Noise and Vibration Risk Prevention Virtual Web for Ubiquitous Training
Bibliographic Data
| ID | 20296342 |
|---|---|
| Authors | María Dolores Redel-Macías (0000-0001-5135-9089, Cordoba University), Antonio J Cubero-Atienza (0000-0002-0349-3440, Cordoba University), Jose Miguel Martinez-Valle (Cordoba University), Gerardo Pedrós-Pérez (0000-0003-4585-9786, Cordoba University), Pilar Martínez-Jiménez (0000-0002-8680-5250, Cordoba University) |
| Year | 2015 |
| Volume | 58 |
| Issue | 4 |
| Pages | 303-308 |
| Publication date | 2015-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | IEEE Transactions on Education (JOURNAL) |
| Journal identifiers | ISSN: 0018-9359 • E-ISSN: 1557-9638 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/te.2015.2415769 |
| OpenAlex | W1993538166 |
| Language | EN |
| Citations received | 1 |
| References cited | 22 |
This paper describes a new Web portal offering experimental labs for ubiquitous training of university engineering students in work-related risk prevention. The Web-accessible computer program simulates the noise and machine vibrations met in the work environment, in a series of virtual laboratories that mimic an actual laboratory and provide the corresponding calculations and plots. The main goal of this work is to provide new learning strategies and methodologies to motivate students and challenge them to learn risk prevention strategies for the workplace. Students can perform the virtual experiments before taking their actual laboratory classes and repeat them whenever and as often as they want. Evaluation results show the system was considered very satisfactory, with an average student rating of 8.95 out of a maximum of 10. As well as being used for educational purposes, the program can be used in industry as a decision tool for factory workers and technicians
Human–computer interaction · Multimedia · Noise (video) · Simulation · Virtual Laboratory · Virtual machine · Virtual reality · Work (physics) · Artificial Intelligence · Biomedical and Engineering Education · Computer Science · Engineering · Engineering Education and Pedagogy · Experimental Learning in Engineering
| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |