Title: Teaching practice-oriented computer vision courses in COVID-19 pandemic

Authors: Jing Tian

Addresses: Institute of Systems Science, National University of Singapore, 119615, Singapore

Abstract: This paper aims to present an online teaching pedagogic experience for the practice-oriented computer vision course during the COVID-19 pandemic. COVID-19 has been disruptive to the education system worldwide, particularly to the computer vision course that usually requires face-to-face lectures and project collaboration during the study. This paper addresses three fundamental questions in teaching computer vision courses: 1) how to design the course topic and adapt to the online teaching format?; 2) how to conduct hybrid project collaboration in a hybrid mode?; 3) how to conduct the course assessment efficiently online? More specifically, this paper presents the pedagogic experience, including learning objectives, course curriculum structure, teaching methodologies, as well as final holistic assessments. The presented approach is an effective way of teaching practical computer vision courses, as verified by feedback from students. These experiences can be insightful to other lecturers who need to design, develop and deliver similar courses in the post pandemic era.

Keywords: engineering education; computer vision teaching; active learning.

DOI: 10.1504/IJCEELL.2023.134349

International Journal of Continuing Engineering Education and Life-Long Learning, 2023 Vol.33 No.6, pp.581 - 591

Received: 08 Jan 2021
Accepted: 12 Jun 2021
Published online: 19 Oct 2023 *

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