1. Pedagogy and Assessment
The what, why, and how behind inquiry-based, integrated instructional units
Susan Singer, Ross Nehm, and Cathy Manduca

2. Wisdom from Learning Science (How People Learn, NRC,1999)
Learning is additive, it builds on current understanding
Understanding is actively constructed
-This requires an engaged learner
-Different people construct/learn most easily in different ways
Learning to learn-metacognition is an important aspect of becoming an expert and is context specific

3. What makes a good activity?

4. A design strategy What do I want them to be able to do?
How will I know that they can do this?
How will they gain the skills, knowledge and experience they need to succeed?
Evaluate results and tune system

5. I3U Design Principles Clear Learning Goals
Integrated into the flow of the class
Brings together content and process
Incorporates reflection and discussion

6. I3U Design Principles Clear Learning Goals
Integrated into the flow of the class
Brings together content and process
Incorporates reflection and discussion

7. Evidence that curricular integration works in undergraduate curricula
Retention of entering engineering majors – 40 to 60%, women and minorities especially low retention
Drexel University (Eli Fromm)
Vertical integration of 4 gateway courses
21% increase in retention
50% increase in on time graduation

8. From Goals to Outcomes: Designing the activity
Students must be engaged to learn- How does the activity engage them?
Students must construct new knowledge incrementally as a results of experience-What experiences will they have in this activity?
Students must refine and connect their knowledge to be able to use it further- How will the activity promote reflection on and application of the new knowledge?
Edelson, 2001, Learning for Use
A Framework for the Design of Technology-Supported Inquiry Activities: Journal of Research in Science Teaching, vol 38, no 3, p

9. NSDL Workshop Report Serc.carleton.edu/usingdata
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 ?
Serc.carleton.edu/usingdata

10. Tools and Techniques
Learning tools and techniques is different than developing a conceptual understanding of the science
Match time on tools to objectives of class
Develop mastery of tool - can you use it creatively
Only master really useful tools-time invested must be on a par with usefullness
Learning tools requires motivation, construction, and refinement.
Provide opportunities for practice outside class or lab

11. Tips for success
Design exercises with student background in mind--an overwhelming or negative early experience with data can be devastating to student confidence.
Create a safety net to support students through the challenges of research.
Develop a balance between guidance and inquiry that is appropriate for the student and the learning objectives.
Create opportunities for students to work with data and tools outside of class or lab.
Match the time spent in learning tools to the goals of course and student proficiency, being careful not to introduce more tools or techniques than students can master.
Reflection, discussion, and reporting are important aspects of the research experience that need to be incorporated in the planning of the exercise.

12. 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

13. A design strategy What do I want them to be able to do?
How will I know that they can do this?
How will they gain the skills, knowledge and experience they need to succeed?
Evaluate results and tune system

14. Thinking Like an Assessor
What is worthy and requiring of understanding?
What would be sufficient and revealing evidence of understanding?
What performance tasks must anchor the unit?
How will I be able to distinguish between those who really understand and those who don’t?
Against what criteria will I distinguish work?
What misunderstandings are likely? How will I check for those?
From Wiggins and McTigue