Educational Technology

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.

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.

Foregrounding climate education in formal science learning environments provides students with opportunities to develop critical climate-related knowledge and skills. However, research has shown many challenges to teaching and learning about Earth’s climate and global climate change (GCC). This longitudinal study aims to establish how secondary science teachers, over time, implement model-based climate curricula in support of students’ climate and GCC education by utilizing EzGCM. The model (EzGCM) is a data-driven, computer-based climate modeling tool use to explore global climate data.

Foregrounding climate education in formal science learning environments provides students with opportunities to develop critical climate-related knowledge and skills. However, research has shown many challenges to teaching and learning about Earth’s climate and global climate change (GCC). This longitudinal study aims to establish how secondary science teachers, over time, implement model-based climate curricula in support of students’ climate and GCC education by utilizing EzGCM. The model (EzGCM) is a data-driven, computer-based climate modeling tool use to explore global climate data.

Global climate change (GCC) is one of the greatest challenges of our age and a highly significant socio-scientific issue (SSI). Developing secondary students’ understanding about the Earth’s climate and GCC is critical for empowering future citizens and a key focus of the Next Generation Science Standards. In this cross-sectional study, we investigated secondary students’ evidence-based reasoning about GCC grounded in a curricular intervention involving the use of a data-driven, computer-based global climate model—EzGCM—over 3 years with four teachers who adapted the module in their own courses.

Global climate change (GCC) is one of the greatest challenges of our age and a highly significant socio-scientific issue (SSI). Developing secondary students’ understanding about the Earth’s climate and GCC is critical for empowering future citizens and a key focus of the Next Generation Science Standards. In this cross-sectional study, we investigated secondary students’ evidence-based reasoning about GCC grounded in a curricular intervention involving the use of a data-driven, computer-based global climate model—EzGCM—over 3 years with four teachers who adapted the module in their own courses.

Science education literature has highlighted socio-scientific issues (SSI) as an effective pedagogy for teaching science in a social and political context. SSI links science education and real-world problems to engage students in real-world issues, making it ideal for teaching global climate change (GCC). Additionally, technological advances have created a unique opportunity for teaching climate by making previously inaccessible computer-based computational models and data visualizations accessible to the typical K-12 learning environment. Here, we present the findings from the 2020–2021 school year pre-/post-implementation of a 3-week, model-based climate education curriculum module (EzGCM).

Science education literature has highlighted socio-scientific issues (SSI) as an effective pedagogy for teaching science in a social and political context. SSI links science education and real-world problems to engage students in real-world issues, making it ideal for teaching global climate change (GCC). Additionally, technological advances have created a unique opportunity for teaching climate by making previously inaccessible computer-based computational models and data visualizations accessible to the typical K-12 learning environment. Here, we present the findings from the 2020–2021 school year pre-/post-implementation of a 3-week, model-based climate education curriculum module (EzGCM).