Simulators in Educational Robotics
A Review
Bibliographic Data
| ID | 22043454 |
|---|---|
| Authors | Sokratis Tselegkaridis (0000-0003-0825-0787, International Hellenic University), Theodosios Sapounidis (0000-0002-0763-2516, International Hellenic University, corresponding author) |
| Year | 2021 |
| Volume | 11 |
| Issue | 1 |
| Pages | 11 |
| Publication date | 2021-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Education Sciences (JOURNAL) |
| Journal identifiers | ISSN: 2227-7102 • E-ISSN: 2227-7102 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/educsci11010011 |
| OpenAlex | W3118819803 |
| Language | EN |
| Citations received | 8 |
| References cited | 27 |
Educational robotics (ER) seems to have a positive effect on students and, in many cases, might help them to successfully assimilate knowledge and skills. Thus, this paper focuses on ER and carries out a literature review on educational robotics simulators with Graphical User Interfaces (GUIs). The review searches for relevant papers which were published in the period 2013–2020 and extracted the characteristics of the simulators used. The simulators that we describe in this article cover various robotic technologies, offering students an easy way to engage with virtual robots and robotics mechanisms, such as wheeled robots or drones. Using these simulators, students might cover their educational needs or prepare themselves for educational robotic competitions by working in as realistic as possible conditions without hardware restrictions. In many cases, simulators might reduce the required cost to obtain a robotic system and increase availability. Focusing on educational robotics simulators, this paper presents seventeen simulators emphasizing key features such as: user’s age, robot’s type and programming language, development platform, capabilities, and scope of the simulator
Educational robotics · Human–computer interaction · Multimedia · Programming language · Robot · Robotic paradigms · Robotics · Computer Science · Experimental Learning in Engineering · Software Testing and Debugging Techniques · Teaching and Learning Programming · Artificial Intelligence
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| Citations per year | 2 |
|---|---|
| Citation span | 2022 - 2026 (5) |
| Highly cited | No |