This is a SGER request that addresses both industry's and academia's need for computer professionals with solid foundational knowledge in computational thinking. Declining computer science enrollment at all levels is making such a need hard to meet, with the result that experienced practitioners are not fully realizing their potential because they may lack formal training in computer science.
By and large, suitable alternatives to mastery on computing foundation do not exist for the population of computing practitioners. Taking a large number of undergraduate courses in foundational computer science topics is inappropriate because of the time commitment and the fact that such courses are oriented towards students with little experience or domain expertise. Moreover, most graduate courses typically assume this knowledge as a prerequisite.
This SGER project proposes to address this critical need by condensing the foundational knowledge into a set of modules that streamlines its presentation and relates it to practical engineering examples, targeting students with some experience in software development. Such a course will help bridge the gap between the practical nature of todays software systems and the foundations needed to apply advanced techniques and theories to solve real problems.
Intellectual Merit: This project will address the current gap between engineering practice and educational materials related to computational thinking and computer science foundations by: 1. Distilling the essential elements of computational thinking for practicing engineers, 2. Providing ways to relate those concepts to practical applications, 3. Packaging the material in modules that can satisfy diverse backgrounds and needs.
This project team proposes to develop a course that directly addresses the requirements outlined above. Specifically, it will distill and package the set of core, foundational concepts of computational thinking that have stood the test of time and are relevant broadly to professionals working in software development or other disciplines that have a significant computational component, for example computational biology, computational astronomy, etc.
An evaluation strategy will be put in place to assess the quality and effectiveness of the project. The two main areas of evaluation will be evaluation of course content, and evaluation of course delivery.
