Curriculum Design Patterns for Teaching with Authentic Geoscience Data
Oral Presentation
A "design pattern" is a template for organizing and sequencing instruction that can be applied across multiple topics or concepts. For example, "think-pair-share" is a familiar and trusted design pattern for classroom instruction. Effective design patterns challenge and exercise human capacities for perception and cognition, and may also draw on social construction of knowledge within small groups or full classes.
We are working to identify effective design patterns for engaging students in analyzing and interpreting complex Earth and environmental datasets in the context of challenging, authentic problems. In this presentation, we will share our analysis of instructional approaches that have been used in instructional materials developed by the InTeGrate project. These undergraduate-level materials cover a wide range of topics, but all are required to involve the use of "authentic credible geoscience data" and to engage with "geoscience-related grand challenge(s) facing society."
The design patterns we have identified to date are as follows: In "Data Puzzles," the curriculum developer selects snippets of data that embody an important Earth phenomenon with a high insight-to-effort ratio. Students view static data visualizations, and answer a series of guiding questions, which ramp up from decoding to explanatory insight. In "Nested Data Sets," students collect and interpret a local data set, and then interpret an encompassing professionally collected dataset that expands beyond the student-collected data time and/or space. In "Predict-Observe-Explain," students predict what data from the system under consideration would look like under various conditions, based on a conceptual, physical or computational model. Then they access a database and compare their prediction to data. In "Hypothesis Array," students are provided with text descriptions or sketches of alternative working hypotheses for a process or structure. They access a database of relevant data, seeking to assemble evidence in support of one of the hypotheses.
We are working to identify effective design patterns for engaging students in analyzing and interpreting complex Earth and environmental datasets in the context of challenging, authentic problems. In this presentation, we will share our analysis of instructional approaches that have been used in instructional materials developed by the InTeGrate project. These undergraduate-level materials cover a wide range of topics, but all are required to involve the use of "authentic credible geoscience data" and to engage with "geoscience-related grand challenge(s) facing society."
The design patterns we have identified to date are as follows: In "Data Puzzles," the curriculum developer selects snippets of data that embody an important Earth phenomenon with a high insight-to-effort ratio. Students view static data visualizations, and answer a series of guiding questions, which ramp up from decoding to explanatory insight. In "Nested Data Sets," students collect and interpret a local data set, and then interpret an encompassing professionally collected dataset that expands beyond the student-collected data time and/or space. In "Predict-Observe-Explain," students predict what data from the system under consideration would look like under various conditions, based on a conceptual, physical or computational model. Then they access a database and compare their prediction to data. In "Hypothesis Array," students are provided with text descriptions or sketches of alternative working hypotheses for a process or structure. They access a database of relevant data, seeking to assemble evidence in support of one of the hypotheses.