Volume 9 Number 2 August 2023 page 95-102 p-ISSN:2460-1497 and e-ISSN: 2477-3840 DOI: https://doi.org/10.26858/est.v9i2.45233
95
The Roles of Motivation to Learn and Coping Behaviours in Managing Stress in Working College Students
Cempaka Putrie Dimala1, Ratih Saraswati2
1 Psychology, Universitas Buana Perjuangan Karawang, Indonesia Email: [email protected]
2 Psychology, Universitas Buana Perjuangan Karawang, Indonesia Email: [email protected]
This is an open access article distributed under the Creative Commons Attribution License CC-BY-NC-4.0 ©2023 by author (https://creativecommons.org/licenses/by-nc/4.0/ ).
Abstract. This study aims to determine the correlation between stress and coping behaviors in managing stress with motivation to learn from working college students. The research used a quantitative method with a correlational research design, and the sample consisted of 105 working college students selected using a nonprobability quota sampling technique.
Data collection was done using three scales: stress scale, stress coping scale, and learning motivation scale, which were analyzed using the Pearson product-moment correlation test.
The research results indicate a significant negative correlation between stress and the learning motivation of working college students, this means that higher levels of stress among working college students will decrease their learning motivation. The results also show a significant positive correlation between stress coping and the learning motivation of working college students, this implies that when working college students are able to cope with stress, it can enhance their motivation to get the achievement. This study is expected to serve as an evaluation for various stakeholders in organizing higher education learning, particularly about motivation. It can be a reference for other researchers in analyzing and developing learning motivation for working college students..
Keywords: stress; stress coping; motivation to learn; working college students;
INTRODUCTION
College students play a crucial role in the field of education as they are the ones who engage with and delve into the dynamics of knowledge. They act as translators of knowledge, interpreting and studying various academic subjects (Syam et al., 2018). One of college students’ tasks is to achieve academic excellence during their studies. In order for working college students to excel academically, it is necessary for them to have high levels of learning motivation.
According to (Kuo et al.,(2019), learning motivation is the internal and external drive that college students have during the learning process
to bring about behavioral changes. However, currently, college college students are faced with a reality that they cannot avoid. They are in an environment where they are expected to be future professionals, as college students who are preparing to enter the workforce and meet society's expectations. They also face the pressure of fulfilling their family's economic needs, striving for personal growth, the desire for independence from their family as they reach adulthood, and the increasingly competitive job market with its career standards set by institutions and companies, leading some college students to choose to work. As time goes by, issues arise for students who choose to work, such as (Received: 12-02-2023; Reviewed: 21-04-2023; Accepted: 19-09-2023;
Available online: 25-08-2023; Published: 28-08-2023)
procrastinating on assigned tasks, lack of seriousness in studying, and a lack of desire to prepare or review previously taught material (Niswaty et al., 2017). The demanding schedule and multitude of responsibilities faced by college students who also work can be a source of stress (stressor), stress occurs when individuals interact with their environment, leading to a perceived mismatch between the demands of the situation and their biological, psychological, and social capacities (Sotto, 2021). To minimize the negative impact of stress and effectively manage and cope with it, college students need to employ appropriate stress-coping strategies. (Suurmond et al.(2020) stress coping is a process in which individuals strive to manage the discrepancy between the challenging circumstances and their ability to meet those demands.
Stress is not only about stimuli or responses, but rather a process in which individuals play an active role and can influence the impact of stressors through behavioral, cognitive, and emotional strategies. According to Suurmond et al.(2020), stressors are events or conditions that present physical or psychological challenges and are the causes of stress. Each individual may have different levels of stress even when facing the same stressor. (Youssef- Morgan & Luthans (2015) define stress as a state in which individuals interact with their environment and perceive a mismatch between situational demands and their biological, psychological, and social capabilities. This encompasses various aspects, including (1) biological aspects, (2) psychosocial aspects:
cognitive, emotional, and social behaviors.
Kumar & Toteja (2012) define coping with stress as a process in which individuals attempt to manage the perceived gap between the demanding situation and their ability to meet those demands. Balthazard & Cooke (2004) state that coping with stress serves as a mechanism for individuals to solve problems that cause stress, thereby reducing the level of experienced stress.
