Elementary

The present study focuses on examining transitions in elementary pre-service teachers (PSTs)’ understanding of, and skills in, leading argumentation-focused discussions in mathematics during participation in a sequence of three different practice-based activities, collectively referred to as the Online Practice Suite (OPS). We will examine 14 PSTs’ responses to post-activity surveys targeting their understanding of argumentation-focused discussions and emotional experiences, over the course of a single semester.

Slides from a pre-conference workshop at the 2021 National Association for Research in Science Teaching Annual Meeting, Orlando, FL.

In this study, our team developed and is studying the use of an Online Practice Suite (OPS) composed of a coordinated and scaffolded collection of three practice-based online simulations designed to support the development of preservice teachers' (PSTs’) abilities, skills, beliefs, and understanding around one ambitious teaching practice within mathematics and science: facilitating discussions that engage students in argumentation.

Background and Context
Students’ self-efficacy toward computing affect their participation in related tasks and courses. Self-efficacy is likely influenced by students’ initial experiences and exposure to computer science (CS) activities. Moreover, student interest in a subject likely informs their ability to effectively regulate their learning in that domain. One way to enhance interest in CS is through using collaborative pair programming.

Background and Context
Students’ self-efficacy toward computing affect their participation in related tasks and courses. Self-efficacy is likely influenced by students’ initial experiences and exposure to computer science (CS) activities. Moreover, student interest in a subject likely informs their ability to effectively regulate their learning in that domain. One way to enhance interest in CS is through using collaborative pair programming.

The COVID-19 pandemic shifted many U.S. schools from in-person to remote instruction. While collaborative CS activities had become increasingly common in classrooms prior to the pandemic, the sudden shift to remote learning presented challenges for both teachers and students in implementing and supporting collaborative learning. Though some research on remote collaborative CS learning has been conducted with adult learners, less has been done with younger learners such as elementary school students.

The COVID-19 pandemic shifted many U.S. schools from in-person to remote instruction. While collaborative CS activities had become increasingly common in classrooms prior to the pandemic, the sudden shift to remote learning presented challenges for both teachers and students in implementing and supporting collaborative learning. Though some research on remote collaborative CS learning has been conducted with adult learners, less has been done with younger learners such as elementary school students.

In this study, we investigated how an experienced fourth-grade teacher responded to her students’ thinking as part of her teacher noticing practice in a formative assessment context. Our primary purpose in doing this work was to decompose the responding component of teacher noticing and use our findings to present an emerging framework characterizing the multidimensional nature of this practice. We present two key outcomes based on the findings of this work. First, we show how a formative assessment context situated outside of instruction can engage teachers in practice-based noticing.

Lee, H.S., Mojica, G. M., & Thrasher, E. (2022). Digging into data: Illustrating an investigative process. Statistics Teacher.

With a call for schools to infuse data across the curriculum, many are creating curricula and examining students’ thinking in data-intensive problems. As the discipline of statistics education broadens to data science education, there is a need to examine how practices in data science can inform work in K-12. We synthesize literature about statistics investigation processes, data science as a field and practices of data scientists. Further, we provide results from an ethnographic and interview study of the work of data scientists.