Comparative Statistical Analysis of Pre-Existing Non-Symbolic Cognitive Math Models as a Predictor of Math Acuity in Children
Approximate Number System (ANS) acuity has been the underlying basis of mathematical magnitude measure in developing children. The early number learning in a child by means of numerosity representation is said to be best estimated by an ANS based model. ANS models are majorly specific to cases where numbers are represented by non-digits and are therefore non-symbolic (dot representations). Prior research also suggests that ANS acuity models could be used to give an estimate of an accuracy of a child in a non-symbolic math task. Common measures of ANS acuity are based on weber fraction based accuracy performance and some others are based on numerical distance effect and reaction time. However though, very few studies have amalgamated reaction time and weber fraction models and compared them at an individualistic level using actual data collected over participants. In this research study, we effectively try to understand how factors like weber fraction, ratio, magnitude of numbers might affect the performance of a participant in a non-symbolic number comparison task. We also seek for any sort established relationship between numerical distance and reaction time and how that might be a predictor of good/bad performance. We carry out statistical analysis on both of these models (individually and combined) using data obtained from an online math task and thereby deduce which model could be a better predictor of a child’s math acuity.