Lecture Notes in Computer Science- P92

Lecture Notes in Computer Science- P92:This year, we received about 170 submissions to ICWL 2008. There were a total of 52 full papers, representing an acceptance rate of about 30%, plus one invited paper accepted for inclusion in this LNCS proceedings. The authors of these accepted papers | 444 Z. Li and X. Zhao The founding process of the optimal group includes the following key steps 1. According to grouping standard the algorithm generates a matrix that consists of the characteristics that need to be similar in the grouping standards and are from the learner s characteristic model. The system assigns all learners into the request K group using Fuzzy C Mean FCM clustering algorithm 2. Pick out a learner from each group as representative who should be kept in the group and others should be deleted from group. In our system the representative may be the arbitrary member in the group. 3. Pick out a learner from learners who have not been assigned into any group then find the group that the selected learner should be assigned to using the data calculation and comparison. Finally assign the learner to the group that has been found. Data calculation includes 1 We calculate the group average distance d base on these characteristics which needs to be similar. 2 We calculate the group average varianceabase on these characteristics that need to be complementary. 3 For each group calculate d-a value. 4 Finds out the group whose d-a value is smallest among existing groups. It is the group that the learner should be assigned to. 4. If all learners have been assigned in a special group then grouping is over else return to 2. In our system we have adopted the ISODATA iterative self-organization data analysis techniques algorithm clustering algorithm. Its advantage is that the algorithm is clear and definite clustering effectiveness is pretty well. However because each iteration needs to calculate the clustering centre again the amount of calculations is tremendous. 7 Conclusion The WBPCLS into which the intelligence course recommendation the optimal group formation and the optimal collaborative partner discovery have been imported support not only collaborative learning but also personal learning. It is able to change learner s passive collaborative style into .

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