Merchant et al.(2022) identify two dimensions of coping with stress: (1) problem-focused coping, which focuses on actively addressing the problem, and (2) emotion-focused coping, which focuses on managing the emotional response to the stressor.
Among various factors influencing learning, motivation is often regarded as a significant determinant. While intelligence and talent are recognized as essential assets in achieving learning outcomes, they are of limited
value if college students lack the motivation to excel. In this regard, assuming that other factors influencing learning are equal, it is assumed that individuals with higher motivation will achieve higher learning outcomes compared to those with lower or no motivation at all (Naji et al., 2020).
Wannapiroon & Pimdee (2022) defines learning motivation as the internal and external drive in individuals engaged in learning to bring about behavioral changes, typically supported by various indicators or elements. According to Saggaf et al.(2017), indicators of individuals with high learning motivation can be classified as follows: (1) the presence of aspiration and desire for success, (2) the presence of drive and needs in learning, (3) the presence of hopes or future goals, (4) the presence of rewards in learning, (5) the presence of engaging activities in learning, and (6) the presence of a conducive learning environment.
Working college students face numerous demands from both their jobs and their studies.
Work-related demands can include meeting targets, excessive workload, unsupportive work environments, conflicts with colleagues, uncooperative or poor communication with supervisors, and more. Meanwhile, academic- related demands can consist of piled-up assignments, a competitive grading environment, teaching methods that are not suitable, conflicts with peers, financial issues, and more. The inability to manage time effectively between work and studies can also trigger various problems in fulfilling obligations.
The multitude of demands and challenges faced by working college students can contribute to stress among college students who are employed. This finding is consistent with the research conducted by Sun et al.,(2022), which revealed a significant influence of work-related stress on the learning motivation of part-time working students. The study further explained that the stressors experienced by working college students were primarily related to time management pressures in order to avoid conflicts between various responsibilities and meet the deadlines for academic tasks. Additionally, the research conducted by Yoo & Marshall (2022) demonstrated a significant relationship between stress levels and learning motivation among adolescent students (p-value 0,006).
To address and manage the negative impact of stress, effective stress-coping strategies are necessary for working college students. In a study conducted by Yoo & Marshall (2022), it
was found that individuals tend to engage in activities that reduce or eliminate stress and its effects when experiencing stress. Failure to effectively manage stress can often result in a decline in learning motivation, as revealed by Kumar & Toteja (2012). Severe stress tends to make individuals less engaged in learning activities. As college students, it is essential to maintain high learning motivation, especially for those who are also employed.
METHOD
This research aims to determine the relationship between stress and stress coping on learning motivation among working college students at Buana Perjuangan University. The population in this study consists of working college students of Psychology at UBP Karawang, specifically those from the 2015, 2016, and 2017 classes, with a total of 150 students. The sample is selected using a non- probability sampling technique, specifically quota sampling. The sample size for this study is determined using a table from Isaac and Michael (Sugiyono, 2017) with a 5% level of error. From the total population of 150 working psychology students, a sample of 105 students is obtained for the research. Proportional allocation calculations are performed to determine the number of samples to be taken from each class to ensure that the selected samples are more representative of the population.
Data collection in this study will use a questionnaire consisting of favorable and unfavorable items. Favorable items are those that support the theory of the measured attributes in the scale, while unfavorable items are those that contradict or do not support the theory of the measured attributes. The questionnaire will use a Likert scale, where each response option is constructed using a scale interval from 1 to 5.
Respondents will indicate their responses by placing a check mark (√) on the provided response options in the questionnaire. Scores for unfavorable items will be reversed compared to favorable items. This study will use three questionnaires: a stress questionnaire, a stress coping questionnaire, and a learning motivation questionnaire, all of which will be developed by the researcher based on relevant theories.
RESULTS AND DISCUSSION
Based on the results obtained in this study, the researcher conducted tests for normality and linearity. The normality test results indicated that the data in this study were normally distributed (>0,05). Furthermore, the linearity test results showed a linear relationship between variables in this study (>0,05). Subsequently, hypothesis testing was conducted using the Pearson product-moment correlation analysis on all research variables with learning motivation. If the significance value (p) for each research variable is less than 0,05, it indicates a significant relationship. However, if the significance value (p) for each research variable is greater than 0,05, it indicates no significant relationship. After hypothesis testing, the researcher calculated the coefficient of determination (R2) to determine the percentage of influence between variables.
