Starr Clyde Sebial
Starr Clyde L. Sebial is an Associate Professor and the Dean of School of Teacher Education at J.
H. Cerilles State College. He specializes in Mathematics education and teaches a range of
courses at both the undergraduate and graduate levels. His expertise includes advanced
educational statistics, multivariate data analysis, exploratory data analysis (EDA), educational
research, and major courses in Mathematics. Dr. Sebial's doctoral dissertation, titled "Structural
Equation Model on Pro-Social Skills and Expectancy-Value of STEM Students" (Sebial & Mirasol,
2023), was published in the European Journal of Educational Research. This study utilized
structural equation modeling (SEM) to analyze the interrelationship between the mathematics
performance of STEM students in Zamboanga del Sur and their self-regulated learning skills,
grit, and expectancy-value towards STEM.
His current research interests encompass function arts, the integration of dynamic mathematics
software in teaching and learning Mathematics, exploratory data analysis (EDA), and the impact
of computer technology on teaching, learning, and academic policies. Dr. Sebial is an active
member of the Philippine GeoGebra Network, advocating for the enhancement of Mathematics
education through teacher and student training, as well as workshops on integrating GeoGebra
resources. Dr. Sebial's expertise has led to invitations as a resource speaker at international and
local research fora and conferences, where he shares insights on addressing students'
difficulties in Mathematics using dynamic geometry software, as well as utilizing basic and
advanced statistical tools in educational studies.
H. Cerilles State College. He specializes in Mathematics education and teaches a range of
courses at both the undergraduate and graduate levels. His expertise includes advanced
educational statistics, multivariate data analysis, exploratory data analysis (EDA), educational
research, and major courses in Mathematics. Dr. Sebial's doctoral dissertation, titled "Structural
Equation Model on Pro-Social Skills and Expectancy-Value of STEM Students" (Sebial & Mirasol,
2023), was published in the European Journal of Educational Research. This study utilized
structural equation modeling (SEM) to analyze the interrelationship between the mathematics
performance of STEM students in Zamboanga del Sur and their self-regulated learning skills,
grit, and expectancy-value towards STEM.
His current research interests encompass function arts, the integration of dynamic mathematics
software in teaching and learning Mathematics, exploratory data analysis (EDA), and the impact
of computer technology on teaching, learning, and academic policies. Dr. Sebial is an active
member of the Philippine GeoGebra Network, advocating for the enhancement of Mathematics
education through teacher and student training, as well as workshops on integrating GeoGebra
resources. Dr. Sebial's expertise has led to invitations as a resource speaker at international and
local research fora and conferences, where he shares insights on addressing students'
difficulties in Mathematics using dynamic geometry software, as well as utilizing basic and
advanced statistical tools in educational studies.
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Papers by Starr Clyde Sebial
purposive sampling. The study utilized a quantitative research design, specifically a descriptive-correlational research approach to explore the interrelationships of teachers’ facilitation skills, online learning self-efficacy, motivation, and attitude towards Mathematics. Results from Partial Least Squares – Structural Equation Modeling (PLS-SEM) revealed that teachers’ facilitation skills significantly and positively affect online learning self-efficacy (β=.32, p<.01), as well as motivation (β=.17, p<.01) and attitude
toward Mathematics (β=.11, p=.03). Mediation analyses also revealed significant mediating effects of both motivation (β=.13, p<.01) and attitude towards Mathematics (β=.09, p=.02) strengthening the causal relationship between teachers’ facilitation skills and online learning self-efficacy. However, the study revealed no significant sequential- mediating effects of motivation and attitude towards Mathematics (β=.02, p=.27) on the relationship between the two constructs. The significant mediating roles of motivation and attitude highlight the importance of addressing these psychological factors in educational interventions. To foster better online learning outcomes, educators should focus on strategies that enhance student motivation and create positive attitudes towards Mathematics. However, the lack of significant sequential-mediating effects suggests that
motivation and attitude do not have a compounded mediating effect when considered in sequence. This implies that interventions may need to target these mediators independently rather than relying on a cascading effect from one to the other.
purposive sampling. The study utilized a quantitative research design, specifically a descriptive-correlational research approach to explore the interrelationships of teachers’ facilitation skills, online learning self-efficacy, motivation, and attitude towards Mathematics. Results from Partial Least Squares – Structural Equation Modeling (PLS-SEM) revealed that teachers’ facilitation skills significantly and positively affect online learning self-efficacy (β=.32, p<.01), as well as motivation (β=.17, p<.01) and attitude
toward Mathematics (β=.11, p=.03). Mediation analyses also revealed significant mediating effects of both motivation (β=.13, p<.01) and attitude towards Mathematics (β=.09, p=.02) strengthening the causal relationship between teachers’ facilitation skills and online learning self-efficacy. However, the study revealed no significant sequential- mediating effects of motivation and attitude towards Mathematics (β=.02, p=.27) on the relationship between the two constructs. The significant mediating roles of motivation and attitude highlight the importance of addressing these psychological factors in educational interventions. To foster better online learning outcomes, educators should focus on strategies that enhance student motivation and create positive attitudes towards Mathematics. However, the lack of significant sequential-mediating effects suggests that
motivation and attitude do not have a compounded mediating effect when considered in sequence. This implies that interventions may need to target these mediators independently rather than relying on a cascading effect from one to the other.