association of response codes) described that larger numbers are responded faster with the right hand and smaller numbers with the left hand. It is held in the literature that arithmetically skilled and nonskilled adults differ in the SNARC. However, the respective data are descriptive, and the decisive tests are nonsignificant. Possible reasons for this nonsignificance could be that in previous studies (a) very small samples were used, (b) there were too few repetitions producing too little power and, consequently, reliabilities that were too small to reach conventional significance levels for the descriptive skill differences in the SNARC, and (c) general mathematical ability was assessed by the field of study of students, while individual arithmetic skills were not examined. Therefore we used a much bigger sample, a lot more repetitions, and direct assessment of arithmetic skills to explore relations between the SNARC effect and arithmetic skills. Nevertheless, a difference in SNARC effect between arithmetically skilled and nonskilled participants was not obtained. Bayesian analysis showed positive evidence of a true null effect, not just a power problem. Hence we conclude that the idea that arithmetically skilled and nonskilled participants generally differ in the SNARC effect is not warranted by our data. © 2013 The Experimental Psychology Society

    What the Attentional-SNARC and its (null) replications can and cannot tell us

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    In response to a recent point raised by Fischer at al. (2020), we discuss the theoretical implications of both the original Attentional SNARC (Att-SNARC) and its recent failed multilaboratory replication. In our view, the theoretical importance of the original Att-SNARC can be summarized in two points: (1) there is a conceptual link between numbers and space, which can be observed as Spatial-Numerical Associations, and (2) Spatial-Numerical Associations are involuntary and automatic. We conclude that convergent evidence from other paradigms saves the first point from being challenged in light of the failed replication; but, on the other hand, empirical evidence for the second point no longer holds.</p

    Forty-two or two-and-forty: learning maths in different languages

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    Doing basic maths seems to be a pretty common thing. 2 + 2 equals 4, both in France and in China. 7 Ă— 8 equals 56, both in the United States of America and in Germany. Although most of us use the same symbols to write down numbers (1, 2, 3, 4 ...), we use very different words for these numbers simply because we speak different languages. In this article, we will give examples of what number words in different languages look like. We also show how the way multi-digit number words are built can make learning maths and dealing with large numbers easier or more difficult. </div

    Analogue magnitude representation of angles and its relation to geometric expertise

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    The distance effect (comparing objects becomes easier with increasing differences in their magnitude) is observed in tasks ranging across domains, and its existence has been interpreted as evidence for analogue magnitude representation. Similarly, associations between response side and magnitude (faster left/right-sided responses to small/large objects, respectively) are observed across domains. We investigated the analogue processing of angles and the association between angle magnitude and response side in relation to geometric expertise. We compared the behavioural pattern of two groups—architects and controls—in a direct angle magnitude classification task (i.e., judge whether a presented angle was greater or less than 90°) and in an indirect task (i.e., judge whether an angle was drawn with a dashed or continuous line). We found a robust distance effect for reaction times and accuracy at the whole sample level and in each group separately. Architects revealed a smaller distance effect for accuracy than controls. This could be interpreted as an argument for a more precise analogue representation of angles in experts compared to non-experts. However, we did not find evidence for an association between angle magnitude and response side in any group.</p
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