The NSF Course, Curriculum, and Laboratory Improvement CCLI Program

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The NSF Course, Curriculum, and Laboratory
Improvement (CCLI) Program

• CUR Meeting March 2007
• Duncan McBride
• Program Director
• Division of Undergraduate Education
• National Science Foundation
• dmcbride_at_nsf.gov

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Course, Curriculum, and Laboratory Improvement
(CCLI)

• Purpose of the Program
• To improve the quality of STEM education for all
  students by targeting activities affecting
  learning environments, course content, curricula,
  and educational practices
• Supports projects at all levels of undergraduate
  education.
• Supports activities in the classroom, laboratory,
  and field settings
• Current CCLI Program Solicitation (NSF07-543)

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Increased Emphases in CCLI Program

• Building on and contributing to the STEM
  education knowledge base
• Building a community of scholars in STEM
  education
• Identifying project-specific measurable outcomes
• Using them in the project management and
  evaluation

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Three Scales of Projects
Phase 1 Exploratory Projects Up to 150,000
(200,000 when 4-year 2-year schools
collaborate) 1 to 3 years (can occur at a single
institution with primarily local impact) Phase 2
Expansion Projects Up to 500,000 2 to 4
years build on smaller-scale proven ideas.
Diverse users at several institutions Phase 3
Comprehensive Projects Up to 2,000,000 3 to 5
years combine proven results and mature
products. Involve several diverse institutions
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CCLI Cycle of Innovation
Project Components
Developing Faculty Expertise
Creating New Learning Materials and Teaching
Strategies
Implementing Educational Innovations
Research on Undergraduate STEM Teaching and
Learning
Assessing Learning and Evaluating Innovations
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CCLI - Creating New Learning Materials and
Teaching Strategies

• Phase 1 projects can focus on piloting new
  educational materials and instructional
  methodologies Phase 2 projects on larger-scale
  development, broad testing, and assessment.
• Similar to the old proof-of-concept and full
  development CCLI-EMD projects, respectively.
• Phase 1 projects can focus on outcomes at a
  single site, but must include a rigorous
  assessment and community engagement program.
• Can be combined with other components, especially
  faculty development in phase 2.

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CCLI - Developing Faculty Expertise

• Methods that enable faculty to gain expertise
• May range from short-term workshops to sustained
  activities
• Foster new communities of scientists in
  undergraduate education
• Cost-effective professional development
• Diverse group of faculty
• Leading to implementation
• May be combined with other components, especially
  materials development and assessment.

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CCLI - Implementing Educational Innovations

• Approximately equivalent to the CCLI-AI track
  projects. Phase 1 projects generally.
• Projects must result in improved STEM education
  at YOUR institution via implementing exemplary
  materials, laboratory experiences, and/or
  educational practices developed and tested at
  other institutions.
• CCLI-Implementation projects should stand as
  models for broader adaptation in the community.
• Proposals may request funds in any budget
  category supported by NSF, including
  instrumentation

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CCLI - Assessing Learning and Evaluating
Innovations

• Design and test new assessment and evaluation
  tools and processes.
• Apply new and existing tools to conduct
  broad-based assessments
• Must span multiple projects and be of general
  interest

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CCLI - Conducting Research on STEM Teaching and
Learning

• Develop new research on teaching and learning
• Synthesize previous results and theories
• Practical focus
• Testable new ideas
• Impact on STEM educational practices.
• - May be combined with other components

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CCLI Cycle of Innovation
Project Components
Developing Faculty Expertise
Creating New Learning Materials and Teaching
Strategies
Implementing Educational Innovations
Research on Undergraduate STEM Teaching and
Learning
Assessing Learning and Evaluating Innovations
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Important Features of Successful CCLI Projects

• Quality, Relevance, and Impact
• Student Focus
• Use of and Contribution to the STEM Education
  Knowledge Base
• STEM Education Community-Building
• Expected Measurable Outcomes
• Project Evaluation

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Quality, Relevance and Impact

• Innovative
• State-of-the-art products, processes, and ideas
• Latest technology in laboratories and classrooms
• Have broad implication for STEM education
• Even projects that involve a local
  implementation
• Advance knowledge and understanding
• Within the discipline
• Within STEM education in general 

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Student Focus

• Focus on student learning
• Project activities linked to STEM learning
• Consistent with the nature of todays students
• Reflect the students perspective
• Student input in design the project.

