Bostic, J. (2023). Engaging hearts and minds in assessment research. School Science and Mathematics Journal, 123(6), 217-219. https://doi.org/10.1111/ssm.12621
A School Science and Mathematics Journal editorial.
Bostic, J. (2023). Engaging hearts and minds in assessment research. School Science and Mathematics Journal, 123(6), 217-219. https://doi.org/10.1111/ssm.12621
A School Science and Mathematics Journal editorial.
This study examines secondary mathematics teachers’ anticipations of student responses related to a series of cognitively demanding mathematics tasks from multiple mathematical domains presented in the context of voluntary and asynchronous online professional development modules. We analyze 283 anticipations made by 127 teachers to 17 mathematics tasks and present four distinct foci of teachers’ anticipations.
This study examines secondary mathematics teachers’ anticipations of student responses related to a series of cognitively demanding mathematics tasks from multiple mathematical domains presented in the context of voluntary and asynchronous online professional development modules.
The need for data literacy is an increasingly pressing priority in society, but most of the work in data-centred education has focused on developing skills at the middle school, secondary, and post-secondary levels, with little attention on the potential for engaging elementary-aged students in reasoning with and about data. This paper reports findings from a foundational study to explore the natural strengths, skills, and strategies that upper elementary students bring to reasoning about data-centred problems.
The need for data literacy is an increasingly pressing priority in society, but most of the work in data-centred education has focused on developing skills at the middle school, secondary, and post-secondary levels, with little attention on the potential for engaging elementary-aged students in reasoning with and about data. This paper reports findings from a foundational study to explore the natural strengths, skills, and strategies that upper elementary students bring to reasoning about data-centred problems.
The need for data literacy is an increasingly pressing priority in society, but most of the work in data-centred education has focused on developing skills at the middle school, secondary, and post-secondary levels, with little attention on the potential for engaging elementary-aged students in reasoning with and about data. This paper reports findings from a foundational study to explore the natural strengths, skills, and strategies that upper elementary students bring to reasoning about data-centred problems.
The need for data literacy is an increasingly pressing priority in society, but most of the work in data-centred education has focused on developing skills at the middle school, secondary, and post-secondary levels, with little attention on the potential for engaging elementary-aged students in reasoning with and about data. This paper reports findings from a foundational study to explore the natural strengths, skills, and strategies that upper elementary students bring to reasoning about data-centred problems.
Despite interest in how students’ implicit theories—their growth and fixed mindsets about their own learning—affect students as learners, relatively little research on mindset has looked at teachers as learners. This study explores elementary teachers’ implicit theories about the malleability of mathematics intelligence and teaching ability. It also examines how implicit theories of learning relate to teacher noticing, a construct that has been linked to teachers’ classroom practice and their students’ learning outcomes.
Despite interest in how students’ implicit theories—their growth and fixed mindsets about their own learning—affect students as learners, relatively little research on mindset has looked at teachers as learners. This study explores elementary teachers’ implicit theories about the malleability of mathematics intelligence and teaching ability. It also examines how implicit theories of learning relate to teacher noticing, a construct that has been linked to teachers’ classroom practice and their students’ learning outcomes.
This counterstory (Delgado, 1989; Martinez, 2020) is based on field notes (Oct. 19 & Nov. 1, 2022) from our collective’s ethnographic project working with upper elementary Latiné learners and their transition to middle school mathematics. We see counterstories as a creative endeavor helping us in exploring the experiences of Latiné learners’ mathematics and our own narratives of navigating the whiteness of schools (see e.g., Cordero-Siy & Gómez Marchant, 2023; Gómez Marchant & Cordero-Siy, 2022).
This counterstory (Delgado, 1989; Martinez, 2020) is based on field notes (Oct. 19 & Nov. 1, 2022) from our collective’s ethnographic project working with upper elementary Latiné learners and their transition to middle school mathematics.
Purpose
Arts-integration is a promising approach to building students’ abilities to create and critique arguments with data, also known as informal inferential reasoning (IIR). However, differences in disciplinary practices and routines, as well as school organization and culture, can pose barriers to subject integration. The purpose of this study is to describe synergies and tensions between data science and the arts, and how these can create or constrain opportunities for learners to engage in IIR.
Purpose
Arts-integration is a promising approach to building students’ abilities to create and critique arguments with data, also known as informal inferential reasoning (IIR). However, differences in disciplinary practices and routines, as well as school organization and culture, can pose barriers to subject integration. The purpose of this study is to describe synergies and tensions between data science and the arts, and how these can create or constrain opportunities for learners to engage in IIR.
Purpose
Arts-integration is a promising approach to building students’ abilities to create and critique arguments with data, also known as informal inferential reasoning (IIR). However, differences in disciplinary practices and routines, as well as school organization and culture, can pose barriers to subject integration. The purpose of this study is to describe synergies and tensions between data science and the arts, and how these can create or constrain opportunities for learners to engage in IIR.
