INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume X Issue XXVI February 2026| Special Issue on Education  
Influence of Problem-Solving Skills and Emotional Regulation on  
Learner Motivation to Finish Senior High School Program  
Christian Oliver F. Guilaran  
Graduate School Program, Student, Holy Cross of Davao College, Philippines  
DOI: https://doi.org/10.47772/IJRISS.2026.1026EDU0110  
Received: 18 February 2026; Accepted: 24 February 2026; Published: 05 March 2026  
ABSTRACT  
Demotivation to complete schooling is alarming. This study aimed to determine the significance of  
problemsolving skills and emotional regulation in determining motivation to complete schooling. The study used  
a diagnostic research design with 204 Senior High School students selected through simple random sampling,  
employed a survey questionnaire, and analyzed the data using multiple linear regression. The findings show that  
the determinants significantly influence the criterion, partially supporting Resilience Theory. Future studies  
should examine additional variables, such as family and external support systems, to explain the remaining  
47.40% of the variance. At the same time, schools implement programs that strengthen students' problem-solving  
and emotional regulation skills, thereby enhancing motivation to complete schooling.  
Keywords: Problem-solving skills, emotional regulation, motivation to complete schooling, persistence, Senior  
High School.  
INTRODUCTION  
The Problem and Its Scope  
Globally, students often lack motivation to complete their schooling. Studies have revealed that many students  
exhibit low motivation to complete their education (OECD, 2023); research indicates that students who lack  
motivation are less likely to complete their schooling (Szabó et al., 2024).  
In the United States, research indicates that low academic motivation among students is associated with declining  
(Alivernini, 2023). In Europe, educational data show that student disengagement and difficulties in sustaining  
motivation are ongoing concerns (OECD, 2023). In Latin America, student motivation remains a challenge, with  
stagnant learning outcomes (UNESCO, UNICEF, & ECLAC, 2024).  
Studies on student motivation in the Philippines indicate challenges with sustaining academic engagement,  
including motivation, which are associated with increased absenteeism, lower participation, and potential  
withdrawal from schooling (Dominado et al., 2025).  
The effects of demotivation extend beyond individual students to communities and the broader economy.  
Incomplete education can limit employment opportunities and reduce workforce readiness, thereby affecting  
long-term socioeconomic progress.  
Reports indicate that demotivated students are more likely to miss school. Being demotivated is associated with  
lower school engagement. The problem, nonetheless, stems from a lack of interest that initially shapes the type  
of environment and social affiliations they fit into.  
In the local setting, Senior High School Learners are often motivated to finish by the belief that they need to  
secure a job even before completing their studies. This factor contributed to these learners leaving school for  
personal reasons, and left the impression that landing a job is more promising than staying in school and doing  
their assignments.  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume X Issue XXVI February 2026| Special Issue on Education  
Significance of the Study  
This study addresses low student motivation to complete schooling and supports SDG 4 by providing insights  
into improving engagement, reducing dropouts, and promoting quality education. Aligned with DepEd's goals  
by guiding interventions that promote perseverance, encourage self-directed learning, and support the  
development of competent, resilient graduates. It also supports the mission of the Holy Cross of Davao College  
by informing programs that enhance students' motivation, perseverance, and holistic growth.  
Statement of the Problem  
This study aimed to determine the significance of problem-solving skills and emotional regulation in determining  
motivation to complete schooling. Specifically, it aimed to achieve the following learning goals.  
1. To determine the levels of problem-solving skills as indicated by identifying and analyzing problems,  
generating possible solutions, decision-making, and implementation; emotional regulation as indicated by  
managing negative emotions, maintaining emotional balance under stress, and using positive coping  
strategies; and the motivation to finish schooling, indicated by academic persistence, goal-setting,  
commitment, and engagement in learning activities.  
2. To determine the significance of the relationship between problem-solving skills, emotional regulation, and  
motivation to finish schooling.  
