Science

Elementary Teachers’ Knowledge of Using Language as an Epistemic Tool in Science Classrooms: A Case Study

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.

Author/Presenter

Qi Si

Jee K. Suh

Jale Ercan-Dursun

Brian Hand

Gavin W. Fulmer

Year
2024
Short Description

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.

Can Generative AI and ChatGPT Outperform Humans on Cognitive-Demanding Problem-Solving Tasks in Science?

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.

Author/Presenter

Xiaoming Zhai

Matthew Nyaaba

Wenchao Ma

Lead Organization(s)
Year
2024
Short Description

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.

Can Generative AI and ChatGPT Outperform Humans on Cognitive-Demanding Problem-Solving Tasks in Science?

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.

Author/Presenter

Xiaoming Zhai

Matthew Nyaaba

Wenchao Ma

Lead Organization(s)
Year
2024
Short Description

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.

Understanding the Effect of Differences in Prior Knowledge on Middle School Students’ Collaborative Interactions and Learning

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.

Author/Presenter

Sadhana Puntambekar

Dana Gnesdilow

Sinan Yavuz

Year
2023
Short Description

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.

Teachers’ Use and Adaptation of a Model-based Climate Curriculum: A Three-Year Longitudinal Study

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.

Author/Presenter

Kimberly Carroll Steward

David Gosselin

Devarati Bhattacharya

Mark Chandler

Cory T. Forbes

Year
2024
Short Description

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.

Teachers’ Use and Adaptation of a Model-based Climate Curriculum: A Three-Year Longitudinal Study

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.

Author/Presenter

Kimberly Carroll Steward

David Gosselin

Devarati Bhattacharya

Mark Chandler

Cory T. Forbes

Year
2024
Short Description

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.

Learning to Listen: Cultivating Pre-Service Teachers’ Attunement to Student Thinking

Reform efforts in science and mathematics education highlight students’ experiences and sensemaking repertoires as valuable resources for instruction. Yet, there is much to learn about how to cultivate teachers’ capacity for eliciting, understanding, and responding to students’ contributions. We argue that the first step of this cultivation is teachers’ learning to listen: to attune and attend to the novel ways that students make sense of scientific phenomena and the natural world.

Author/Presenter

Shannon G. Davidson

Lama Z. Jaber

Allison Metcalf

Year
2024
Short Description

Reform efforts in science and mathematics education highlight students’ experiences and sensemaking repertoires as valuable resources for instruction. Yet, there is much to learn about how to cultivate teachers’ capacity for eliciting, understanding, and responding to students’ contributions. We argue that the first step of this cultivation is teachers’ learning to listen: to attune and attend to the novel ways that students make sense of scientific phenomena and the natural world.

Fostering Expansive and Connective Sensemaking with Preservice Secondary Science Teachers

Preservice secondary science teachers often experience science learning in narrow and marginalizing ways in their science preparation. These experiences cause harm, particularly for preservice teachers of color. They also limit the disciplinary resources they can develop for later teaching science in ways that value and sustain their students' ways of knowing and being in the world. Our research explores possibilities for cultivating new spaces for preservice secondary science teachers to engage in science.

Author/Presenter

Jessica Watkins

Natalie A. De Lucca

Serena R. Pao

Lead Organization(s)
Year
2023
Short Description

Our research explores possibilities for cultivating new spaces for preservice secondary science teachers to engage in science. In a content-focused education course, we designed for and studied preservice teachers' engagement in expansive and connective sensemaking, incorporating heterogeneity, power, and historicity in pursuits of explanatory accounts of the natural world. In this article, we examined how this course design can support preservice teachers to attune to heterogeneity in ways of knowing in science and to connect to identity and historicity in scientific sensemaking.

Why Do Teachers Vary in Their Instructional Change During Science PD? The Role of Noticing Students in an Iterative Change Process

Instructional shifts required by equitable, reform-based science instruction are challenging, especially in the elementary context. Such shifts require professional development (PD) that supports teacher internalization of new pedagogical strategies as well as changes in beliefs about how students learn. Because of this complexity, many PD programs struggle to foster lasting pedagogical shifts, necessitating further investigation into why some teachers successfully embrace reform practices while others do not.

Author/Presenter

Linda Preminger

Kathryn N. Hayes

Christine L. Bae

Dawn O'Connor

Year
2024
Short Description

This qualitative study uses a nonlinear, iterative model of teacher learning (Interconnected Model of Professional Growth; Clarke & Hollingsworth, 2002) alongside professional noticing to help understand why elementary teachers in science PD differentially make sense of and internalize new pedagogies.

Why Does Teacher Learning Vary in Professional Development? Accounting for Organisational Conditions

Professional development providers often struggle with how some teachers take up and internalise new instructional practices while others have difficulty implementing new ideas and strategies. Teacher personal characteristics account for only part of this differentiation in learning, and there are unanswered questions regarding how organisational conditions shape teacher learning in professional development (PD). To address these questions, we examined U.S. elementary teachers’ learning and change in a science professional development project.

Author/Presenter

Kathryn N. Hayes

Linda Preminger

Christine L. Bae

Year
2023
Short Description

Professional development providers often struggle with how some teachers take up and internalise new instructional practices while others have difficulty implementing new ideas and strategies. Teacher personal characteristics account for only part of this differentiation in learning, and there are unanswered questions regarding how organisational conditions shape teacher learning in professional development (PD). To address these questions, we examined U.S. elementary teachers’ learning and change in a science professional development project.