NSF CCLI Funding Info June 1999

Course, Curriculum, and Laboratory Improvement (CCLI) NSF99-53



Proposal Due Date: June 7, 1999

Educational Materials Development (CCLI-EMD): (703) 306-1681
Adaptation and Implementation (CCLI-A&I): (703) 306-1671
National Dissemination (CCLI-ND): (703) 306-1668


Educational Materials
                           Proof of Concept
                           (up to $75,000)
                                               Full Development
                                                (up to $500,000)
  Adaptation & Implementation
                           (up to $100,000)
                                            Comprehensive Curriculum
                                                (up to $200,000)
  National Dissemination

                            Large-Scale Faculty Professional Development
                                     (up to $1,000,000)

CISE	Dr. Ruzena Bajcsy, Assistant Director
Engin	Dr. Eugene Wong, Assistant Director



1. Aim at Integration of Technology

Key Phrase: improve distance learning

All DUE programs seek proposals for projects that use current and
emerging technologies to improve learning and teaching in SMET. These
proposals should integrate innovative educational strategies,
appropriate content, and sound evaluation with current technology to
produce more effective learning environments. Projects may also
develop or adapt materials and strategies to improve distance
learning, incorporating effective uses of technology.

The use of technology in education is an important component of the
NSF-wide Knowledge and Distributed Intelligence (KDI) effort (refer to
NSF 99-29). The recent explosive growth in computer power and
connectivity is reshaping relationships among people and
organizations, and transforming the processes of discovery, learning,
and communication. As a result of the technological advances, we have
unprecedented opportunities for providing rapid and efficient access
to enormous amounts of knowledge and information, for studying vastly
more complex systems than was hitherto possible, and for advancing in
fundamental ways our understanding of learning and intelligence in
living and engineered systems. KDI promotes the realization of these
opportunities. Results from KDI will have a major impact on learning
and research in SMET. DUE encourages proposals that apply positive
results from KDI to improve learning and teaching.