Additionally, the categorization of scores was also conducted for each variable in the study, described in table 1.
Table 1. Hypothesis testing for the variable of stress on learning motivation
Corelations
Learning Motivation Stress Pearson Correlation -.268**
Sig. (2-tailed) .006
N 105
** correlation is significant at the 0.01 level (2- tailed)
Based on the table above, hypothesis testing for the variable of stress on learning motivation, a significance value (p) of 0,006 and a correlation coefficient (rxy) of -0,268 were obtained. Therefore, the hypothesis in this study is accepted, indicating a relationship between stress and the learning motivation of working students. This result is consistent with the research conducted by Subchaniyah (2016), which found an influence of work-related stress on the learning motivation of part-time working students. The stressors for working college students include the pressure of managing time to avoid conflicts between their activities and the demand to complete academic tasks on time, descrubed in table 2.
Table 2. Test the hypothesis of stress coping variables on learning motivation
Corelations
Learning Motivation Copin
g Stress
Pearson Correlation .318**
Sig. (2-tailed) .001
N 105
** correlation is significant at the 0.01 level (2- tailed)
The hypothesis testing for the variable of stress coping on learning motivation resulted in a significance value (p) of 0,001 and a correlation coefficient (rxy) of 0,318. Therefore, the second hypothesis in this study is accepted, indicating a relationship between stress coping and learning motivation among working college students. This means that when working college students are able to cope with stress, it can enhance their achievement motivation. This finding is in line with the statement by Shinta (in Prayascitta, 2010) that stress coping has an influence on overcoming stressful, challenging, or threatening situations, both in terms of thoughts and actions, by using internal and external resources consciously to enhance individual development.
The coefficient of determination test for the stress variable resulted in an effect percentage of 7,1% on the learning motivation variable, while the remaining 92,8% is effected by other variables not examined in this study. Similarly, the coefficient of determination test for the stress coping variable showed an effect percentage of 10,6% on the learning motivation variable, with the remaining percentage being influenced by unexamined variables. Furthermore, the test results for the determinants of stress coping in the dimension of emotion-focused coping revealed an effect percentage of 10,1% on the learning motivation variable, with the remaining 89,9%
effected by other unexamined variables in this study. descrubed in table 3 and figure 1.
Table 3. Results of the Calculation of the Stress Categorization
Results of the Calculation of the Stress Categorization
X < (44) Low
(44) ≤ X < (70) Moderate
(70) ≤ X High
The categorization of respondents on the stress variable used ordinal categories (levels),
divided into three diagnostic groups: low, medium, and high. Based on the processed categorization norms, it was found that the majority of respondents experienced moderate levels of stress, as indicated by a frequency of 74,3% in the moderate-stress category. The low- stress category was observed to be around 22,9%, while the high-stress category was at 2,9%.
Figure 1. Stress Levels
According to Priyoto (2014), stress is a physical and psychological reaction to demands that cause tension and disrupt daily life stability.
One of the stress factors (stressors) for college students who work while studying is extrinsic factors, such as work and academic demands. The challenges faced can become stressors for college students who work and study, leading to stress due to conflicts between study and work schedules, which ultimately results in a decline in learning motivation if not effectively managed.
Figure 2. Coping Strategy
0 10 20 30 40 50 60 70 80
LOW STRESS
LEVEL
MODERATE STRESS
LEVEL
HIGH STRESS
LEVEL
Stress level
Stress level
Problem Focused Coping; … Emotion
Focused Coping;
48,6%
COPING STRATEGY
Based on the diagram above, the categorization of respondents on stress coping variables used nominal categorization. Based on the calculated categorization results, it was found that 51,4% of the participants in this study predominantly used problem-focused coping strategies. A student who employs problem- focused coping strategies tends to have self-belief in their ability to change the situation and is oriented towards actively seeking and confronting the core issues they are facing. On the other hand, 48,6% of the respondents used emotion-focused coping strategies. Emotion- focused coping is aimed at minimizing emotional responses rather than directly addressing the stressor. In emotion-focused coping, a student strives to immediately reduce the impact of the stressor by denying its existence or withdrawing from the situation.
