Science

The authors are developing a model for rural science teacher professional development, building teacher expertise and collaboration and creating high-quality science lessons: technology-mediated lesson study (TMLS).

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.

In this paper, we describe three challenges (conflict between multiple dimensions of science proficiency, authentic data, and grade-appropriate graphing tools) that we faced when designing for a specific Next Generation Science Standard, and the theoretical and design principles that guided us as we ideated design solutions. Through these designs we maintained alignment to our multidimensional assessment targets, a critical component of our larger assessment validity argument.

In this paper, we describe three challenges (conflict between multiple dimensions of science proficiency, authentic data, and grade-appropriate graphing tools) that we faced when designing for a specific Next Generation Science Standard, and the theoretical and design principles that guided us as we ideated design solutions. Through these designs we maintained alignment to our multidimensional assessment targets, a critical component of our larger assessment validity argument.

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.

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.

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.

We investigated how the level of variance in students’ prior knowledge may have influenced their collaborative interactions and science learning in small groups. We examined learning outcomes from 102 groups from seven science teachers’ classes and discourse from two contrasting groups: Homogeneous versus heterogeneous. We examined individual and group outcomes using hierarchical linear modeling (HLM) to explore the effect of membership in a homogeneous or heterogeneous group on students’ learning. We then used social network analyses (SNA) to identify any differences in interaction patterns between the two contrasting groups as they conducted multiple compost simulations. Finally, we examined students’ discussions in these groups to better understand their interactions.