Remote-Controlled Laboratories of Experimental Physics: Measuring the Stiffness of a Spring

Authors

  • AL Sabri Ahmed LIMAT, Faculty of Sciences Ben M’sik, Hassan II University Casablanca, Morocco
  • Khazri Yassine LIMAT, Faculty of Sciences Ben M’sik, Hassan II University Casablanca, Morocco
  • Moussetad Mohamed LIMAT, Faculty of Sciences Ben M’sik, Hassan II University Casablanca, Morocco
  • Akensous Youness GAGE, Faculty of Sciences Ben M’sik, Hassan II University Casablanca, Morocco
  • Fahli Ahmed Faculty of Sciences and Techniques, Hassan I University Settat, Morocco
  • AL Amoudi Mohamed Faculty of Education, University of Aden

DOI:

https://doi.org/10.14738/tmlai.54.3187

Keywords:

learning, data infrastructures, scientific computer, data services Practical exercises, E-lab, experiences experiences.

Abstract

In modern E-Learning, students and scientists will be able to access Web portals for scientific computer and data infrastructures, thus accessing large collections of data and digital objects using metadata, knowledge management techniques, and specific data services. Students will apply existing scalable Web and grid technologies to access and share scientific data, using educational and computing resources to run scientific Practical exercises. Such an approach will allow the creation of enriched interactive through a real devices and real remote mechanisms that interactively support the exploration of scientific phenomena. Advanced repository and collaboration services will allow students to remotely and securely up- and download science and engineering learning objects. E-lab is essentially created to realize experiments by interacting with real devices that are real remote mechanisms, through an appropriate telecommunications platform, equipped with a dedicated management system and a number of software interfaces and material.  Our works is aiming to : Measurement of the rigidity of a spring. This method translator pedagogical experiences and turn them into reality at an affordable, expand research sources to students.

References

(1) J. V. Nickerson, J. E. Corter, S. K. Esche, and C. Chassapis, “A model for evaluating the effectiveness of remote engineering laboratories and simulations in education,” Comput. Educ., vol. 49, no. 3, pp. 708–725, Nov. 2007.

(2) A. Alexiou, C. Bouras, and E. Giannaka, “Virtual laboratories in education,” in Technology Enhanced Learning, Springer, 2005, pp. 19–28.

(3) O. Dziabenko and J. García-Zubía, IT Innovative practices in secondary schools: Remote experiments, vol. 10. Universidad de Deusto, 2013.

(4) A. A. TALEB, A. FAHLI, and M. MOUSSETAD, “Mise en Oeuvre d’une Télé-Séance de TP de Physique Nucléaire" Rétrodiffusion de Particules α.”

(5) D. MECHTA, “Plate-forme pour les travaux pratiques à distance sur le Web,” Ferhat Abbas, Algrie, 2012.

(6) M. A. Bochicchio and A. Longo, “Hands-On Remote Labs: Collaborative Web Laboratories as a Case Study for IT Engineering Classes,” IEEE Trans. Learn. Technol., vol. 2, no. 4,

pp. 320–330, Oct. 2009.

(7) U. Hernandez-Jayo and J. Garcia-Zubia, “Remote measurement and instrumentation laboratory for training in real analog electronic experiments,” Measurement, vol. 82, pp. 123–134, Mar. 2016.

(8) M. R. Laskar, R. Bhattacharjee, M. S. Giri, and P. Bhattacharya, “Weather Forecasting Using Arduino Based Cube-Sat,” Procedia Comput. Sci., vol. 89, pp. 320–323, 2016.

(9) M. Teng, H. Considine, Z. Nedic, and A. Nafalski, “Current and Future Developments in Remote Laboratory NetLab,” Int. J. Online Eng. IJOE, vol. 12, no. 8, p. 4, Aug. 2016.

(10) C. Depover, F. Orivel, and Institut international de planification de l’éducation, Les pays en développement à l’ère de l’e-learning. Paris: Unesco, Institut international de planification de l’éducation, 2012.

Downloads

Published

2017-09-01

How to Cite

Ahmed, A. S., Yassine, K., Mohamed, M., Youness, A., Ahmed, F., & Mohamed, A. A. (2017). Remote-Controlled Laboratories of Experimental Physics: Measuring the Stiffness of a Spring. Transactions on Machine Learning and Artificial Intelligence, 5(4). https://doi.org/10.14738/tmlai.54.3187

Issue

Section

Special Issue : 1st International Conference on Affective computing, Machine Learning and Intelligent Systems