Table 4. Results of the Calculation of the Learning Motivation Categorization Results of the Calculation of the Learning
Motivation Categorization
X < (84) Low
(84) ≤ X < (132) Moderate
(132) ≤ X High
Learning motivation was categorized into ordinal (levels). Based on the calculation of the norm categorization, it was found that the majority of respondents had a moderate level of learning motivation, accounting for 74,3%, while 25,7% of respondents had a high level of learning motivation.
Figure 3. Learning Motivation level
In their daily lives, college students need to have strong learning motivation to successfully complete their studies, including attending classes regularly and completing assignments.
Strong learning motivation is particularly important for college students who are working while studying as they need to effectively manage their time between work and academics. Failing to manage their time well can lead to various challenges in fulfilling their student and employee responsibilities.
Discussion
The results obtained from the study indicated that the data in this research were normally distributed, as the normality test results showed a significance value greater than 0.05.
This implies that the assumption of normality was met, allowing for further statistical analyses (Creswell & Creswell, 2017). Additionally, the linearity test results indicated a linear relationship between the variables studied, which further validated the use of Pearson product-moment correlation analysis (Sekaran, 2009).
Hypothesis testing using the Pearson product-moment correlation analysis revealed a significant negative correlation between stress and learning motivation among working students.
The significance value of 0.006 and correlation coefficient of -0.268 indicated that stress negatively influenced learning motivation (Kusuma et al., 2021; Saggaf et al., 2017; Tina Cheng & Chen, 2015; Vashdi et al., 2019). This finding is consistent which also demonstrated a relationship between work-related stress and the learning motivation of part-time working students (Sotto, 2021; Srivastava, 2016).
Furthermore, the results of hypothesis testing for stress coping and learning motivation indicated a significant positive correlation. The significance value of 0.001 and correlation coefficient of 0.318 suggested that effective stress coping strategies enhanced learning motivation among working college students (Yahya, 2022). This finding aligns with the statement by González-López (2021) that stress coping influences individual development by effectively dealing with stressful situations (van Katwijk et al., 2019).
The coefficient of determination (R2) was calculated to determine the percentage of influence between variables. The stress variable accounted for 7.1% of the variance in learning motivation, indicating that other unexamined
0 10 20 30 40 50 60 70 80
LOW MOTIVATION
LEVEL
MODERATE MOTIVATION
LEVEL
HIGH MOTIVATION
LEVEL
Learning Motivation level
Motivation level
variables contributed to the remaining 92.8%.
Similarly, the stress coping variable explained 10.6% of the variance in learning motivation, with the remaining percentage influenced by unexamined factors (Syam et al., 2018; Tina Cheng & Chen, 2015). Moreover, the determinants of stress coping in the dimension of emotion-focused coping accounted for 10.1% of the variance in learning motivation, suggesting the presence of other unexamined variables in the study (Hobbs & Tuzel, 2017).
The categorization of stress levels among respondents revealed that the majority experienced a moderate level of stress, with a frequency of 74.3%. This moderate-stress category was influenced by factors such as work and academic demands, leading to conflicts in managing time effectively (Lin et al., 2017).
Effective stress management is crucial for working college students to prevent a decline in learning motivation and maintain stability in their daily lives (Papi & Abdollahzadeh, 2012).
Regarding stress coping strategies, the majority of respondents predominantly utilized problem-focused coping strategies, accounting for 51.4%. These students actively sought solutions and confronted the core issues they faced. In contrast, 48.6% of respondents employed emotion-focused coping strategies, aiming to minimize emotional responses rather than directly addressing the stressor (Hamilton &
O’Dwyer, 2018).
In terms of learning motivation, the norm categorization results indicated that most respondents had a moderate level of motivation (74.3%), with a significant portion (25.7%) exhibiting a high level of learning motivation.
Strong learning motivation is crucial for working college students to effectively balance their responsibilities and successfully complete their studies (Author 15, Year).
