PIIT - Summer Software Teams for CS Students

Many authors have documented the improvement in retention realized through active learning pedagogies [Prince, 2004; Goodman, 2002; Felder, 2000; Hake, 1998; Campbell, 1997; Tinto, 1997; Seymour, 1994; Berry, 1991]. The form of active learning we are suggesting is most akin to "problem based learning (PBL)"; which uses complex, real-world projects to motivate learning [Beasley]. PBL has been shown to develop and improve communication skills, teamwork, leadership and problem solving skills [Matsuura, 2006]. It also has a positive impact on student motivation [Markham, 2003].

During the summer, each college/university will offer at least two real-world software team projects (MTSU will host 3 projects, and NSCC and AAMU will host 2 projects each) provided by one of the partner companies. This component of PIIT will build on the current NSF-CPATH project that is working with area companies to build a database of real-world problems and projects that can be used in various computing classes at MTSU. College students will be able to apply to any of the seven team projects depending on their interest. Each team will be led by a faculty member or a graduate student who will work with the participating company to help the students design and implement a solution to a problem identified by the company. The company must agree to provide a liaison that serves as the "customer"; for the project. Students will experience vague, incomplete, incorrect, and frequently changing specifications instead of the traditional clearly defined course project specifications. They will participate in an actual team that must produce a solution under a deadline. PIIT will carefully select the projects to be confident they can be completed during the summer project time period. The mentor will have a general idea of how to solve the problem, but will allow the team to find its own solution.


This material is based upon work supported by the National Science Foundation under Grant Number 0917840. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.