Survey of Robotics in Education, Taxonomy, Applications, and Platforms during COVID-9
Source abstract
Abstract
The coronavirus disease 2019 (COVID-19) is characterized as a disease caused by a novel coronavirus known as severe acute respiratory coronavirus syndrome 2 (SARS-CoV-2; formerly known as 2019-nCoV). In December 2019, COVID-19 began to appear in a few countries. By the beginning of 2020, it had spread to most countries across the world. This is when education challenges began to arise. The COVID-19 crisis led to the closure of thousands of schools and universities all over the world. Such a situation requires reliance on e-learning and robotics education for students to continue their studies to avoid the mingling between people and students. In relation to this alternative learning solution, the present study was conducted. A systematic literature review on educational robotics (ER) keywords between 2015–2020 was carried out for the purpose to review a total of 2253 articles from the selected sources; Scopus (452), Taylor & Francis (311), Science Direct (427), IEEE Xplore (221), and Web of Science (842). This review procedure was labelled as Taxonomy 1. After filtering Taxonomy 1, it was found that 98 scientific articles formed the so-called Taxonomy II that was categorized into six categories: (i) Robotics concepts, (ii) Device, (iii) Robotic applications, (iv) Manufacturing robots, (v) Robotics analysis, and (vi) Education/taxonomy. For this study, only 35 articles in this specific field were selected, of which were then assigned into three categories: (i) Application, (ii) Platform, and (iii) Educational. The results show that the application category carries 17.4%, platform 20%, and education 22.85%. This study serves as the application platform to help students, academics, and researchers.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Teaching and Learning Programming · Modular Robots and Swarm Intelligence · Robot Manipulation and Learning
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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