The study of elementary teachers' professional ethical decision making : developing constructs and verifying process model

• Main Authors: Yi-mei Lee, 李宜玫
• Other Authors: Sieh-hwa Lin
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/23887757818523181096

博士 === 國立臺灣師範大學 === 教育心理與輔導學系 === 94 === The purposes of this study were to construct Elementary Teachers’ Professional Ethical Decision Making Process Model and to verify the goodness of fit between empirically observed data and the model with the theory structure equation modeling (SEM). The participants were 541 university students of studying education program and elementary teachers. The study procedure was seeing scenario first, then writing the questionnaire. The result was not ideally fitted well and waited to modify the model. Between the relations of each latent variable, there were some conclusions: (1) first three predictive variables of intention were sensibility, procedural treatment judgment and responsible behavior. (2) responsible behavior was affected by motivation, reflection and personality, in the other way; procedural treatment was effected by it. (3) the correlation between emphasized moral reasoning and the judgment in this study were very low. It fitted bounded rationality of human being. (4) the hypothesis about the expert teachers and the novice teachers fitted in the same model was rejected, but comparing differences were not so significant, those models were as same as the whole model. Based on the results of the study, the researcher provided three recommendations: First, in future we would enhance teachers’ sensibility by training and communicating, and impel teacher more using reasoning. Moreover, the verified result indicated that we should add more important variables in the model, for example belief for human nature and education, or past experiment, which were interpretative schema. Final, future researches may adopt that subjects could free answer and partly be interviewed, in order to resolve the statistical problems that violated assumption of normality.