3. To determine the significance of the individual and combined degree of influence of problem-solving skills  
and emotional regulation on motivation to finish schooling.  
Hypotheses  
The following hypotheses were formulated and tested at the 0.05 significance level:  
Ho1: Problem-solving skills and emotional regulation are not significantly associated with the motivation to  
complete schooling.  
Ho2: Problem-solving skills and emotional regulation did not significantly influence motivation to complete  
schooling as individual determinants, nor did they influence it as combined determinants.  
THEORETICAL FRAMEWORK  
(Garmezy 1985) Proposed that resilience emerges from the interaction of three major systems: individual  
attributes, family support systems, and external support systems. His theory emphasized that resilience is not a  
fixed trait but a dynamic developmental process in which people learn to manage emotions, solve problems, and  
use available resources to overcome academic, social, and emotional challenges. In education, this means that  
students become more motivated and persistent when they develop coping skills and receive supportive  
environments.  
Conceptual Framework  
In this study, problem-solving skills, as indicated by identifying and analyzing problems, generating possible  
solutions, decision-making, and implementation (D’Zurilla & Goldfried, 1971), served as the individual attribute  
element mentioned in the theory. Emotional regulation, as indicated by managing negative emotions,  
maintaining emotional balance under stress, and using positive coping strategies (Gross & John, 2003), also  
reflected individual attributes. Motivation to finish school, as indicated by academic persistence, goal-setting,  
commitment, and engagement in learning activities (Deci & Ryan, 1985; Deci & Ryan, 2000), served as the  
resilience concept in the theory.  
This study was limited only to the relationship between internal attributes and resilience. Family and external  
support, as factors of resilience, were excluded from the study.  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume X Issue XXVI February 2026| Special Issue on Education  
Figure 1. Conceptual Framework of the Study  
METHODOLOGY  
This chapter describes the methods used in this study, including the research design, respondents, locale,  
instrument, data gathering procedure, and data analysis.  
Research Design  
This study used a diagnostic research design. Diagnostic research design is a quantitative research type that  
investigates the underlying causes of a problem. The design goes beyond mere description, seeking not only  
what is happening but also why it is happening and what factors are associated with it. This design typically  
involves identifying and analyzing variables to determine their relationships and root causes. It explains the  
association between the variables; more or less, it uses cross-sectional data (Research.life. 2023)  
Locale of the Study  
The study conducted in Davao City, a highly urbanized city in southern Philippines, known for its diverse  
population and strong educational sector; It serves as a regional hub for commerce, culture, and public services  
in Mindanao, providing a suitable environment for educational and social research; Its mix of urban and suburban  
communities enables the study to capture a diverse range of socioeconomic and academic contexts.  
Sample and Sampling Technique  
The study selected 204 Senior High School students from public schools enrolled in SY 2025–2026; in the  
study, we used a simple random sampling technique to select the respondents; a probability sampling method in  
which every member of the target population has an equal and known chance of being selected for the sample  
(Ahmed, S.K., 2024).  
Research Instruments  
The researcher rated all questionnaires using a 4-point Likert scale: 4 = strongly agree, 3 = agree, 2 = neither  
agree nor disagree, 1 = strongly disagree.  
Data Gathering Technique  
The data-gathering technique used in this study was a survey technique. In quantitative research, a survey  
questionnaire is a structured instrument consisting of a series of standardized questions designed to  
systematically collect numerical data from respondents on specific variables of interest. This tool allows  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume X Issue XXVI February 2026| Special Issue on Education  
researchers to obtain numerical data that can be statistically analyzed to describe, explain, or test hypotheses  
related to the research problem. Researchers widely use survey questionnaires because they enable efficient data  
collection from large samples in a consistent and comparable format, thereby facilitating the generalizability of  
findings (Ranganathan, 2023).  
