Person: Vidal-Szabó, Pedro
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Vidal-Szabó
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Pedro
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Publication Exploring informal statistical inference in early statistics: a learning trajectory for third-grade students(2023) Estrella, Soledad; Méndez-Reina, Maritza; Vidal-Szabó, PedroRecent research suggests the benefits of supporting a progressive understanding of concepts of inference prior to the teaching of procedures and formal calculations through the study of informal statistical inference (ISI). To contribute to the growing knowledge about the early learning and teaching of statistics, particularly regarding the development of informal inferential reasoning (IIR), we designed a learning trajectory (LT) that addresses ISI in K–4 students (ages 5 to 9 years). This article describes part of the LT in detail, in which third-grade students (n = 12) were introduced to sampling, frequency distribution, randomness and sampling variation as well as to developing a data sense in online lessons. The results of this type of teaching show that the creation and collection of authentic data in a playful context, together with an exploratory analysis of the data as a precursor to utilizing aspects specific to IIR, promoted the integration progress of IIR components in the oral and written informal inferences of students.Publication Diseño de una trayectoria hipotética de aprendizaje para introducir la inferencia informal en primaria(2024) Estrella, Soledad; Morales, Sergio; Méndez-Reina, Maritza; Vidal-Szabó, Pedro; Ramírez, Brahiam; Mondaca-Saavedra, AlejandraMediante un estudio de diseño que desarrolla una trayectoria hipotética de aprendizaje para la inferencia estadística informal (ISI), se introdujo a estudiantes de grado 3 y 4 (n=23), conceptos claves de variabilidad, muestreo repetido y distribución muestral empírica. La trayectoria de cinco pasos con un enfoque lúdico del experimento aleatorio del lanzamiento de dos monedas comprendía: obtener muestras; reconocer la incertidumbre y expresarla con lenguaje de posibilidades; contrastar predicciones mediante muestreo repetido; visualizar y reconocer la variabilidad entre muestras; asignar niveles de posibilidades considerando la distribución muestral empírica al generalizar más allá de los datos. Los resultados indican que los estudiantes de ambos grados pueden acceder a conceptos de la ISI, logrando hacer inferencias informales y presentando niveles sofisticados en el razonamiento propio de la ISI.