Educational Technology

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.

Supporting Secondary Students’ Understanding of Earth’s Climate System and Global Climate Change Using EzGCM: A Cross-Sectional Study

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 (NGSS Lead States, 2013).

Author/Presenter

Silvia-Jessica Mostacedo-Marasovic

Amanda A. Olsen

Cory T. Forbes

Year
2023
Short Description

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.

Supporting Secondary Students’ Understanding of Earth’s Climate System and Global Climate Change Using EzGCM: A Cross-Sectional Study

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 (NGSS Lead States, 2013).

Author/Presenter

Silvia-Jessica Mostacedo-Marasovic

Amanda A. Olsen

Cory T. Forbes

Year
2023
Short Description

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.

Student Outcomes of Teaching About Socio-scientific Issues in Secondary Science Classrooms: Applications of 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.

Author/Presenter

Kimberly Carroll Steward

David Gosselin

Mark Chandler

Cory T. Forbes

Year
2023
Short Description

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).

Student Outcomes of Teaching About Socio-scientific Issues in Secondary Science Classrooms: Applications of 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.

Author/Presenter

Kimberly Carroll Steward

David Gosselin

Mark Chandler

Cory T. Forbes

Year
2023
Short Description

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).

Classroom-Based STEM Assessment: Contemporary Issues and Perspectives

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Author/Presenter

Christopher J. Harris, Eric Wiebe, Shuchi Grover, James W. Pellegrino, Eric Banilower, Arthur Baroody, Erin Furtak, Ryan “Seth” Jones, Leanne R. Ketterlin-Geller, Okhee Lee, Xiaoming Zhai

Year
2023
Short Description

This report takes stock of what we currently know as well as what we need to know to make classroom assessment maximally beneficial for the teaching and learning of STEM subject matter in K–12 classrooms.

Myths, Mis- and Preconceptions of Artificial Intelligence: A Review of the Literature

Artificial Intelligence (AI) is prevalent in nearly every aspect of our lives. However, recent studies have found a significant amount of confusion and misunderstanding surrounding AI. To develop effective educational programs in the field of AI, it is vital to examine and understand learners' pre- and misconceptions as well as myths about AI. This study examined a corpus of 591 studies.

Author/Presenter

Arne Bewersdorff

Xiaoming Zhai

Jessica Roberts

Claudia Nerdel

Lead Organization(s)
Year
2023
Short Description

Artificial Intelligence (AI) is prevalent in nearly every aspect of our lives. However, recent studies have found a significant amount of confusion and misunderstanding surrounding AI. To develop effective educational programs in the field of AI, it is vital to examine and understand learners' pre- and misconceptions as well as myths about AI. This study examined a corpus of 591 studies.

ChatGPT for Next Generation Science Learning

This article pilots ChatGPT in tackling the most challenging part of science learning and found it successful in automation of assessment development, grading, learning guidance, and recommendation of learning materials.

Zhai, X. (2023). ChatGPT for Next Generation Science Learning | XRDS: Crossroads, 29(3), 42-46. https://doi.org/10.1145/3589649

Author/Presenter
Xiaoming Zhai
Lead Organization(s)
Year
2023
Short Description

This article pilots ChatGPT in tackling the most challenging part of science learning and found it successful in automation of assessment development, grading, learning guidance, and recommendation of learning materials.