NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Panchompoo Wisittanawat; Richard Lehrer – Cognition and Instruction, 2024
This report characterizes forms of dialogic support that a sixth-grade teacher generated during whole-class and small-group conversations to help students develop a practice of statistical modeling. During four weeks of instruction, students constructed and revised models to account for variability and uncertainty across a variety of random…
Descriptors: Statistics Education, Mathematical Models, Grade 6, Evaluation Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Dvir, Michal; Ben-Zvi, Dani – Mathematical Thinking and Learning: An International Journal, 2023
Growing scholarship on the pedagogical applications of statistical modeling is currently taking place to create adaptations of this practice to introduce novices to statistics. These are intended to promote novices' reasoning, and are typically void of formal mathematical procedures and calculations. In this article, we define the potential…
Descriptors: Teaching Methods, Statistics Education, Novices, Correlation
Peer reviewed Peer reviewed
Direct linkDirect link
Dvir, Michal; Ben-Zvi, Dani – Mathematical Thinking and Learning: An International Journal, 2023
Employing a statistical modeling inspired pedagogy is becoming a widespread practice in the statistics education community. Many have incorporated the practice of formulating conjectures in their modeling-enhanced educational designs and have reported on its benefits. We further elucidate the mechanism through which students' conjecturing may be…
Descriptors: Mathematics Instruction, Teaching Methods, Statistics Education, Instructional Design
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Lehrer, Richard – Statistics Education Research Journal, 2017
Grade 6 (modal age 11) students invented and revised models of the variability generated as each measured the perimeter of a table in their classroom. To construct models, students represented variability as a linear composite of true measure (signal) and multiple sources of random error. Students revised models by developing sampling…
Descriptors: Models, Statistics, Statistical Inference, Mathematics Instruction