Automation Adoption as Predictors of Remote Education of Teachers in Public Elementary Schools

This study aimed to examine the significant relationship between automation adoption and the predictors of remote education among public elementary school teachers. A descriptive-correlational research design was utilized, involving 165 teachers from public schools in Baganga District, Division of Davao Oriental. Data were collected through standardized questionnaires administered via face-to-face surveys. The data were analyzed using mean, standard deviation (SD), multiple regression analysis, and correlation statistics. The findings revealed that teachers rated automation adoption and remote education certainty at a very high level. Correlation analysis revealed that automation adoption significantly relates the predictors of remote education. Moreover, multiple regression analysis indicated that institutional support and technological readiness significantly influenced predictors of remote education, while pedagogical integration did not show a statistically significant impact. Based on these results, it is recommended that school administrators focus on strengthening institutional support and technological readiness to improve teachers’ effectiveness in remote education. It is recommended also to investigate and enhance pedagogical integration further, as its lack of statistical significance may stem from limited teacher training, insufficient practical application in remote settings, or inadequate access to supportive instructional resources.