The Relationship between Final-Year Students’ Problems and the Thesis
Keywords:
correlation, final-year students, student problems, thesis writing processAbstract
Final-year university students often face academic and non-academic challenges—such as poor time management, ineffective supervision, psychological pressure, and limited methodological competence—that may delay thesis completion. This study aimed to examine the relationship and predictive contribution of final-year students’ problems to the thesis writing process. A quantitative correlational design was employed. The sample consisted of 40 final-year students selected through purposive sampling, with inclusion criteria of being actively supervised and having completed at least Chapter 1. Data were collected using a structured questionnaire and analyzed with IBM SPSS version 25 through the Kolmogorov–Smirnov normality test, Pearson correlation, and simple linear regression. The results indicated that the data were normally distributed (Sig = 0.200). Pearson correlation revealed a significant positive association between student problems and the thesis writing process (r = 0.458, p = 0.003), suggesting that higher levels of problems are linked to greater hindrance in thesis progress. Regression analysis further showed that student problems accounted for 21.0% of the variance in the thesis writing process (R² = 0.210). These findings confirm that final-year students’ problems are significantly related to and meaningfully predict barriers in thesis writing, highlighting the importance of strengthening time-management support, improving supervision quality, expanding methodological training, and providing psychological assistance to promote timely and effective thesis completion.
References
Ariyanti, A. (2016). Shaping students’ writing skills: The study of fundamental aspects in mastering academic writing. Indonesian Journal of EFL and Linguistics, 1(1).
Barbayannis, G., Bandari, M., Zheng, X., Baquerizo, H., Pecor, K. W., & Ming, X. (2022). Academic stress and mental well-being in college students: Correlations, affected groups, and COVID-19. Frontiers in Psychology, 13, 886344. https://doi.org/10.3389/fpsyg.2022.886344
Bearman, M., Tai, J., Henderson, M., Esterhazy, R., Mahoney, P., & Molloy, E. (2024). Enhancing feedback practices within PhD supervision: A qualitative framework synthesis of the literature. Assessment & Evaluation in Higher Education. Advance online publication. https://doi.org/10.1080/02602938.2024.2307332
Campbell, S., Greenwood, M., Prior, S., Shearer, T., Walkem, K., Young, S., Bywaters, D., & Walker, K. (2020). Purposive sampling: Complex or simple? Research case examples. Journal of Research in Nursing, 25(8), 652–661. https://doi.org/10.1177/1744987120927206
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
Enita, S., & Sumardi, S. (2023). Dialogic feedback on graduate students’ thesis writing supervision: Voices of Indonesian graduate students. AL-ISHLAH: Jurnal Pendidikan, 15(1). https://doi.org/10.35445/alishlah.v15i1.2614
Fu, Y., Wang, Q., Wang, X., et al. (2025). Unlocking academic success: The impact of time management on college students’ study engagement. BMC Psychology, 13, 323. https://doi.org/10.1186/s40359-025-02619-x
IBM Corp. (2017). IBM SPSS Statistics for Windows (Version 25.0) [Computer software]. IBM Corp.
J
uniar, D., van Ballegooijen, W., Kleygrewe, G., van Schaik, A., Passchier, J., & Riper, H. (2025). Stress management interventions for university students in low- and middle-income countries: A systematic review and meta-analysis.
Frontiers in Digital Health, 7, 1603389. https://doi.org/10.3389/fdgth.2025.1603389
Medaille, A., Tokarz, R., Bucy, R., & Beisler, M. (2022). The role of self-efficacy in the thesis-writing experiences of undergraduate honors students. Teaching and Learning Inquiry, 10. https://doi.org/10.20343/teachlearninqu.10.2
Mishra, P., Pandey, C. M., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of Cardiac Anaesthesia, 22(1), 67–72. https://doi.org/10.4103/aca.ACA_157_18
Pascoe, M. C., Hetrick, S. E., & Parker, A. G. (2020). The impact of stress on students in secondary school and higher education. International Journal of Adolescence and Youth, 25(1), 104–112.
https://doi.org/10.1080/02673843.2019.1596823
Schober, P., Boer, C., & Schwarte, L. A. (2018). Correlation coefficients: Appropriate use and interpretation. Anesthesia & Analgesia, 126(5), 1763–1768. https://doi.org/10.1213/ANE.0000000000002864
Svartdal, F., & Løkke, J. A. (2022). The ABC of academic procrastination: Functional analysis of a detrimental habit. Frontiers in Psychology, 13, 1019261. https://doi.org/10.3389/fpsyg.2022.1019261
Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
van Eerde, W., & Klingsieck, K. B. (2018). Overcoming procrastination? A meta-analysis of intervention studies. Educational Research Review, 25, 73–85. https://doi.org/10.1016/j.edurev.2018.08.002
Wilson, R., Joiner, K., & Abbasi, A. (2021). Improving students’ performance with time management skills. Journal of University Teaching and Learning Practice, 18(4). https://doi.org/10.53761/1.18.4.16
Wisniewski, B., Zierer, K., & Hattie, J. (2020). The power of feedback revisited: A meta-analysis of educational feedback research. Frontiers in Psychology, 10, 3087. https://doi.org/10.3389/fpsyg.2019.03087
