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Learning from Model-Produced Graphs in a Climate Change Science Class

This study explores the role of graphs in learning climate science and promoting scientific reasoning skills. It investigates the cognitive aspects of graph comprehension and the ability to deal with quantitative information. The study also examines the effectiveness of model-based inquiry courses and multimedia displays in enhancing students' understanding and interpretation of graphs.

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Learning from Model-Produced Graphs in a Climate Change Science Class

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  1. Learning from Model-Produced Graphs in a Climate Change Science Class Catherine Gautier Geography Department UC Santa Barbara

  2. Graphs • Graphs are commonly used in geoscience courses • Graphs help students understand geoscience, quantitative information and scientific reasoning Some students have difficulties comprehending information depicted in some geoscience graphs Should students be at ease with simple visual representations like graphs, maps, charts before more sophisticated visual representations such as animations or 3-D representations are presented to them?

  3. Communicate relevant quantitative information Promote thinking about data and scientific information What is the role of graphs in learning climate science Cognitive aspects Comprehension Scientific Reasoning Dealing with quantitative information

  4. Graphs and Scientific Reasoning • Ability to think about data by relating them to: theories, conclusions, hypotheses, explanations • What kind of tasks promote students’ ability to explain data and relate data to theories and hypotheses? • Ability to ask the “right” question • Do certain kinds of graphs support reasoning about the “right” questions? • Can graphs highlight questions students might ask and therefore promote scientific reasoning skills?

  5. Experiment and Data CollectionModel-based Inquiry Course • Student-generated scientific question and experimental design • Student-performed experiment with model • Graphs and data tables generation • Graphs integration into a scientific reasoning • Students- produced graphics analyzed to evaluate • students’ ability to comprehend graphs and interpret quantitative information (display quantitative skills) • Graphs’ role in helping students’ thinking about data and in promoting scientific inquiry (asking “right” question)

  6. Multimedia Display Multimedia display • Visual and textual • Interaction of task and graphic format • Complementarity of graphical presentation forms: integrative with graph and separative with table Visual characteristics of graphic display • 2-D format • Line graph (suggests continuity of vertical distribution and provide trend) • Multiple lines for comparisons • Simple mapping between referent (flux) and variable altitude, wavelength, time, sun angle Table • To get single point value (surface) • To extract data for additional (external) visualization Text • To explain how model works • To describe inputs and outputs

  7. Experiment and Data CollectionModel-based Inquiry Course • Student-generated scientific question and experimental design • Student-performed experiment with model • Graphs and data tables generation • Graphs integration into scientific reasoning • Students-produced graphics analyzed to evaluate • Students’ ability to interpret quantitative information (display quantitative skills) • Graphs’ role in helping students’ thinking about data and in promoting scientific inquiry (asking “right” question)

  8. Analysis of Graphs • Two types of graphs • model-produced • student-produced (advanced investigations) • Graph interpretation: graphs and quantitative skills • Graphs and scientific reasoning: analytical representation of results for theory establishment or verification • Graphs and scientific reasoning: asking “right” question

  9. Student-Produced Graphs From sensitivity experiments Data extraction from table produced by a series of runs From one experiment

  10. Analysis of Graphs • Two types of graphs • model-produced • student-produced (advanced investigations) • Graph interpretation: graphs and quantitative skills • Graphs and scientific reasoning: analytical representation of results for theory establishment or verification • Graphs and scientific reasoning: asking “right” question

  11. Graphs Interpretation and Quantitative Skills

  12. Analysis of Graphs • Two types of graphs • model-produced • student-produced (advanced investigations) • Graph interpretation: graphs and quantitative skills • Graphs and scientific reasoning: analytical representation of results for theory establishment or verification • Graphs and scientific reasoning: asking “right” question (talk on Thursday morning)

  13. Theory Verification instructor Theory Establishment Theory Verification or Establishment Theory Verification Noisy data from model?

  14. Summary • Importance of repetitive nature of tasks and graphs produced to graph comprehension • Development of graph schema for lower performing students • Graph interpretation and quantitative skills • Required quantitative skills related to the use of graphs well grasped • Other quantitative skills only employed by best students • Graphs allowed students to visualize and communicate quantitative information and this promoted thinking about data • Through the interaction between graphs and quantitative skills, the class activities supported the application and development of scientific reasoning including • theory validation or establishment, hypothesis testing • Asking valid scientific questions

  15. Future Research • Assessment • Scientific reasoning cognitive level in climate change science • Students’ graph comprehension/schema prior and after class • Interaction between graph schema and content knowledge • Develop series of focused questions • What are the main characteristics of the “relevant” information that need to be communicated in climate change? What makes a graph better or worse at communicating relevant quantitative information in climate change? • How do students comprehend graphs and what are the factors that influence students’ interpretations? • How might different ways in which data are manipulated promote thinking about data? • How do individual differences in graph reading skills and domain knowledge influence the kinds of interpretations that students give graphs presented to them? • Develop customized tools for assessment • Develop multiple assessment approach and Integrate results from different tools • For each question develop appropriate tool (questionnaires, video and audio recording, analysis of written and presented work, concept maps)

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