Technological Self-efficacy, Learning Motivation, and Selfdirected Learning of Selected Senior High School Students in a Blended Learning Environment
Authors: Liwanag Maryrose F. , Galicia Leomar S. 
Published: June 2023

The differences between online and traditional learning are evident considering many important factors. The study of Al-Maroof et al (2021) reveals that students prefer online learning platforms depending on the content appropriate to their skills and abilities and on the quality of the platform thus meeting their expectations and satisfaction. Zheng (2021) also argues that online learning becomes an avenue for students’ self-directed learning. Moreover, Pan (2020) emphasizes that students' technology self-efficacy influences their self-directed learning, and according to Grande et al (2022) and Anette (2018) intrinsic motivation plays a big role in the student’s self-directed learning. In contrast to traditional university students, students learning online have a high correlation between self-directed learning (SDL) and academic performance. Using SDL as a teaching strategy can help students become more adept at controlling their own teaching-learning process (Khalid et al, 2020). Hence, the researcher was motivated to conduct a study to determine the level of technological self-efficacy, learning motivation, and self-directed learning of selected senior high school students of the University of Perpetual Help System –JONELTA and the relationship of each variable. The findings of this study could serve as a guide for senior high school students for them to realize their technological self-efficacy and the importance of learning motivation to their ability to self-direct their learning and a great significance in the field of education specifically policy makers and curriculum designers of Department of Education, administrators, school principals and senior high school teachers might use as reference for the outcomes in assessing blended learning in private academic institution in order to decide whether or not this modern trend in instruction is viable for other public schools. The researcher utilized the descriptive-correlational method of research using survey questionnaire in gathering data. Statistical method utilized to give credence and reliability to the work. The findings show in terms of level of technological self-efficacy, the average weighted mean of 3.97 revealed that the respondents’ level of technological self-efficacy is high. Meanwhile, for learning motivation, the average weighted mean of 4.10 revealed that the respondents’ have high level of learning motivation in terms of control of learning beliefs (4.23), goal orientation and task value (4.18), intrinsic goal orientation (4.10), teacher support (4.08) and social engagement (3.94. Moreover, the average weighted mean of 4.03 revealed that the respondents had a high level of self-directed learning. An average weighted mean of 4.03 revealed that the respondents have a high level of self-directed learning. Meanwhile, for the relationship between technological self-efficacy, learning motivation and self-directed learning, the findings showed that there was a multiple correlation between the respondents’ level of technological self-efficacy, level of learning motivation, and level of self-directed learning. A value of 0.000 indicated a high level of prediction of the dependent variable (level of self-directed learning). The obtained r square of 0.670 shows that independent variables (technological self-efficacy and learning motivation) explain 67% of the variability of the dependent variable (level of self-directed learning). Further, the ANOVA shows that the independent variables, technological self-efficacy and learning motivation, are significant predictors of the dependent variable, self-directed learning with an F-value of 86.892 and a probability value of 0.000 which is less than the 0.05 significance level. Based on the findings of the study, the following conclusion are drawn: the respondents’ level of technological self-efficacy is high; the respondents are highly motivated to learn which means students are open to learning and participation in the class and the students’ level of self-directed learning is high. Moreover, the higher the students’ technological self-efficacy, the higher their level of learning motivation; the higher the level of students’ learning motivation, the higher the level of their self-directed learning. The higher the level of the students’ technological self-efficacy, the higher the level of their self-directed learning. Finally, technological self-efficacy and learning motivation in terms of intrinsic goal orientation, extrinsic goal orientation, control of learning belief, self-efficacy, task value, and social engagement are significant predictors of the student self-directed learning.