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Despite the ubiquity of variation in child development within individuals, across groups, and across tasks, timescales, and contexts, dominant methods in developmental science and education research still favor group averages, short snapshots of time, and single environments. These methods cannot provide evidence about variability or potential interactions among different dimensions of variability. The Learning Variability Network Exchange (LEVANTE) is a framework designed to enable coordinated data collection by diverse individual research teams worldwide, with the goal of measuring children’s variability within and across individuals, groups, and cultures. The measure set developed for LEVANTE aims to capture variability in learning outcomes (literacy and numeracy) as well as core cognitive constructs (language, reasoning, executive function, spatial cognition) and social constructs (social cognition, caregiver engagement, relations with peers), with each measure selected based on length, psychometric properties, cross-cultural applicability, and age span. LEVANTE will yield a large, open access longitudinal dataset for long-term research use. This repository will not only facilitate the science of learning variability, but also constitute the backbone of a larger multidisciplinary research network working toward improving children’s learning and development globally.
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Michael C. Frank (2024) studied this question.
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