1. PERFORMANCE-BASED ASSESSMENT IN GEOSCIENCES Mara Chen & Dan Harris Dept. of Geography and Geosciences Salisbury University ECLIPSE August 11 th, 2012

2. Real World Data in STEM Assessment Geosciences Project-based Assessments Classroom Model Identify and Define Learning Objectives Comprehensive Assessment Components Pre-assessment Evaluates prior knowledge and existing geoscience skillsets Baseline determination to evaluate learning gains Formative Assessment Evaluating student critical and analytical thinking during project implementation Summative Assessment Learning gains Internal and external evaluation

3. Geosciences Project-Based Example: Chesapeake Bay Health “Bringing the Earth into the Classroom” Rubric Areas Across Assessment Types Data Types of data Sources of data Contacts Data Analysis Spatial and temporal extent Temporal trends Interpretation Data Presentation Representations Applications Modeling

4. Data -

5. Pre-Assessment (Student Focused) What is your area of interest? (Project Clarification) Chesapeake Bay? Watershed? Urban vs. Rural What type of data are you looking for? (Project Planning) Water Land Atmosphere Population Maps Where do you find these data? (Project Resources) Local, State, Federal, Non-profits How do you obtain these data? web sites, phone numbers, contact person, address

6. Pre-Assessment Example Atmospheric Impact on Bay Health Weather data or climate data What are the differences? Where do you obtain weather data? Where do you obtain climate data? What time frame? What is regional extent? Analysis Quantitative or qualitative Quantitative – descriptive statistics, tabular, graphical representations (charts and maps) Qualitative – descriptions, interviews, photographs Presentation Oral or written (or both) Past, present, future (trends) “Ideal” Bay Artifacts What types of materials collected? How do you collect these?

7. Formative Assessment (Student Focused) Data Acquisition Evaluating appropriateness of data types and sources (Where, Who and How?) Data Analysis Alignment – data and type of analysis Sense-making – process of understanding results of analysis Data Presentation Geospatial skills employed – graphics production (maps, charts, tables) Delivery – oral presentation, paper, poster Prediction and extension – future, results application Artifacts Documentation: observation, interrogation, audio/video, logs, journals

11. Analysis -

12. Chlorophyll Index Analysis -

13. http://pubs.usgs.gov/fs/2006/3046/ Analysis -

14. http://www2.dickinson.edu/departments/envst/lucewebpages/hypoxia- gurbiszc/lucehome.htm Analysis -

15. Summative Assessment (Student ) Data Acquisition Were data acquired appropriate? Were data adequate in scope and extent? Data Analysis Were data and type of analysis aligned? Were students able to interpret results of analysis? Data Presentation Geospatial skills – graphics production (maps, charts, tables) Delivery – oral articulation, paper, poster presentation, multimedia Prediction and extension – future, results application

16. Summative Assessment (Teacher) Project Articulation Project alignment to learning objectives Project Reflection Time and efficiency vs. learning effectiveness Classroom vs. Real World Novice - expert

17. Presentation -

18. Modeling -