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Title: Toward a Theoretical Framework for Data Fluency Teaching and Learning in Middle School STEM
This paper presents findings from a qualitative study of eleven experienced STEM educators who worked alongside developers to design and implement data-rich lessons in their grades 6–9 mathematics and science classrooms. In the context of a project that seeks to develop professional learning for data fluency, researchers documented the co-development process to articulate a model of what teachers need to know and be able to do in order to support their students’ data fluency. The project team distilled key findings into two framing documents: 1) a description of high-leverage areas of focus for PL which highlight challenges faced by teachers, which are common, important for data fluency, and represent opportunities for supporting teacher and student growth; and 2) a logic model that describes how the PL course under development is expected to influence teacher, classroom, and student outcomes. This paper contributes to the larger education community by defining the professional learning needs of educators who wish to integrate data into their STEM classrooms. These frameworks provide designers and researchers with touchpoints to structure and study PL experiences, lesson materials, and other classroom resources for both new and veteran educators. These tools can provide STEM teachers with guidance for reflecting on their current knowledge, skills, beliefs, and teaching practices that help their students become more data fluent.  more » « less
Award ID(s):
2101049
PAR ID:
10501737
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
NARST
Date Published:
Journal Name:
Ninety-seventh annual international conference of the National Association for Research in Science Teaching (NARST)
Subject(s) / Keyword(s):
data fluency professional learning STEM mathematics science teachers logic model
Format(s):
Medium: X
Location:
Denver, CO
Sponsoring Org:
National Science Foundation
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