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Please use this identifier to cite or link to this item:
http://hdl.handle.net/1812/988
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| Title: | Adaptive web based module for learning unified modelling language |
| Authors: | Noor Hasrina Bakar |
| Keywords: | Unified Modeling Language UML Learning methods Online learning sites Teaching methods |
| Issue Date: | 2010 |
| Publisher: | University Malaya |
| Abstract: | Every person learns differently. Some may find reading useful, but some may find discussing with others help them retain information more effectively. Various
approaches have been used by Unified Modeling Language (UML) instructors all over
the world to assist students in learning UML. The normal face-to-face meeting in the
classroom for a typical 14-week semester at undergraduate level seems to be insufficient for students to master the subject as well as to equip them with the knowledge that they can apply after graduating. At present, many UML learning sites online were designed to provide the students with additional information beyond the face-to-face classroom interaction. Nevertheless, as to date, the available UML resources online are limited to static-text-based lessons that might only cater for students with verbal learning style. The objective of this study is to combine various approaches of teaching and learning UML that is adaptable to individual’s learning style and knowledge level. To demonstrate that, a prototype for a web-based module is designed and implemented at International Islamic University of Malaysia Department of Electrical and Computer Engineering with the purpose to help students learn UML better. The findings from evaluation and testing conducted suggest positive feedback from students in terms of usefulness and effectiveness of learning. More testing and
evaluation will be carried out to further enhance this UML learning module. |
| Description: | Dissertation (M.C.S.) -- Faculty of Computer Science & Information Technology, University of Malaya, 2010. |
| URI: | http://dspace.fsktm.um.edu.my/handle/1812/988 |
| Appears in Collections: | Masters Dissertations: Computer Science
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