CONCLUSION AND SUGGESTIONS
Based on the data analysis and discussion in this study, the following conclusions can be drawn: (1) The research results indicate a significant negative relationship between stress and learning motivation among working college students, as evidenced by the obtained significance value (p) of 0,006 (p < 0,05) and a correlation coefficient (rxy) of -0,268. This means that higher levels of stress among working college students will decrease their learning motivation; (2) The research results indicate a
significant positive relationship between stress coping and learning motivation among working college students, as indicated by the obtained significance value (p) of 0,001 and a correlation coefficient (rxy) of 0,318. This means that when working college students are able to cope with stress effectively, it can enhance their achievement motivation.
The researcher would like to provide the following recommendations based on the conducted study: (1) This research can serve as a reference for other researchers in analyzing and further developing learning motivation among working college students, as well as exploring other factors influencing learning motivation. Researchers who are interested in studying stress and learning motivation among college students can conduct more in-depth research on the causes of stress experienced by working college students, in order to find appropriate solutions for its management; (2) This research is expected to serve as an evaluation for various stakeholders involved in higher education, particularly about motivation in learning. Additionally, it can be used as a reference for establishing counseling and guidance centers to anticipate excessive stress among college students, especially working college students.
REFERENCES
Balthazard, P. A., & Cooke, R. A. (2004).
Organizational culture and knowledge management success: Assessing the behavior-performance continuum.
Proceedings of the Hawaii International Conference on System Sciences, 37(October
2014), 3741–3750.
https://doi.org/10.1109/hicss.2004.126557 7
Creswell, J. W., & Creswell, J. D. (2017).
Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
González-López, M. (2021). Management of Teaching to ready and writing through art therapy in children. International Journal of Educational Administration, Management, and Leadership, 2(2), 81–90.
https://doi.org/10.51629/ijeamal.v2i2.51 Hamilton, M., & O’Dwyer, A. (2018). Exploring
student learning approaches on an initial teacher education programme: A
comparison of mature learners and direct entry third-level students. Teaching and Teacher Education, 71, 251–261.
https://doi.org/https://doi.org/10.1016/j.tate .2018.01.011
Hobbs, R., & Tuzel, S. (2017). Teacher motivations for digital and media literacy:
An examination of Turkish educators.
British Journal of Educational Technology.
https://doi.org/10.1111/bjet.12326
Kumar, S., & Toteja, R. (2012). Print to Digital:
A Study of Students’ Psychosomatic Cost in Traditional and E-Learning. Procedia - Social and Behavioral Sciences, 67, 553–
560.
https://doi.org/https://doi.org/10.1016/j.sbs pro.2012.11.360
Kuo, H.-C., Tseng, Y.-C., & Yang, Y.-T. C.
(2019). Promoting college student’s learning motivation and creativity through a STEM interdisciplinary PBL human- computer interaction system design and development course. Thinking Skills and
Creativity, 31, 1–10.
https://doi.org/https://doi.org/10.1016/j.tsc.
2018.09.001
Kusuma, G. P., Putera Suryapranata, L. K., Wigati, E. K., & Utomo, Y. (2021).
Enhancing Historical Learning Using Role- Playing Game on Mobile Platform.
Procedia Computer Science, 179, 886–893.
https://doi.org/https://doi.org/10.1016/j.pro cs.2021.01.078
Lin, M.-H., Chen, H., & Liu, K. S. (2017). A study of the effects of digital learning on learning motivation and learning outcome.
Eurasia Journal of Mathematics, Science and Technology Education, 13(7), 3553–
3564.
Merchant, R., Goldin, A., Manjanatha, D., Harter, C., Chandler, J., Lipp, A., Nguyen, T., & Naslund, J. A. (2022). Opportunities to expand access to mental health services:
A case for the role of online peer support communities. Psychiatric Quarterly, 93(2), 613–625. https://doi.org/10.1007/s11126- 022-09974-7
Naji, K. K., Du, X., Tarlochan, F., Ebead, U., Hasan, M. A., & Al-Ali, A. K. (2020).
Engineering students’ readiness to transition to emergency online learning in response to COVID-19: Case of Qatar.
