Sharing engineering knowledge is not limited to the classroom setting; it takes place under many different circumstances and settings. Conferences are a good example of one of these settings. Thus, in an effort to foster the knowledge sharing in engineering education, the American Society of Engineering Education Southeast Section (ASEE-SE) hosts a peer-reviewed conference every year. The review process for the conference requires a great amount of communication among the conference organizers, authors and reviewers. As of today, the communication is mainly done through e-mails, which in most cases need to be compiled, processed, and redistributed manually to the different parties involved. This paper describes the first attempt made by the ASEE-SE to develop and implement a web-based system to enhance the review process of the papers submitted to the conference. This system partially automates some of the most common tasks performed by the conference organizers. Thus, it is anticipated that this system will decrease the repetitive workload of the conference organizers and allow more effective and efficient system of sharing knowledge. It is also expected that the system will allow the storage of valuable conference submission information in a centralized location and it will serve as the asis for future enhancements of the review process. Therefore, the project described in this paper has the potential to directly benefit the educational engineering community associated with the ASEE-SE and also indirectly benefit the overall educational engineering community. Background of Knowledge Sharing in Engineering Engineering knowledge sharing is fundamental to promote best practices, create new knowledge and achieve academic and professional excellence [Lee 2003]. Thus, the analysis of knowledge sharing deserves particular attention from both academics and professionals. Engineering knowledge sharing could be analyzed from a variety of perspectives. One perspective for analysis is the characterization of knowledge based on its source. Nanoka and Takeuchi portray this characterization by classifying knowledge as tacit and explicit [Nanoka and Takeuchi 1995]. Tacit knowledge is personal, experiential, and context specific while explicit knowledge is codified, articulated, and published in some way. Another perspective for analyzing knowledge sharing is the setting in which it occurs. These settings are very diverse and include classrooms, laboratories, field trips, peer-discussions, seminars and conferences among others. With the advent of new information technology resources, these settings are changing, thereby impacting the way in which knowledge is shared. According to a 2003 study by the University of California, Berkeley, the amount of data stored in 2002 totaled five exabytes, a staggering volume that could fill roughly half a million libraries full of sharable knowledge. The vast majority of this data was stored on magnetic media such as hard disks. As if this figure were not impressive enough, the study also concluded that this amount is growing at a rate of about 30 percent a year [Gross, 2003]. This study and others like it beg the question of how such large quantities of information are processed and shared in usable form to promote academic and professional excellence. As the amount of knowledge grows, processes by which we share such knowledge must necessarily become more powerful and efficient in order to keep pace. If 1 Assistant Professor in the Construction Program at the University of Southern Mississippi, Box 5137, Hattiesburg, MS, 39406. E-mail: Tulio.Sulbaran@usm.edu. 2 Graduate Research Assistant in the Business Information Technology PhD program at Virginia Tech, 1007 Pamplin Hall, Virginia Tech. Blacksburg, VA 24061. E-mail: firstname.lastname@example.org.
Download Full PDF Version (Non-Commercial Use)