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STEM Education Knowledge Base

• Reflect high quality science, technology,
  engineering, and mathematics
• Rationale and methods derived from the existing
  STEM education knowledge base
• Effective approach for adding the results to
  knowledge base

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Community-Building

• Include interactions with
• Investigators working on similar or related
  approaches in PIs discipline and others
• Experts in evaluation, educational psychology or
  other similar fields
• Benefit from the knowledge and experience of
  others
• Engage experts in the development and evaluation
  of the educational innovation

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Expected Measurable Outcomes

• Goals and objectives translated into expected
  measurable outcomes
• Project-specific
• Some expected measurable outcomes on
• Student learning
• Contributions to the knowledge base
• Community building
• Used to monitor progress, guide the project, and
  evaluate its ultimate impact

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Project Evaluation

• Includes strategies for
• Monitoring the project as it evolves
• Evaluating the projects effectiveness when
  completed
• Based on the project-specific expected measurable
  outcomes
• Appropriate for scope of the project

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Lessons from the first year (2006)

• Phase 1 is an open competition many new
  players
• Phase 2 requires substantial demonstrated
  preliminary work
• Phase 3 is for projects from an experienced team
  with a national scale.
• Program for 2008 has no substantive changes from
  2006. Changes may be made for 2009.

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Funding and Deadlines

• 35 million for FY07 (Maybe more)
• Project Deadlines Phase 1 -- May 8 and 9, 2007
  depending on first letter in state name
• January 10, 2008 Phase 2 and Phase 3 proposals

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CCLI Funding 2000-2007
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Merit Review Criteria

• Intellectual merit of the proposed activity
• How important is the proposed activity to
  advancing knowledge and understanding within its
  own field or across different fields?
• How well qualified is the proposer to conduct the
  project?
• How well conceived and organized is the proposed
  activity?
• Is there sufficient access to resources?

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Merit Review Criteria

• Broader impacts of the proposed activity
• How well does the proposed activity advance
  discovery and understanding while promoting
  teaching, training, and learning?
• How well does the proposed activity broaden the
  participation of underrepresented groups?
• To what extent will it enhance the infrastructure
  for research and education?
• Will the results be disseminated broadly to
  enhance scientific and technological
  understanding
• What may be the benefits of the proposed activity
  to society?

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Additional Review Criteria

• Phase 1
• How likely is it that the project will result in
  a successful implementation, prototype, or pilot
  study?
• Phase 2
• based on previously developed and tested
  innovations and implementations?
• more than one component and multiple institutions
  as appropriate
• successfully deliver a mature version of the work

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Additional Review Criteria

• Phase 3
• Based on proven results and mature products?
• Include most of the program components defined in
  the cyclic model
• involve a set of diverse institutions?
• outcomes will have a national impact?
• appropriate plan for sustainability or
  commercialization?

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Relation to Tracks  in Previous Solicitation      

• AI
• Implementing Educational Innovations component
• May include equipment projects
• Likely Phase 1
•  EMD
• Creating Learning Materials and Teaching
  Strategies component, perhaps including some
  other components
• Phase 1 (Proof of Concept) Phase 2 or 3 (Full
  Development)

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Relation to Tracks  in Previous Solicitation
(Cont)

• ASA
• Assessing Learning and Evaluating Innovations
  component
• Phase 1, 2, or 3 
• ND
• Developing Faculty Expertise component
• Now should include other components
• Phase 1, 2, or 3 

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Getting Started

• Start EARLY
• Get acquainted with FASTLANE
• Read the Program Solicitation and follow the
  guidelines
• Learn about the recent DUE awards using PIRS
• Become an NSF reviewer
• Contact (e-mail is best) a program officer to
  discuss your idea. This may cause you to refine
  your idea and may prevent you from applying to
  the wrong program

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Formatting, Fastlane, and Grants.gov

• NSF proposal format requirements
• 15 single-spaced pages
• 10-point or larger font (please use 11 or 12)
• Intellectual Merit and Broader Impact explicit in
  Project Summary
• Fastlane submission
• Web-based software access from any browser
• Mature, well-supported system for NSF
• Accepts many file types, converts to .pdf
• Grants.gov
• Stand-alone software downloaded to local computer
• May eventually be used for any Federal agency
• Still under development and does not support all
  NSF processes (for example, collaborative
  proposals)
• Accepts only .pdf files

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How to Really Know About a Program

• Become a reviewer for the proposals submitted to
  the program.
• Give me a business card
• Send e-mail to dmcbride_at_nsf.gov
• Your name will be added to the database of
  potential reviewers.
• We want to use many new reviewers each year,
  especially for Phase 1.

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Whos Who in DUE

• Biology
• Terry Woodin
• Dan Udovic
• Nancy Palaez
• Chemistry
• Susan Hixson
• Pratibha Varma-Nelson
• Eileen Lewis
• Computer Science
• Dianna Burley
• Mark Burge
• Geosciences
• Keith Sverdrup
• gt Rotator

• Engineering
• Russ Pimmel
• Bevlee Watford
• Sheryl Sorby
• Barbara Anderegg
• Mathematics
• Elizabeth Teles
• Lee Zia
• Dan Mackie
• Physics/Astronomy
• Duncan McBride
• Dan Litynski
• Social Sciences
• Myles Boylan