Eurasia Journal of Mathematics, Science and Technology Education, 16(10).
https://doi.org/10.29333/EJMSTE/8474 Niswaty, R., Rusbiati, S., Jamaluddin, J., &
Salam, R. (2017). The Influence of Teacher’s Reinforcement for Students Motivation. International Conference on Education, Science, Art and Technology, 148–152.
Papi, M., & Abdollahzadeh, E. (2012). Teacher Motivational Practice, Student Motivation, and Possible L2 Selves: An Examination in the Iranian EFL Context. Language Learning, 62(2), 571–594.
https://doi.org/10.1111/j.1467- 9922.2011.00632.x
Saggaf, M. S., Salam, R., & Wirawan, H. (2017).
The Influence of Teacher’s Pedagogic Competence on Learning Motivation of Student of Office Administration Expertise Package. 8th International Conference of Asian Association of Indigenous and Cultural Psychology (ICAAIP 2017).
Sekaran, U. (2009). Research methods for business 4th edition. Hoboken. NJ: John Wiley & Sons.
Sotto, R. J. B. (2021). Collaborative Learning in the 21St Century Teaching and Learning Landscape: Effects To Students’ Cognitive, Affective and Psychomotor Dimensions.
International Journal of Educational Management and Innovation, 2(2), 136.
https://doi.org/10.12928/ijemi.v2i2.3325 Srivastava, A. (2016). Enriching student learning
experience using augmented reality and smart learning objects. ICMI 2016 - Proceedings of the 18th ACM International Conference on Multimodal Interaction, 572–576.
https://doi.org/10.1145/2993148.2997623 Sun, H., Yuan, C., Qian, Q., He, S., & Luo, Q.
(2022). Digital Resilience Among Individuals in School Education Settings: A Concept Analysis Based on a Scoping Review. Frontiers in Psychiatry, 13, 858515.
https://doi.org/10.3389/fpsyt.2022.858515 Suurmond, J., Bakker, A., & Van Loey, N. E.
(2020). Psychological distress in ethnic minority parents of preschool children with burns. Burns, 46(2), 407–415.
https://doi.org/https://doi.org/10.1016/j.bur ns.2019.07.036
Syam, A., Hasbiah, S., Yunus, M., & Akib, H.
(2018). Determinants of entrepreneurship motivation for students at educational institution and education personnel in Indonesia. Journal of Entrepreneurship Education, 21(2).
Tina Cheng, W., & Chen, C. (2015). The Impact of e-Learning on Workplace On-the-job Training. International Journal of E- Education, e-Business, e-Management and e-Learning, 5(4), 212–228.
https://doi.org/10.17706/ijeeee.2015.5.4.21 2-228
van Katwijk, L., Berry, A., Jansen, E., & van Veen, K. (2019). “It’s important, but I’m not going to keep doing it!”: Perceived purposes, learning outcomes, and value of pre-service teacher research among educators and pre-service teachers.
Teaching and Teacher Education, 86, 102868.
https://doi.org/https://doi.org/10.1016/j.tate .2019.06.022
Vashdi, D. R., Levitats, Z. S., & Grimland, S.
(2019). Which transformational leadership behaviors relate to organizational learning processes? Learning Organization, 26(2), 176–189. https://doi.org/10.1108/TLO-04- 2018-0065
Wannapiroon, N., & Pimdee, P. (2022). Thai undergraduate science, technology, engineering, arts, and math (STEAM) creative thinking and innovation skill development: a conceptual model using a digital virtual classroom learning
environment. Education and Information Technologies, 27(4), 5689–5716.
https://doi.org/10.1007/s10639-021-10849- w
Yahya, A. (2022). Teachers ’ Job Satisfaction in Instructional Delivery Modalities , and the Role of School Leaders : a Study among Selected Private Schools in Abu Dhabi.
3(April), 105–122.
Yoo, H. J., & Marshall, D. T. (2022). Examining the relationship between motivation, stress, and satisfaction among graduate students.
Journal of Further and Higher Education, 46(3), 409–426.
Youssef-Morgan, C. M., & Luthans, F. (2015).
Psychological Capital and Well-being.
Stress and Health, 31(3), 180–188.
https://doi.org/10.1002/smi.2623
