High

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.

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.

Exploring the Noticing of Science Teachers: What Teachers' Notice and Using Video to Capture Teacher Knowledge

Knowing how science teachers develop their professional knowledge has been a challenge. One potential way to determine the professional knowledge of teachers is through videos. In the study described here, the authors recruited 60 elementary and secondary science teachers, showed them one of two 10-min videos, and recorded and analyzed their comments when watching the videos. The coding focused on their noticing of student learning, teacher's teaching, types of teaching practices, and the use of interpretative frames.

Author/Presenter

Julie A. Luft

Yuxi Huang

Harleen Singh

Hatice Ozen-Tasdemir

Joe DeLuca

Shelby Watson

Elizabeth Ayano

Brooke A. Whitworth

Lead Organization(s)
Year
2023
Short Description

Knowing how science teachers develop their professional knowledge has been a challenge. One potential way to determine the professional knowledge of teachers is through videos. In the study described here, the authors recruited 60 elementary and secondary science teachers, showed them one of two 10-min videos, and recorded and analyzed their comments when watching the videos.

Comparing Optimization Practices Across Engineering Learning Contexts Using Process Data

Despite an increasing focus on integrating engineering design in K-12 settings, relatively few studies have investigated how to support students to engage in systematic processes to optimize the designs of their solutions. Emerging learning technologies such as computational models and simulations enable rapid feedback to learners about their design performance, as well as the ability to research how students may or may not be using systematic approaches to the optimization of their designs.

Author/Presenter

James P. Bywater

Tugba Karabiyik

Alejandra Magana

Corey Schimpf

Ying Ying Seah 

Year
2023
Short Description

Despite an increasing focus on integrating engineering design in K-12 settings, relatively few studies have investigated how to support students to engage in systematic processes to optimize the designs of their solutions. This study explored how middle school, high school, and pre-service students optimized the design of a home for energy efficiency, size, and cost using facets of fluency, flexibility, closeness, and quality.

Comparing Optimization Practices Across Engineering Learning Contexts Using Process Data

Despite an increasing focus on integrating engineering design in K-12 settings, relatively few studies have investigated how to support students to engage in systematic processes to optimize the designs of their solutions. Emerging learning technologies such as computational models and simulations enable rapid feedback to learners about their design performance, as well as the ability to research how students may or may not be using systematic approaches to the optimization of their designs.

Author/Presenter

James P. Bywater

Tugba Karabiyik

Alejandra Magana

Corey Schimpf

Ying Ying Seah 

Year
2023
Short Description

Despite an increasing focus on integrating engineering design in K-12 settings, relatively few studies have investigated how to support students to engage in systematic processes to optimize the designs of their solutions. This study explored how middle school, high school, and pre-service students optimized the design of a home for energy efficiency, size, and cost using facets of fluency, flexibility, closeness, and quality.

‘But, Is It Supposed to be a Straight Line?’ Scaffolding Students’ Experiences with Pressure Sensors and Material Resistance in a High School Biology Classroom

This case study examines how material resistance (limitations posed by the physical world) and graph interpretation intersected during a high school biology investigation using digital sensors. We use an extended episode from a small group to illustrate how, in an inquiry-based unit, measuring near the resolution limit of a sensor caused scaling issues in graphs.

Author/Presenter

Natalya St. Clair

A. Lynn Stephens

Hee-Sun Lee

Lead Organization(s)
Year
2023
Short Description

This case study examines how material resistance (limitations posed by the physical world) and graph interpretation intersected during a high school biology investigation using digital sensors.