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We have demonstrated the extent to which a reconstruction algorithm can account for participants' performance in a simple navigation task.
The purpose of the current study was to further our understanding of the neural mechanisms underlying inner speech and its relation to overt speech, while controlling for participants' performance.
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Based on studies completed with previous versions of COACH, 10 trials per phase were deemed to be sufficient for participant performance to stabilize and for the desired changes in the dependent variables to be observed [ 22].
We did use single blinding (of assessors) for the assessment of participants' performance in the prescribing exercises, however.
As such, we dropped the challenging question across all learning checks and quiz when we analyzed the participants' performance for mathematics.
In fact, a recent reanalysis of data from large L1 and L2 lexical decision databases suggests that participants' performance for words on the lowest frequency level is a similarly effective predictor of vocabulary size as LexTALE is (Diependaele, Lemhöfer, & Brysbaert, 2011).
In this system, the participants' performance both for the main task (simulated by simple arithmetic problems) and for the secondary task (a simulation of a production process) can be measured in a more fine-grained manner than has been the case for existing research in this field.
The participants' performance characteristics for the VO2 max test are presented in Table 2.
> -wrap-foot> The rotated PCA produced a three factor solution which accounted for 82% of variance in participants' performance (F1 = 61%; F2 = 14%, F3 = 7%).
For this analysis, we compared participants' performance as a function of their change from the most direct condition (no decoupling, standard mapping), similar to our previous studies.
However, participants' performance differed greatly for these two visually and semantically similar numerals (Fig. 2), further indicated that it is the common properties of small Chinese numerals as a whole (e.g., being multi-representational numerals), rather than the individual characteristic of each numeral per se, that contributes to their processing advantage over small Arabic numerals.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com