Leadership Traits Affecting to Digital Citizenship of School Administrators Under The Office of Secondary School Educational Service Area in Northeastern Region

  • saruda chaisuwan School of Creative Educational Management, Panyapiwat Institute of Management
Keywords: Leadership Traits, Digital Citizenship, School Administrators, Secondary School.


The research purposes were as follows: 1) to study leadership traits of school administrators      2) to study digital citizenship of school administrators 3) to study leadership traits affecting to digital citizenship of school administrators under the office of secondary school educational service area in northeastern region. The sample consisted of 250 secondary school directors in northeastern region in 2019. Instrument was questionnaire with rating scales, content validity index item-objective congruence (IOC) was at 0.80 - 1.00, and Cronbach's alpha as 0.933. The statistical methods used to analyze data were mean, standard deviation, Pearson's product moment correlation, stepwise multiple regression analysis.              

The results finding were follow:  1) Leadership traits of school administrators, as a whole and as individual aspect, at highest level. Ethical leadership was rating the highest mean, the second highest mean was characteristic. 2) Digital citizenship of school administrators, as a whole and as individual aspect, at highest level.  Political and social participation dimension was rating the highest mean, the second highest mean was knowledge of media and information dimensions , ethical dimension was rating the lowest mean.            

3) Forecasting variables of leadership traits affecting to digital citizenship of school administrators under the office of secondary school educational service area in northeastern region were found only 3 factors including ethical leadership, instructional leadership, characteristic which multiple correlation coefficient was found at 0.528. with statistically significant at level of .01. The regression coefficient predictive competence was found at 27.9 percent. These could be formed as the regression equations of raw score and standardized score as follows: Z = . 550 (X6) + -.191(X4) + .150 (X1)


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