A Structural Model of Meaningful Learning as Predicted by Technological Leadership, Computer Competence and Technology Integration of Public Secondary Schools in Region XI

Morris John  I. Lobetos,

A Structural Model of Meaningful Learning as Predicted by Technological Leadership, Computer Competence and Technology Integration of Public Secondary Schools in Region XI

Abstract:

Meaningful learning experiences of students are enhanced by the use of technology and make the latter as an indispensable partner of educators and administrators. This study aimed to develop a structural model of meaningful learning as predicted by technological leadership, computer competence and technology integration. Quantitative research design was utilized in the study. The participants of the study were the 450 public school teachers in Region 11. Moreover, sets of survey questionnaires were used as instruments to obtain information from the participants. Pearson product moment correlation was used to find the significance of the relationship between the independent and dependent variables. Stepwise multiple regression analysis was used to identify the variables that best predict meaningful learning and likewise Structural Equation Modeling was used to identify the model that best fits meaningful learning. Results of the study revealed that the level of technological leadership, computer competence and technology integration were rated high. Furthermore, technological leadership, computer competence and technology integration were significantly correlated with meaningful learning. Among the five hypothesized model in the study, structural Model 5 was the best fitting structural model. This indicated further that meaningful learning was best anchored on technology integration.