Asee peer logo

Adapting Pervasive Learning Technologies To A Machine Vision Course

Download Paper |

Conference

2004 Annual Conference

Location

Salt Lake City, Utah

Publication Date

June 20, 2004

Start Date

June 20, 2004

End Date

June 23, 2004

ISSN

2153-5965

Conference Session

Issues in Computer Education

Page Count

9

Page Numbers

9.144.1 - 9.144.9

Permanent URL

https://peer.asee.org/13217

Download Count

53

Request a correction

Paper Authors

author page

Chi Thai

Download Paper |

Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Session 3420

Adapting Pervasive Learning Technologies to Machine Vision Course

Chi N. Thai University of Georgia Biological & Agricultural Engineering Department Athens, GA 30602-4435

Abstract

An IT architecture suitable for teacher-centered active-learning approaches is proposed herein, using gigabit network and video conferencing equipment as well as network control and collaborative learning software. The chosen software approach supports interaction and collaboration features in the lecture delivery task, between teacher and students, as well as between students, within as well as outside of the classroom. This report describes the integration of two collaborative learning software packages "NetSupport Manager" and "Silicon Chalk" in the delivery of an Applied Machine Vision course whereas lecture, demonstration and laboratory activities are merged seamlessly. The system performance for a classroom having 12 student PCs and 1 teacher station is reported herein. This class was offered in Spring 04 but unfortunately no students enrolled for this class, thus we do not have student feedback on this instructional approach at this time.

Introduction

Several reports from the National Research Council1, 2 advocated the adoption of Information Technology to improve student learning at the high school and university levels, but Hilton2 also acknowledged that "Information Technology (IT) is changing at a breathtaking pace, making it virtually impossible to accurately predict its future impact on teaching and learning in undergraduate science, mathematics, engineering, and technology education". Maeroff's3 survey showed that "A Classroom of One" is just around the corner, and Raschke4 predicted that the University, as we know it, will be "deconstructed" in the near future as learning shifts from a teacher-initiated orientation to a more active role from the student. For this purpose, the National Science Foundation had been funding for more than a decade 7 Engineering Coalitions (Academy, ECSEL, Foundation, Gateway, Greenfield, SUCCEED, Synthesis) for researching and disseminating better methodologies for engineering education (http://www.foundationcoalition.org/home/foundationcoalition/engineering_coalitions.html). Recently, we also have Project Catalyst from Bucknell University to train engineering faculty for problem-based learning (http://www.departments.bucknell.edu/projectcatalyst/). DiSessa5 and Shneiderman6 described innovative computing concepts and technologies better suited for human needs, especially in science and engineering education. Interestingly, Shneiderman's active learning approach goes beyond the academic realm to extend to the corporate community or civic

Proceedings of the 2004 American Society for Engineering Education Annual Conference & Exposition Copyright 2004, American Society for Engineering Education

Thai, C. (2004, June), Adapting Pervasive Learning Technologies To A Machine Vision Course Paper presented at 2004 Annual Conference, Salt Lake City, Utah. https://peer.asee.org/13217

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2004 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015