Beyond the average: person-specific analytics for precision education
[EN]Educational research has traditionally relied on group-level analyses to identify patterns across learners. While valuable for detecting general trends, such approaches often provide limited insight into how learning processes unfold within individuals. This introduction to person-specific analy...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión enviada para evaluación y publicación |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad de Salamanca (USAL) |
| Repositorio: | GREDOS. Repositorio Institucional de la Universidad de Salamanca |
| OAI Identifier: | oai:gredos.usal.es:10366/165840 |
| Acceso en línea: | http://hdl.handle.net/10366/165840 |
| Access Level: | acceso abierto |
| Palabra clave: | Person-specific analytics Idiographic methods Learning analytics Precision education |
| Sumario: | [EN]Educational research has traditionally relied on group-level analyses to identify patterns across learners. While valuable for detecting general trends, such approaches often provide limited insight into how learning processes unfold within individuals. This introduction to person-specific analytics presents recent methodological and conceptual developments that address this gap, including intensive longitudinal designs, idiographic modeling, and person-specific machine learning. The contributing articles examine how individual trajectories in motivation, self-regulation, collaboration, and cognitive development can be studied more accurately when variability is treated as a central feature rather than as noise. Together, the contributions highlight how person-specific methods can complement traditional approaches by enabling more precise, adaptive, and context-sensitive educational practices. |
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