Computer science foundation-building courses at the freshman and sophomore levels pose the greatest stumbling blocks to undergraduate students' learning. CS student enrollment has declined over 60% nationwide, even though the demand for skilled professionals was increasing. There is an urgent need for a more effective CS learning model.
The main purpose of this research is to enrich the context of the CS learning process which is important from motivational and educational perspectives. This project investigates a verification-driven learning model that facilitates students' involvement in real-world computing tasks starting from their early computing courses and continuing throughout their entire studies in computing. This model can significantly reduce the prerequisites for students to study real-world problems in their early years. The students are tasked to validate the functionality of software, execute programs, test parts of systems (pre-decomposed subsystems and components), and locate possible errors. Such seemingly complex high-level tasks can be done by novice students because software verification does not require design and implementation, and can be turned into a learn-by-example process with adequate preparation. This kind of preparation is wrapped in a Verification-Driven Learning Case, which defines the configuration to support a verification-driven learning activity, and consists of elements such as the justification of the system's existence, the requirement specification, description of the functionality, a set of test cases, and the decomposition of the system.
The foundation of the verification-driven learning model lies in software testing theories and techniques. Frequent and progressive exercises on verification will prepare the students for formal specifications. To realize the learning model, this project will produce Learning Cases based on faculty research including computer security, bioinformatics, geographic information systems, database and data mining techniques, remote sensing, and fuzzy set techniques. The Learning Cases will expose the students to working software systems that serve a real-world purpose in scientific research, engineering development, or social networks.
This project will particularly advocate computer science education in under-represented minority and woman students. This learning approach will also help adult students who have rich experience in various areas but need to reposition themselves in the work force. The final goal of this project is to revitalize the CS programs and produce more competent graduates capable of computational thinking.
