Abstract
Technology of e-learning has been gradually applied to all kinds of professional teaching fields. However, practicing and operation in real environment cannot be replaced by the method of e-learning such as multimedia and interactive simulations. The present e-learning system has very limited benefit for course of experiment and practical training, especially for the course which requires to experiment in clean room (ex. MEMS). Thus, the quality and quantity of industrial technology education cannot be improved. In order to overcome obstacles of traditional experiment and practical training course and enhance functions of present e-learning system, the study is going to take sensor network technology as foundation to developed web services system. The system is able to present the students ‘operation and results right away, thus students can be guided appropriately when they face problems during experiment and practical training. Besides, the system is able to record students’ learning process of experiment and practical training. These data of learning process will be helpful for building adaptive u-learning environment for skill-training.
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References
Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A survey on sensor networks. IEEE Communications Magazine 40(8), 102–114 (2002)
Tubaishat, M., Madria, S.: Sensor networks: An overview. IEEE Potentials 22(2), 20–23 (2003)
Dong, M., Tong, L., Sadler, B.M.: Information Retrieval and Processing in Sensor Networks: Deterministic Scheduling Versus Random Access. IEEE Transactions on Signal Processing 55(12), 5806–5820 (2007)
Long, H.B.: Skills for Self-Directed Learning, http://faculty-staff.ou.edu/L/Huey.B.Long-1/articles.htm (retrieved December 15)
Desikan, P., DeLong, C., Beemanapalli, K., Bose, A., Srivastava, J.: Web Mining For Self Directed E-Learning. In: Data Mining for E-Learning. WIT Press (also available as AHPCRC Technical Report –TR # 2005-030)
Paquette, G., Ricciardi-Rigault, C., Paquin, C., Liegeois, S., Bleicher, E.: Developing the Virtual Campus Environment. In: Proceedings of Ed-Media, pp. 244–249 (1996)
Sung, W.T., Ou, S.C.: Using Virtual Reality Technologies for Manufacturing Applications. Int. J. Com. Applications Tech. 17(4), 213–219 (2003)
Craig, A.B., Sherman, W.R.: Understanding Virtual Reality – Interface, Application, and Design. Elsevier Science (Morgan Kaufmann Publishers, Calif., USA (2003)
Bouras, C., Philopoulos, A., Tsiatsos, T.: E-learning through distributed virtual environments. J. Netw. Comput. Appl. 24(3), 175–199 (2001)
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Liu, CC., Wu, DW., Jou, M., Tsai, SJ. (2010). Development of a Sensor Network System for Industrial Technology Education. In: Lytras, M.D., Ordonez De Pablos, P., Ziderman, A., Roulstone, A., Maurer, H., Imber, J.B. (eds) Knowledge Management, Information Systems, E-Learning, and Sustainability Research. WSKS 2010. Communications in Computer and Information Science, vol 111. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16318-0_43
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DOI: https://doi.org/10.1007/978-3-642-16318-0_43
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