Susilo, E, Liu, J, Alvarado Rayo, Y et al. (4 more authors) (2016) STORMLab for STEM Education: An Affordable Modular Robotic Kit for Integrated Science, Technology, Engineering, and Math Education. IEEE Robotics and Automation Magazine, 23 (2). pp. 47-55. ISSN 1070-9932
Abstract
The demand for graduates in science, technology, engineering, and math (STEM) has steadily increased in recent decades. In the United States alone, jobs for biomedical engineers are expected to increase by 62% by 2020, and jobs in software development and medical science are expected to increase by 32% and 36%, respectively. Combined with an insufficient number of students enrolled in STEM fields, this will result in about 2.4 million STEM job vacancies by 2018. Therefore, increasing the number of STEM graduates is currently a national priority for many governments worldwide. An effective way to engage young minds in STEM disciplines is to introduce robotic kits into primary and secondary education. The most widely used robotic kits, such as LEGO Mindstorm, VEX Robotics, and Fischertechnik, are composed of libraries of prefabricated parts that are not interoperable among kits from different vendors. As recently surveyed in Kee, alternatives to these popular kits are either highly modular but very expensive (e.g., Kondo, Bioloid, Cubelets, K-Junior V2, and Kephera) and unaffordable for the majority of schools, or single-configuration and lowcost robots (e.g., AERObot, iRobot, and Boe-Bot) with a restricted number of activities possible. An affordable solution that provides a number of interchangeable modules is littleBits. This platform offers a variety of sensing and actuation modules that use magnets to connect, but it lacks programmability, thus limiting students' ability to learn about coding.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2016, IEEE. This is an author produced version of a paper published in IEEE Robotics and Automation Magazine. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Jul 2016 15:25 |
Last Modified: | 13 Apr 2017 03:28 |
Published Version: | http://dx.doi.org/10.1109/MRA.2016.2546703 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Identification Number: | 10.1109/MRA.2016.2546703 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:102505 |