Teaching with Data: Context and Resources Sean Fox, SERC Carleton College.

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Presentation transcript:

Teaching with Data: Context and Resources Sean Fox, SERC Carleton College

Growth of Science and Education Overall spending on Science research (and associated acronym space) grew by an order of magnitude following Sputnik (NSF, NASA, NIH, etc, etc, etc, etc) 1960’s curricular reform--even earth science got attention: ESCP–Earth Science Curriculum Project Percentage of year olds as college graduates % % Curriculum reform target (or at least hit) “best and brightest”

Science Education Reform Shaping the Future Revolution National Science Education Standards Science for All Americans htm Pathways to Progress s.pdf/ DLESE Community Plan al_secure.pdf

NSDL Workshop Report What do we mean by data? Why is using data important? How do we do it? What do we know about how well this works? What are the implications for digital libraries and data providers ?

What do we mean by data? Processed vs raw Model vs observation Images vs digital underpinnings Student collected On-line data sets

Why is teaching with data important ? Real world complex problems Use scientific methods Critically evaluate validity of data and strength of conclusions Quantitative skills, technical methods, scientific concepts; Communication skills Values and ethics of working with data

What is range of current practices? To illustrate concepts or ideas To enable student investigations: Students collect and interpret their own data often in the context of a larger data set or model Students use existing data sets to answer questions, often asking their own new questions Students collect data, develop a model of processes at work, and test the relationship between model predictions and observed data

Why does it work? Wisdom from Learning Science Learning is additive, it builds on current understanding Students must be engaged to learn To develop competence students must: Have a deep foundation of factual knowledge Understand ideas in the context of conceptual framework Organize knowledge in ways that facilitate retrieval and application How People Learn (NRC, 2000)

Teaching Challenges Presenting data with analysis tools that can be effectively mastered in the time available Designing learning activities to match the level of student expertise with data analysis and critical thinking Creating assessments that capture learning beyond factual recall. Finding and/or preparing suitable data can be time consuming or difficult particularly if working out of field

Resources for Educators Using Data in the Classroom Portal: data, tools, activities and pedagogy Starting Point Teaching Entry Level Geoscience: Teaching with Data; Teaching with Models Earth Exploration Toolbook: Step by step instructions Bringing Research on Learning to the Geosciences: bibliography, on-going research efforts serc.carleton.edu

Criteria for Effective Educational Use Students can Reliably find and access data easily Ascertain quality of data Manipulate data to answer questions Find information on relevance Sharing Data for Educational Use Discovery Review