Research-oriented teaching of PDC topics in integration with other undergraduate courses at multiple levels: A multi-year report

Abstract

Parallel and distributed computing (PDC) is finding its usage from system, algorithms, and architecture perspectives in research and industries of many domains. Due to its ever-increasing applications and benefits, the need of skilled manpower in the area of PDC is also increasing. It is felt that if the basic knowledge taught through the core course of PDC is supplemented with the discussion of PDC topics in integration with other computer science courses, then it will not only provide the students with more opportunities to ‘think in parallel’, but will also motivate them to harness the best of PDC. In this paper, we present our experiences of performing research-oriented teaching of PDC topics in integration with other undergraduate courses since 2014 to 2016 spread over multiple semesters. The courses mainly include Software Engineering, Computer Networks, Computer Architecture, Network Programming, and Network based Laboratory taught to undergraduate level students of Computer Science and Engineering. Our integration plan is encouraged from the objectives of NSF/TCPP–IEEE core curriculum initiative on PDC. Most of these courses are compulsory courses for undergraduate students of our department. In addition to the goals of the respective courses, we tried to fulfill many pedagogical goals corresponding to the PDC course. The teaching-contents of these courses have been adapted to also cover the aspects of PDC. A well-defined methodology for selection of PDC topics for integration, selection of topics for laboratory projects and home assignments, conduct of examinations (mid-term/end-term), pre-post feedback and evaluation, and other related activities has been planned. The methodology is intended to fulfill the priorly set goals and to achieve the intended learning outcomes (ILOs). This paper presents the methodology used, detailed topics and integration plan of PDC topics along with corresponding bloom levels, ILOs, evaluation strategies, and performance evaluation based on the students’ feedback and statistical analysis. Success of integration has been validated by performing statistical analysis of students’ pre-post feedback and performance in examinations.