Abstract
Science and engineering education play a very important role in the industrial development of a country. Although most people are aware of the importance of science, students often find science boring and uninteresting as traditional textbooks only provide static information. Students who achieve better usually have practical experiences related to the subject or have been exposed to interactive learning tools. In order to promote science education development, a learning system based on RFID is proposed to provide personalized learning service. This paper introduces the architecture of the proposed service and the technologies used including RFID and collaborative filtering. The contributions of the proposed system and how the profiles are used to provide personalization are also discussed. Evaluations of the system reveal that the system inspires and nurtures their interest in science.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Bellotti, F., Berta, R., Margarone, M.: User testing a hypermedia tour guide. IEEE Pervasive Computing 1(2), 33–41 (2002)
Davies, N., Cheverst, K., Mitchell, K., Efrat, A.: Using and determining location in a context-sensitive tour guide. IEEE Computer 34(8), 35–41 (2001)
Derntl, M., Hummel, K.A.: Modeling context-aware e-learning scenarios. In: Proc. of the 3rd IEEE International Conference on Pervasive Computing and Communications Workshops, Kauai Island, HI, USA, March 2005, pp. 337–342 (2005)
Facer, K., Joiner, R., Stanton, D., Reid, J., Hull, R., Kirk, D.: Savannah: mobile 75 game and learning. Journal of Computer Assisted Learning 20(4), 399–409 (2004)
Billsus, D., Pazzani, M.J.: Learning collaborative information filters. In: Proc. of International Conference on Machine Learning, Madison, WI, USA, pp. 46–54 (July 1998)
Claypool, M., Gokhale, A., Miranda, T., Murnikov, P., Netes, D., Sartin, M.: Combining Content-Based and Collaborative Filters in an Online Newspaper. In: Proc. of ACM SIGIR Workshop on Recommender Systems, Berkeley, CA (1999)
Good, N., Schafer, J., Konstan, J., Borchers, A., Sarwar, B., Herlocker, J., Riedl, J.: Combining collaborative filtering with personal agents for better recommendations. In: Proc. of the Conference of the American Association of Artificial Intelligence, Orlando, FL, USA, July 1999, pp. 439–446 (1999)
Haverkamp, D.S., Gauch, S.: Intelligent information agents: review and challenges for distributed information sources. Journal of the American Society of Information Science 49(9), 304–311 (1998)
Bahl, P., Padmanabhan, V.N.: RADAR: An in-building RF-based user location and tracking system. In: Proc. of IEEE Computer & Communications Societies, Tel-Aviv, Israel, vol. 2, pp. 775–784 (March 2000)
Ponnusamy, R., Gopal, T.V.: A user adaptive self-proclamative multi-agent based recommendation system design for e-learning digital libraries. In: IEEE Conference on Cybernetics and Intelligent Systems, pp. 1–7 (June 2006)
Wen, Q., He, J.: Personalized recommendation services based on service-oriented architecture. In: IEEE Asia-Pacific Conference on Services Computing, pp. 356–361 (December 2006)
Xi-Zheng, Z.: Building personalized recommendation system in e-commerce using association rule-based mining and classification. In: International Conference on Machine Learning and Cybernetics, vol. 7, pp. 4113–4118 (August 2007)
Zaiane, O.R.: Building a recommender agent for e-learning systems. In: International Conference on Computers in Education, vol. 1, pp. 55–59 (December 2002)
Chen, T., Han, W.-L., Wang, H.-D., Zhou, Y.-X., Xu, B., Zang, B.-Y.: Content recommendation system based on private dynamic user profile. In: International Conference on Machine Learning and Cybernetics, vol. 4, pp. 2112–2118 (August 2007)
Puntheeranurak, S., Tsuji, H.: Mining Web logs for a personalized recommender system. In: 3rd International Conference on Information Technology: Research and Education, pp. 445–448 (June 2005)
Youji, O., Wakita, R., Yano, Y.: Web based self-directed learning environment using learner’s annotation. In: International Conference on Computers in Education, vol. 2, pp. 1207–1211 (December 2002)
Tan, X., Yao, M., Xu, M.: An effective technique for personalization recommendation based on access sequential patterns. In: IEEE Asia-Pacific Conference on Services Computing, pp. 42–46 (December 2006)
Furukawa, M., Watanabe, M., Kinoshita, M., Kakazu, Y.: A mathematical model for learning agents on a multi-agent system. In: IEEE International Symposium on Computational Intelligence in Robotics and Automation, vol. 3, pp. 1369–1374 (July 2003)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Huang, YP., Chang, YT., Sandnes, F.E. (2008). RFID-Based Interactive Learning in Science Museums. In: Sandnes, F.E., Zhang, Y., Rong, C., Yang, L.T., Ma, J. (eds) Ubiquitous Intelligence and Computing. UIC 2008. Lecture Notes in Computer Science, vol 5061. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69293-5_55
Download citation
DOI: https://doi.org/10.1007/978-3-540-69293-5_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69292-8
Online ISBN: 978-3-540-69293-5
eBook Packages: Computer ScienceComputer Science (R0)