TY - GEN
T1 - Classification of and search for online laboratory resources using a coding approach
AU - Li, Yaoye
AU - Aziz, El Sayed
AU - Esche, Sven K.
AU - Chassapis, Constantin
PY - 2007
Y1 - 2007
N2 - Numerous resources for online laboratories have been and continue to be developed by many educational institutions around the world. These resources include both remote laboratories, which are based on actual experimental devices accessed remotely, as well as virtual laboratories, which represent software simulations of experiments. While the operation of online laboratories is very effective compared with traditional, on-site laboratories, their development demands vast financial, temporal and personnel resources. In this context, there is an increasing need for a unified method for describing, aggregating and presenting such online laboratory resources in order to allow potential users to easily and efficiently search for them and ultimately use them. In this paper, a coding approach for online laboratory resources is proposed. The coding allows the capturing of the salient attributes of the online laboratory resources and forms the basis for developing highly efficient search algorithms, which can be used to identify appropriate resources for a given set of user requirements. Furthermore, this paper describes a prototype implementation of such a coding approach for online laboratory resources and demonstrates the performance of this prototype system using the online laboratory resources developed and implemented by the authors.
AB - Numerous resources for online laboratories have been and continue to be developed by many educational institutions around the world. These resources include both remote laboratories, which are based on actual experimental devices accessed remotely, as well as virtual laboratories, which represent software simulations of experiments. While the operation of online laboratories is very effective compared with traditional, on-site laboratories, their development demands vast financial, temporal and personnel resources. In this context, there is an increasing need for a unified method for describing, aggregating and presenting such online laboratory resources in order to allow potential users to easily and efficiently search for them and ultimately use them. In this paper, a coding approach for online laboratory resources is proposed. The coding allows the capturing of the salient attributes of the online laboratory resources and forms the basis for developing highly efficient search algorithms, which can be used to identify appropriate resources for a given set of user requirements. Furthermore, this paper describes a prototype implementation of such a coding approach for online laboratory resources and demonstrates the performance of this prototype system using the online laboratory resources developed and implemented by the authors.
KW - Classification
KW - Code
KW - Online laboratory
KW - Remote experiment
KW - Search algorithm
KW - Virtual experiment
UR - http://www.scopus.com/inward/record.url?scp=50049093580&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=50049093580&partnerID=8YFLogxK
U2 - 10.1109/FIE.2007.4417813
DO - 10.1109/FIE.2007.4417813
M3 - Conference contribution
AN - SCOPUS:50049093580
SN - 1424410843
SN - 9781424410842
T3 - Proceedings - Frontiers in Education Conference, FIE
SP - F3G1-F3G6
BT - 37th ASEE/IEEE Frontiers in Education Conference, FIE
T2 - 37th ASEE/IEEE Frontiers in Education Conference, FIE
Y2 - 10 October 2007 through 13 October 2007
ER -