Data Analysis  
The data were summarized, sorted, and analyzed using the statistical tools. The researcher used the following  
statistical instruments to analyze the data, with assistance from a statistician.  
Mean and Standard Deviation. The researchers used these instruments to measure the level of problemsolving  
skills, emotional regulation, and motivation of senior High School learners to complete school. The mean  
provided the average level of each variable, while the standard deviation indicated the variability or dispersion  
of the responses. This Analysis addressed the first research question.  
Pearson Correlation (r) indicated that higher problem-solving skills and emotional regulation were positively  
associated with SHS learners' motivation, suggesting that enhancing these skills may increase their drive to  
complete schooling.  
Multiple Linear Regression Analysis. This Analysis examined how problem-solving and emotional regulation  
influenced the motivation of Senior High School learners. The model illustrated the contribution of each skill to  
persistence, highlighting those with the greatest impact and informing strategies to enhance motivation and  
reduce dropout rates.  
Ethical Consideration  
The Society for Moral Integrity and Legal Ethics (SMILE) promotes ethical accountability at the highest level.  
The ethical values of informed consent, privacy, and confidentiality are foundational to ethical and professional  
practice. Privacy and confidentiality ensure individuals' autonomy and control over personal information, and  
the law provides ethical protection and justification for respecting these rights.  
RESULTS  
This section presents descriptions of the variables' levels and indicators, analyses of the variables' relationships,  
and the influence of the predictors on the criteria.  
Descriptive Analysis  
Table 1 presents the descriptive statistics. It contains the study's variables: Problem-solving Skills, Emotional  
Regulation, and Motivation to Finish Schooling. Moreover, it covers the sample size, standard deviation, mean,  
and descriptive interpretation.  
Table 1. Descriptive Analysis, n=204  
Variables  
SD  
Mean Descriptive Level  
0.358 3.17  
0.414 3.19  
0.420 3.16  
0.454 3.16  
0.388 3.06  
High  
High  
High  
High  
High  
Problem-Solving Skills  
Identifying and Analyzing Problems  
Generating Possible Solutions  
Decision-Making and Implementation  
Emotional Regulation  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume X Issue XXVI February 2026| Special Issue on Education  
Managing Negative Emotions  
0.552 3.10  
High  
Maintaining Emotional Balance Under Stress 0.478 2.90  
High  
Using Positive Coping Strategies  
Motivation  
0.481 3.17  
0.387 3.28  
0.401 3.37  
0.485 3.30  
0.469 3.16  
High  
Very High  
Very High  
Very High  
High  
Academic Persistence  
Goal-Setting and Commitment  
Engagement in Learning Activities  
Specifically, the table shows that the problem-solving skills variable had a mean of 3.17, indicating that  
respondents have strong problem-solving skills. Identifying and Analyzing Problems, Generating Possible  
Solutions, Decision-Making, and Implementation were described as high. With a standard deviation of .358,  
the indicators showed strong uniformity. Moreover, the emotional regulation variable had a mean of 3.06,  
indicating that respondents had good problem-solving skills; the researcher described it as high. The researcher  
described all its indicators as high. With a standard deviation of .388, the indicators showed a strong uniform  
response. Lastly, the motivation to finish school variable had a mean of 3.28, indicating that respondents had  
strong problem-solving skills. Two of its indicators were rated very high, and one was rated high. With a standard  
deviation of 0.387, the indicators showed a strong uniformity of perception.  
Correlation Analysis  
Table 2 presents the correlation results. It covers the study's variables, namely problem-solving skills and  
emotional regulation. On the left side of the table is the predictive variable, which represents problemsolving  
skills and emotional regulation. Motivation, as represented by the criterion variable, shows the details and values  
in the table describing the r-value, p-value, decision on the null hypothesis, and interpretation.  
