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. The Learning Variability Network Exchange (LEVANTE) is a framework designed to enable coordinated data collection by research teams worldwide, with the goal of measuring variability in children's learning and development. The LEVANTE measure set aims to capture variability in learning outcomes (literacy and numeracy) as well as in core cognitive and social constructs. LEVANTE will yield a large, open access longitudinal dataset for long-term research use, both creating a multidisciplinary research network and facilitating the science of learning variability.
Learning Variability Network Exchange (LEVANTE): A Global Framework for Measuring Children's Learning Variability Through Collaborative Data Sharing.
Michael C. Frank,Heidi A. Baumgartner,M. Braginsky,George Kachergis,A. Lightbody,Robert Z. Sparks,Rebecca Zhu,Stephanie M. Carlson,Sandra Graham,S. Lipina,Nora S. Newcombe,Candice L. Odgers,R. Pianta,Robert S. Siegler,M. Snowling,Hirokazu Yoshikawa,A. Cubillo,Kenneth A. Dodge
Published 2025 in Child Development
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- Publication year
2025
- Venue
Child Development
- Publication date
2025-08-02
- Fields of study
Medicine, Education, Psychology
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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