An innovative educational change: Massive Open Online Courses in robotics and robotic vision

Corke, Peter, Greener, Elizabeth, & Philip, Robyn (2016) An innovative educational change: Massive Open Online Courses in robotics and robotic vision. IEEE Robotics and Automation Magazine, 23(2), pp. 81-89.

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Abstract

In this article, we discuss our experience in developing and implementing two massive open online courses (MOOCs) at Queensland University of Technology (QUT), Brisbane, Australia. The MOOCs, titled Introduction to Robotics and Robotic Vision, each ran for six weeks and comprised online lectures, assessments, programming exercises, and an optional robot-making or vision-system-creating project, respectively. As well as being among the first MOOCs in the world on these topics at the undergraduate level, the QUT MOOCs were innovative in two particular areas: first in the integration of automatically graded MATLAB programming assignments and second in the use of an automated process for student-peer review of project outcomes.

Impact and interest:

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ID Code: 96771
Item Type: Journal Article
Refereed: Yes
Additional Information: IEEE Robotics and Automation Magazine is a unique technology publication which is peer-reviewed, readable and substantive. The Magazine is a forum for articles which fall between the academic and theoretical orientation of scholarly journals and vendor sponsored trade publications. http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=100
Keywords: Robotics, Robotic vision, Massive Open Online Courses (MOOCs), Online learning, HERN
DOI: 10.1109/MRA.2016.2548779
ISSN: 1070-9932
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Control Systems Robotics and Automation (090602)
Australian and New Zealand Standard Research Classification > EDUCATION (130000) > SPECIALIST STUDIES IN EDUCATION (130300) > Educational Technology and Computing (130306)
Divisions: Current > Research Centres > ARC Centre of Excellence for Robotic Vision
Current > Schools > School of Curriculum
Current > QUT Faculties and Divisions > Division of Technology, Information and Learning Support
Current > QUT Faculties and Divisions > Faculty of Education
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2016 IEEE
Copyright Statement: Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Deposited On: 11 Jul 2016 22:36
Last Modified: 15 Jul 2016 05:23

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