Climate Change

Climate Education in Secondary Science: Comparison of Model-based and Non-Model-based Investigations of Earth’s Climate

In this mixed method study, we analyse the effectiveness of two pedagogical approaches – one model-based and another non-model-based – for developing secondary students’ understanding of the phenomenon of increase in Earth’s average surface temperatures, a core dimension of global climate change (GCC). Building on past research on teaching and learning about Earth’s climate, we use an Evidence-Based Reasoning framework to assess student tasks and interviews from a 3-week, project-developed, model-based curriculum.

Author/Presenter

Devarati Bhattacharya

Kim Carroll Steward

Cory T. Forbes

Lead Organization(s)
Year
2021
Short Description

In this mixed method study, we analyse the effectiveness of two pedagogical approaches – one model-based and another non-model-based – for developing secondary students’ understanding of the phenomenon of increase in Earth’s average surface temperatures, a core dimension of global climate change (GCC).

Wildfire Risks & Impacts

The Wildfire Module asks students to consider the question, "How will wildfire risks and impacts change over the next 100 years?" This five-activity module helps students build an understanding of the variables that influence fire spread rate and intensity, the risks that wildfires bring to people and their communities, and the impact of climate change through focused case studies and interactions with the Wildfire Explorer model. 

Author/Presenter

Amy Pallant

Lead Organization(s)
Year
2021
Short Description

The Wildfire Module asks students to consider the question, "How will wildfire risks and impacts change over the next 100 years?" This five-activity module helps students build an understanding of the variables that influence fire spread rate and intensity, the risks that wildfires bring to people and their communities, and the impact of climate change through focused case studies and interactions with the Wildfire Explorer model.

Easy Global Climate Modeling (EzGCM) Toolkit

EzGCM is a climate modeling toolkit that allows students to examine climate change using the same tools and following the same scientific processes as climate scientists.

Author/Presenter

The EzGCM Team

Year
2019
Short Description

EzGCM is a climate modeling toolkit that allows students to examine climate change using the same tools and following the same scientific processes as climate scientists.

Easy Global Climate Modeling (EzGCM) Toolkit

EzGCM is a climate modeling toolkit that allows students to examine climate change using the same tools and following the same scientific processes as climate scientists.

Author/Presenter

The EzGCM Team

Year
2019
Short Description

EzGCM is a climate modeling toolkit that allows students to examine climate change using the same tools and following the same scientific processes as climate scientists.

CHANGE Curriculum

CHANGE provides a website, https://climatechange.usf.edu/ which includes nine units from a marine sciences course, complete with lesson plans involving inexpensive, easy to find materials, Powerpoints, downloadable files and an interactive web-based eBook with simulation-based games.

Author/Presenter

The CHANGE Team

Lead Organization(s)
Year
2018
Short Description

Nine units for high school-level Marine Science classes: (1) Ocean Exploration, (2) Marine Geology, (3) Marine Chemistry, (4) Estuaries, (5) Marine Physics, (6) Populations: Producers, (7) Populations: Invertebrates, (8) Populations: Vertebrates and (9) Capstone: Apollo Beach. All of these materials can be potentially repurposed for other high school science courses. The units include lesson plans involving inexpensive, easy to find materials, Powerpoints, downloadable files and an interactive web-based eBook with simulation-based games. Teachers can view the top level, outline of the CHANGE curriculum web-page: https://climatechange.usf.edu/. However, to access the actual materials, they will need to register to get a username, by emailing Dr. Glenn Smith: glenns@usf.edu and metinbesalti@mail.usf.edu

Hurricane Risk & Impact

Students will use the Hurricane Explorer model to explain and predict how the path and strength of a hurricane can change, investigate real-world case studies on the risk and impact of hurricanes, and explore the effect of rising global temperatures on hurricanes.

Author/Presenter

Amy Pallant

Lead Organization(s)
Year
2020
Short Description

Students will use the Hurricane Explorer model to explain and predict how the path and strength of a hurricane can change, investigate real-world case studies on the risk and impact of hurricanes, and explore the effect of rising global temperatures on hurricanes.

The Effect of Automated Feedback on Revision Behavior and Learning Gains in Formative Assessment of Scientific Argument Writing

Application of new automated scoring technologies, such as natural language processing and machine learning, makes it possible to provide automated feedback on students' short written responses. Even though many studies investigated the automated feedback in the computer-mediated learning environments, most of them focused on the multiple-choice items instead of the constructed response items. This study focuses on the latter and investigates a formative feedback system integrated into an online science curriculum module teaching climate change.

Author/Presenter

Mengxiao Zhu

Ou Lydia Liu

Hee-Sun Lee

Lead Organization(s)
Year
2019
Short Description

This study investigates a formative feedback system integrated into an online science curriculum module teaching climate change.

Appendix 5 of the California Science Framework: Computer Science in Science

This appendix of the California Science Framework focuses on Computer Science in Science.

Citation: Lee, I.2016. California Science Framework. Appendix 5: Computer Science in Science  Retrieved on 11-15-16 at http://www.cde.ca.gov/ci/sc/cf/scifw2nd60daypubreview.asp

Author/Presenter

Irene Lee

Lead Organization(s)
Year
2016
Short Description

This appendix of the California Science Framework focuses on Computer Science in Science.

Constructing Scientific Arguments Using Evidence from Dynamic Computational Climate Models

Pallant, A., & Lee H.-S. (2015). Constructing scientific arguments using evidence from dynamic computational climate models. Journal of Science Education and Technology. 24 (2-3) 378-395. doi 10.1007/s10956-014-9499-3.

Author/Presenter

Amy Pallant

Hee-Sun Lee

Lead Organization(s)
Year
2014
Short Description

Modeling and argumentation are two important scientific practices students need to develop throughout school years. In this paper, we investigated how middle and high school students (N=512) construct a scientific argument based on evidence from computational models with which they simulated climate change. We designed scientific argumentation tasks with three increasingly complex dynamic climate models. Each scientific argumentation task consisted of four parts: multiple-choice claim, open ended explanation, five-point Likert scale uncertainty rating, and open-ended uncertainty rationale.
We coded 1,294 scientific arguments in terms of a claim’s consistency with current scientific consensus, whether explanations were model based or knowledge based and categorized the sources of uncertainty (personal vs. scientific). We used chi-square and ANOVA tests to identify significant patterns. Results indicate that (1) a majority of students incorporated models as evidence to support their claims, (2) most students used model output results shown on graphs to confirm their claim rather than to explain simulated molecular processes, (3) students’ dependence on model results and their uncertainty rating diminished as the dynamic climate models became more and more complex, (4) some students’ misconceptions interfered with observing and interpreting model results or simulated processes, and (5) students’ uncertainty sources reflected more frequently on their assessment of personal knowledge or abilities related to the tasks than on their critical examination of scientific evidence resulting from models. These findings have implications for teaching and research related to the integration of scientific argumentation and modeling practices to address complex Earth systems.