Title :
Fuzzy-based clustering genetic group model of project practice teaching
Author_Institution :
Software Inst., Jiangxi Univ. of finance & Econ., Nanchang, China
Abstract :
The grouping of software project practice teaching has very important valuable for improving teaching quality. Traditional grouping method, which based on grades of students, is probable that leads to grouping unreasonably, and it affect teaching quality of software project practice. In this paper the fuzzy-based clustering genetic grouping model is present, it makes use of fuzzy clustering to classify the students into types, and then it makes use of genetic algorithm(GA) to divide these classified students into several teaching groups. Fuzzy clustering method based on multi-course grades of student makes classes more abundant and GA makes teaching groups reasonably, so the model provides reliable proof for the software project practice teaching. The practice teaching result shows that the model greatly improves rationality for teaching of software project practice and it is accepted by students and teacher.
Keywords :
computer science education; fuzzy set theory; genetic algorithms; pattern clustering; project management; software engineering; teaching; fuzzy-based clustering genetic group model; genetic algorithm; multicourse student grade; software project practice teaching; Clustering algorithms; Clustering methods; Computer science; Computer science education; Educational institutions; Finance; Genetic algorithms; Simulated annealing; Software engineering; Software quality; Fuzzy Clustering; Genetic Algorithm; Project Practice; Teach Grouping;
Conference_Titel :
Computer Science & Education, 2009. ICCSE '09. 4th International Conference on
Conference_Location :
Nanning
Print_ISBN :
978-1-4244-3520-3
Electronic_ISBN :
978-1-4244-3521-0
DOI :
10.1109/ICCSE.2009.5228570