Table 2. Correlation Table  
Variable  
r
p-value  
Decision on Ho (α = 0.05) Interpretation  
Problem-Solving Skills 0.674 p < 0.001 Reject Ho  
Significant  
Significant  
Emotional Regulation  
0.607 p < 0.001 Reject Ho  
Range of r-value  
±0.00 - ±0.19  
±0.20 - ±0.39  
±0.40 - ±0.59  
±0.60 - ±0.79  
±0.80 - ±1.00  
Strength of Correlation  
Interpretation  
Very Weak  
Weak  
Negligible or almost no relationship  
Low degree of relationship  
Moderate  
Strong  
Substantial or fair relationship  
High degree of relationship  
Very Strong  
Very high or near-perfect relationship  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
ISSN No. 2454-6186 | DOI: 10.47772/IJRISS | Volume X Issue XXVI February 2026| Special Issue on Education  
Standard Interpretation of the Correlation Coefficient (r)  
Specifically, the table shows the correlation between problem-solving skills and motivation to finish schooling,  
which obtained a p-value of 0.001, which is less than the 0.05 significance level; hence, the researchers rejected  
the null hypothesis. An r-value of 0.674 indicates a strong, significant relationship between these variables.  
Additionally, the correlation between problem-solving skills and motivation to finish schooling, which obtained  
a p-value of 0.001, which is less than the 0.05 significance level; hence, the researchers rejected the null  
hypothesis. An r-value of 0.674 indicates a strong, significant relationship between these variables. Additionally,  
the correlation between problem-solving skills and motivation to finish schooling obtained a p-value of 0.001,  
which is less than the 0.05 significance level; hence, the researchers rejected the null hypothesis. An R-value of  
0.607 indicates a strong, significant relationship between these variables.  
Comparing the correlations, problem-solving skills showed a slightly stronger association with motivation than  
did emotional regulation, but both variables demonstrated meaningful, positive relationships that influenced  
students' persistence in schooling. In summary, both dependent variables were significant determinants.  
Regression Analysis  
Table 3 presents the regression results. The study includes the following determinants: problem-solving skills  
and emotional regulation, and the criterion variable, motivation to finish schooling. It also includes the beta  
coefficient, standard error, t-value, p-value, decisions on the hypothesis, and corresponding interpretation.  
Table 3. Regression Analysis  
Motivation to Finish Schooling  
Unstandardized  
Coefficients  
Standardized Coefficients  
Determinants  
B
Std.  
Beta  
T
p value  
Decision  
on Ho  
Interpretation  
Error  
0.190  
0.068  
Constant  
0.614  
0.524  
3.234  
7.724  
0.001  
Problem-  
0.485  
0.328  
p<0.001  
Reject Ho  
Reject Ho  
Significant  
Significant  
Solving Skills  
Emotional  
Regulation  
0.328  
0.063  
5.226  
p<0.001  
R = 0.725; R2 = 0.526;  
Adjusted R2 = 0.521; F-value = 99.43; p-value = p<0.001  
Table 3 specifically shows that problem-solving skills had a standardized beta coefficient of 0.485, indicating a  
48.5% influence on motivation to finish schooling. With a p-value of 0.001, which is less than 0.05 degrees of  
confidence, the researcher rejected the null hypothesis. It implies that such a degree of influence is significant.  
Moreover, the emotional regulation variable had an unstandardized beta coefficient of 0.328, indicating a 32.8%  
influence on motivation to finish schooling. With a p-value of 0.001, which is less than 0.05 degrees of  
confidence, the researcher rejected the null hypothesis. It implies that such a degree of influence is significant.  
The combined problem-solving skills and emotional regulation accounted for an R2 of 0.526, indicating a 52.6%  
influence on motivation to finish schooling. With a p-value of 0.001, which is less than 0.05, the researcher  
rejected the null hypothesis. It implies that such a degree of influence is significant.  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
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The regression results indicate that both problem-solving skills and emotional regulation significantly determine  
motivation to finish schooling. However, problem-solving skills contribute more strongly than emotional  
regulation.  
