Elementary

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.

Contemporary views on what students should learn increasingly emphasize that students need to acquire more than a base of knowledge; they need to acquire the skills and abilities to use such knowledge in dynamic and flexible ways. To be most effective, learning environments need assessments that are aligned to these perspectives. Using a principled design framework can help guide assessment development toward such targets. Even when using a framework, however, thorny design challenges may arise.

Contemporary views on what students should learn increasingly emphasize that students need to acquire more than a base of knowledge; they need to acquire the skills and abilities to use such knowledge in dynamic and flexible ways. To be most effective, learning environments need assessments that are aligned to these perspectives. Using a principled design framework can help guide assessment development toward such targets. Even when using a framework, however, thorny design challenges may arise.

We explored the semiotic choices children in grades 1–6 made that nurtured embodied, dramatizing performances in science classes at urban public schools, serving predominantly students of color in a large US city. We studied how such choices in school and home settings (when instruction was remote during the COVID-19 pandemic) were implicated in the children’s knowledge and identity construction and related to available resources and positionings.

Language is a fundamental tool for learning science. This study highlights the importance of teacher knowledge in utilising language as a tool for knowledge generation in the classrooms. This case study examines elementary teachers’ development of declarative, procedural, and epistemic knowledge related to using language, particularly focusing on how a three-year professional development programme centred around the Science Writing Heuristic (SWH) approach influences the development of these knowledge bases.

Teacher-facilitated whole-class conversations can help elementary students apply the full power of the NGSS science and engineering practices to an engineering design process. In this article we describe and provide examples for five kinds of Design Talks. Each type of Design Talk centers on a different framing question and is facilitated by specific prompts that help students voice their ideas and make connections to others' ideas.

This study aimed to examine an assumption regarding whether generative artificial intelligence (GAI) tools can overcome the cognitive intensity that humans suffer when solving problems. We examine the performance of ChatGPT and GPT-4 on NAEP science assessments and compare their performance to students by cognitive demands of the items. Fifty-four 2019 NAEP science assessment tasks were coded by content experts using a two-dimensional cognitive load framework, including task cognitive complexity and dimensionality.

This study aimed to examine an assumption regarding whether generative artificial intelligence (GAI) tools can overcome the cognitive intensity that humans suffer when solving problems. We examine the performance of ChatGPT and GPT-4 on NAEP science assessments and compare their performance to students by cognitive demands of the items. Fifty-four 2019 NAEP science assessment tasks were coded by content experts using a two-dimensional cognitive load framework, including task cognitive complexity and dimensionality.

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.