Teaching citizenship : the primary teachers' view from two districts of Hong Kong

University of Technology, Sydney. Faculty of Education.The literature shows that the teaching of civics and values evolved from religious, normative approach to rational/objective approach to the emphasis on character development. Development in teaching citizenship followed the ideology and social political changes of the surrounding society. Teachers’ views were found to be very important in the implementation of citizenship education. Hong Kong’s Government agreed that citizenship encompasses both self and collective realization (Lee 2001). Many initiatives and guidelines have been produced for moral and civic education since 1980. Budget cuts and teachers’ heavier burden to fulfill the requirements of educational reforms have made implementation difficult. The voice of the primary teachers was seldom heard. This research set out to identify the qualities which primary teachers in Hong Kong associated with “good citizenship”. Teachers were asked to prioritize the qualities of a good citizen, identify influences on the development of good citizens, and describe the development of their own citizenship and the teaching of such content in classrooms and throughout the school. Finally, teachers discussed suggestions for in-service training for teaching citizenship. A translated version of a citizenship survey, focus group and individual interviews were used to collect the data for analysis. This was an exploratory/interpretive research using quantitative and qualitative methods. By using stratified, random sampling procedures (in accordance to the major types of school sponsoring bodies in Hong Kong), the survey was sent to the full time teachers of 12 schools in two districts. 359 responses were collected, representing a 79% response rate. Correlation statistics and factor analysis procedures were used to analyse the quantitative data collected. The qualitative data collected explored the reasons behind the teachers’ choice. Focus groups and individual interviews results revealed the teachers’ view of content of citizenship that fit the students’ needs; best practices in school and classrooms; and types of training and resources needed in teaching citizenship education. The research findings showed primary teachers’ prioritizing on teaching skills, knowledge aspects of citizenship for students. Parents, teachers and friends were identified as influential in the development of citizenship. Teachers acknowledged the importance of helping students learn through processes or experience. Modelling and examples are important too. Results also showed that teachers from religious-based schools had stronger agreement in teaching of citizenship than did teachers from Government schools. Results were discussed, analyzed with reference to literature and previous research, and recommendations were made. The thesis concluded with suggestions for future research

Genetic algorithm-based variable translation wavelet neural network and its application

Author name used in this publication: F. H. F. Leung"Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering"Refereed conference paper2005-2006 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

A study of picture-elicited narratives by Cantonese- speaking children

Thesis (B.Sc)--University of Hong Kong, 1994"A dissertation submitted in partial fulfilment of the requirements for the Bachelor of Science (Speech and Hearing Sciences), The University of Hong Kong, April 29, 1992 [i.e. 1994]"Also available in print.published_or_final_versionSpeech and Hearing SciencesBachelorBachelor of Science in Speech and Hearing Science

An improved genetic algorithm with average-bound crossover and wavelet mutation operations

This paper presents a real-coded genetic algorithm (RCGA) with new genetic operations (crossover and mutation). They are called the average-bound crossover and wavelet mutation. By introducing the proposed genetic operations, both the solution quality and stability are better than the RCGA with conventional genetic operations. A suite of benchmark test functions are used to evaluate the performance of the proposed algorithm. Application examples on economic load dispatch and tuning an associative-memory neural network are used to show the performance of the proposed RCGA. © Springer-Verlag 2006

Real-coded genetic algorithm with average-bound crossover and wavelet mutation for network parameters learning

Author name used in this publication: F. H. F. Leung"Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering"Refereed conference paper2005-2006 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Application of a modified neural fuzzy network and an improved genetic algorithm to speech recognition

This paper presents the recognition of speech commands using a modified neural fuzzy network (NFN). By introducing associative memory (the tuner NFN) into the classification process (the classifier NFN), the network parameters could be made adaptive to changing input data. Then, the search space of the classification network could be enlarged by a single network. To train the parameters of the modified NFN, an improved genetic algorithm is proposed. As an application example, the proposed speech recognition approach is implemented in an eBook experimentally to illustrate the design and its merits. © Springer-Verlag London Limited 2007

On interpretation of graffiti digits and characters for eBooks : neural-fuzzy network and genetic algorithm approach

Author name used in this publication: K. F. LeungCentre for Multimedia Signal Processing, Department of Electronic and Information Engineering2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

On interpretation of Graffiti digits and characters for eBooks: Neural-fuzzy network and genetic algorithm approach

This paper presents the rule optimization, tuning of the membership functions, and optimization of the number of fuzzy rules, of a neural-fuzzy network (NFN) using a genetic algorithm (GA). The objectives are achieved by training a proposed NFN with rule switches. The proposed NFN and GA are employed to interpret graffiti number inputs and commands for electronic books (eBooks)