SUMMARY OF FINDINGS  
1. Problem-solving skills and emotional regulation are significantly correlated with motivation to finish  
schooling.  
2. Problem-solving skills and emotional regulation significantly influence motivation to finish schooling as  
individual and combined determinants, respectively.  
DISCUSSION  
This chapter presents the discussion of the findings, conclusions, and recommendations.  
The results show that problem-solving skills and emotional regulation significantly influence motivation  
to complete schooling.  
The study finds that Problem-solving skills and emotional regulation are significantly related to students'  
motivation to complete schooling, supporting Rentzios et al.'s (2025) assertion that emotional regulation and  
emotional intelligence positively influence academic motivation and engagement. Moreover, the study also  
affirms Günaydın, H. D. (2021), that social problem-solving skills were significantly associated with academic  
motivation, indicating that stronger problem-solving abilities are associated with higher motivation to study.  
Lastly, this study supports Usán Supervía et al. (2021) by encouraging that emotional regulation is significantly  
linked to self-efficacy and academic motivation, thereby supporting students’ persistence and performance.  
However, the findings of this study contradict those of Hormillada and Jajalla (2025), who reported that problem-  
solving skills did not directly predict motivation, suggesting that their effect on motivation may be indirect or  
mediated by other factors. Additionally, Hayes et al. (2022) stated that Psychological inflexibility, rather than  
emotional regulation, predicted school satisfaction and dropout intentions, suggesting that regulation alone may  
not determine motivation to finish schooling. The current study also opposed this. Finally, the idea of Thomas  
et al. (2024) that emotional intelligence does not directly predict dropout intention, as motivational factors  
mediate its effect on degree completion, is opposed.  
Problem-solving skills and emotional regulation significantly influence motivation to finish schooling as  
individual and combined determinants, respectively.  
The study's findings show that problem-solving skills and emotional regulation significantly influence students'  
motivation to complete schooling, both individually and in combination, supporting de la Fuente et al. (2023),  
who found that problem-solving ability uniquely contributes to student adjustment, well-being, and academic  
persistence. In addition, the study's findings support Arias et al. (2022), who noted that emotional intelligence,  
including emotional regulation, is significantly correlated with school motivation, suggesting that emotional  
competencies are predictors of academic motivation. Lastly, Mahrous, R.ꢀM. (2025) affirms that emotional  
intelligence positively correlates with learning motivation and academic performance, reinforcing the link  
between emotional regulation and motivation in educational settings.  
The study's results contradict those of Enguídanos et al. (2023), which stated that emotional experiences and  
regulation affect dropout intentions. The study's findings oppose Nieto‑Carracedo, A. (2024), who stated that  
Emotional intelligence indirectly influences academic achievement through factors such as motivation and  
learning strategies, suggesting that emotional regulation alone may not directly determine school motivation or  
completion. Ultimately, this study opposes Sánchez‑Cabrero et al. (2022), who found that the relationship  
between emotional intelligence and academic performance is not direct but occurs through mediators such as  
emotional well‑being and learning strategies, highlighting the complexity of how emotional competencies affect  
schooling outcomes.  
INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN SOCIAL SCIENCE (IJRISS)  
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CONCLUSION  
Based on findings, the researcher concludes that problem-solving skills and emotional regulation together  
significantly impact motivation to finish schooling. Hence, resilience theory is partly supported, stating that  
individual attributes shape resilience. The researchers attributed the study's limitation to its partial focus on the  
family and external support systems.  
RECOMMENDATIONS  
Based on the study's conclusion, researchers may pursue a further regression analysis. Utilizing the other  
remaining variables not covered in this study, such as the family support system and external support system, in  
order to account for the remaining 47.40% variance in motivation to finish schooling. Furthermore, schools may  
implement additional programs and classroom activities that enhance students' problem-solving skills and  
emotional regulation, thereby strengthening motivation to complete schooling.  
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